Release 0.4.0
Nikita Manovich
7 years ago
commit
7d6dcd1c04
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[bandit]
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# B101 : assert_used
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# B102 : exec_used
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# B320 : xml_bad_etree
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# B404 : import_subprocess
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# B406 : import_xml_sax
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# B410 : import_lxml
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skips: B101,B102,B320,B404,B406,B410
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exclude_paths:
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- '**/3rdparty/**'
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/*
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* Copyright (C) 2018 Intel Corporation
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*
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* SPDX-License-Identifier: MIT
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*/
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module.exports = {
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"env": {
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"node": false,
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"browser": true,
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"es6": true,
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"jquery": true,
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"qunit": true,
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},
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"parserOptions": {
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"sourceType": "script",
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},
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"plugins": [
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"security",
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"no-unsanitized",
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"no-unsafe-innerhtml",
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],
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"extends": [
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"eslint:recommended",
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"plugin:security/recommended",
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"plugin:no-unsanitized/DOM",
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"airbnb",
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],
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"rules": {
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"no-new": [0],
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"class-methods-use-this": [0],
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"no-restricted-properties": [0, {
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"object": "Math",
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"property": "pow",
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}],
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"no-param-reassign": [0],
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"no-underscore-dangle": ["error", { "allowAfterThis": true }],
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"no-restricted-syntax": [0, {"selector": "ForOfStatement"}],
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"no-continue": [0],
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"no-unsafe-innerhtml/no-unsafe-innerhtml": 1,
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// This rule actual for user input data on the node.js environment mainly.
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"security/detect-object-injection": 0,
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"indent": ["warn", 4],
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},
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};
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exports.settings = {bullet: '*', paddedTable: false}
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exports.plugins = [
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'remark-preset-lint-recommended',
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'remark-preset-lint-consistent',
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['remark-preset-lint-markdown-style-guide', 'mixed'],
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['remark-lint-no-dead-urls', { skipOffline: true }],
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['remark-lint-maximum-line-length', 120],
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['remark-lint-maximum-heading-length', 120],
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['remark-lint-strong-marker', "*"],
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['remark-lint-emphasis-marker', "_"],
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['remark-lint-unordered-list-marker-style', "-"],
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['remark-lint-ordered-list-marker-style', "."],
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['remark-lint-no-file-name-irregular-characters', false],
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['remark-lint-list-item-spacing', false],
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]
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sudo: required
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language: python
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python:
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- "3.5"
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services:
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- docker
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before_script:
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- docker-compose -f docker-compose.yml -f docker-compose.ci.yml up --build -d
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script:
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- docker exec -it cvat /bin/bash -c 'tests/node_modules/.bin/karma start tests/karma.conf.js'
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### There are some additional components for CVAT
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* [NVIDIA CUDA](cuda/README.md)
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* [OpenVINO](openvino/README.md)
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* [Tensorflow Object Detector](tf_annotation/README.md)
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* [Analytics](analytics/README.md)
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## Auto annotation
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### Description
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The application will be enabled automatically if
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[OpenVINO™ component](../../../components/openvino)
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is installed. It allows to use custom models for auto annotation. Only models in
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OpenVINO™ toolkit format are supported. If you would like to annotate a
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task with a custom model please convert it to the intermediate representation
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(IR) format via the model optimizer tool. See [OpenVINO documentation](https://software.intel.com/en-us/articles/OpenVINO-InferEngine) for details.
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### Usage
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To annotate a task with a custom model you need to prepare 4 files:
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1. __Model config__ (*.xml) - a text file with network configuration.
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1. __Model weights__ (*.bin) - a binary file with trained weights.
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1. __Label map__ (*.json) - a simple json file with `label_map` dictionary like
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object with string values for label numbers.
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Example:
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```json
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{
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"label_map": {
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"0": "background",
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"1": "aeroplane",
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"2": "bicycle",
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"3": "bird",
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"4": "boat",
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"5": "bottle",
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"6": "bus",
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"7": "car",
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"8": "cat",
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"9": "chair",
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"10": "cow",
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"11": "diningtable",
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"12": "dog",
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"13": "horse",
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"14": "motorbike",
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"15": "person",
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"16": "pottedplant",
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"17": "sheep",
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"18": "sofa",
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"19": "train",
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"20": "tvmonitor"
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}
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}
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```
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1. __Interpretation script__ (*.py) - a file used to convert net output layer
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to a predefined structure which can be processed by CVAT. This code will be run
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inside a restricted python's environment, but it's possible to use some
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builtin functions like __str, int, float, max, min, range__.
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Also two variables are available in the scope:
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- __detections__ - a list of dictionaries with detections for each frame:
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* __frame_id__ - frame number
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* __frame_height__ - frame height
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* __frame_width__ - frame width
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* __detections__ - output np.ndarray (See [ExecutableNetwork.infer](https://software.intel.com/en-us/articles/OpenVINO-InferEngine#inpage-nav-11-6-3) for details).
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- __results__ - an instance of python class with converted results.
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Following methods should be used to add shapes:
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```python
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# xtl, ytl, xbr, ybr - expected values are float or int
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# label - expected value is int
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# frame_number - expected value is int
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# attributes - dictionary of attribute_name: attribute_value pairs, for example {"confidence": "0.83"}
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add_box(self, xtl, ytl, xbr, ybr, label, frame_number, attributes=None)
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# points - list of (x, y) pairs of float or int, for example [(57.3, 100), (67, 102.7)]
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# label - expected value is int
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# frame_number - expected value is int
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# attributes - dictionary of attribute_name: attribute_value pairs, for example {"confidence": "0.83"}
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add_points(self, points, label, frame_number, attributes=None)
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add_polygon(self, points, label, frame_number, attributes=None)
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add_polyline(self, points, label, frame_number, attributes=None)
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```
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### Examples
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#### [Person-vehicle-bike-detection-crossroad-0078](https://github.com/opencv/open_model_zoo/blob/2018/intel_models/person-vehicle-bike-detection-crossroad-0078/description/person-vehicle-bike-detection-crossroad-0078.md) (OpenVINO toolkit)
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__Links__
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- [person-vehicle-bike-detection-crossroad-0078.xml](https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-vehicle-bike-detection-crossroad-0078/FP32/person-vehicle-bike-detection-crossroad-0078.xml)
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- [person-vehicle-bike-detection-crossroad-0078.bin](https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/person-vehicle-bike-detection-crossroad-0078/FP32/person-vehicle-bike-detection-crossroad-0078.bin)
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__Task labels__: person vehicle non-vehicle
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__label_map.json__:
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```json
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{
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"label_map": {
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"1": "person",
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"2": "vehicle",
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"3": "non-vehicle"
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}
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}
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```
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__Interpretation script for SSD based networks__:
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```python
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def clip(value):
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return max(min(1.0, value), 0.0)
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for frame_results in detections:
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frame_height = frame_results["frame_height"]
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frame_width = frame_results["frame_width"]
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frame_number = frame_results["frame_id"]
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for i in range(frame_results["detections"].shape[2]):
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confidence = frame_results["detections"][0, 0, i, 2]
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if confidence < 0.5:
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continue
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results.add_box(
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xtl=clip(frame_results["detections"][0, 0, i, 3]) * frame_width,
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ytl=clip(frame_results["detections"][0, 0, i, 4]) * frame_height,
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xbr=clip(frame_results["detections"][0, 0, i, 5]) * frame_width,
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ybr=clip(frame_results["detections"][0, 0, i, 6]) * frame_height,
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label=int(frame_results["detections"][0, 0, i, 1]),
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frame_number=frame_number,
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attributes={
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"confidence": "{:.2f}".format(confidence),
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},
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)
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```
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#### [Landmarks-regression-retail-0009](https://github.com/opencv/open_model_zoo/blob/2018/intel_models/landmarks-regression-retail-0009/description/landmarks-regression-retail-0009.md) (OpenVINO toolkit)
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__Links__
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- [landmarks-regression-retail-0009.xml](https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.xml)
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- [landmarks-regression-retail-0009.bin](https://download.01.org/openvinotoolkit/2018_R5/open_model_zoo/landmarks-regression-retail-0009/FP32/landmarks-regression-retail-0009.bin)
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__Task labels__: left_eye right_eye tip_of_nose left_lip_corner right_lip_corner
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__label_map.json__:
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```json
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{
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"label_map": {
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"0": "left_eye",
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"1": "right_eye",
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"2": "tip_of_nose",
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"3": "left_lip_corner",
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"4": "right_lip_corner"
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}
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}
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```
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__Interpretation script__:
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```python
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def clip(value):
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return max(min(1.0, value), 0.0)
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for frame_results in detections:
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frame_height = frame_results["frame_height"]
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frame_width = frame_results["frame_width"]
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frame_number = frame_results["frame_id"]
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for i in range(0, frame_results["detections"].shape[1], 2):
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x = frame_results["detections"][0, i, 0, 0]
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y = frame_results["detections"][0, i + 1, 0, 0]
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results.add_points(
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points=[(clip(x) * frame_width, clip(y) * frame_height)],
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label=i // 2, # see label map and model output specification,
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frame_number=frame_number,
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)
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```
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# Copyright (C) 2018 Intel Corporation
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#
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# SPDX-License-Identifier: MIT
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from cvat.settings.base import JS_3RDPARTY, CSS_3RDPARTY
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default_app_config = 'cvat.apps.auto_annotation.apps.AutoAnnotationConfig'
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JS_3RDPARTY['dashboard'] = JS_3RDPARTY.get('dashboard', []) + ['auto_annotation/js/dashboardPlugin.js']
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CSS_3RDPARTY['dashboard'] = CSS_3RDPARTY.get('dashboard', []) + ['auto_annotation/stylesheet.css']
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# Copyright (C) 2018 Intel Corporation
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#
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# SPDX-License-Identifier: MIT
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from django.apps import AppConfig
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class AutoAnnotationConfig(AppConfig):
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name = "cvat.apps.auto_annotation"
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def ready(self):
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from .permissions import setup_permissions
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setup_permissions()
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# Copyright (C) 2018 Intel Corporation
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#
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# SPDX-License-Identifier: MIT
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import cv2
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class ImageLoader():
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def __init__(self, image_list):
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self.image_list = image_list
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def __getitem__(self, i):
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return self.image_list[i]
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def __iter__(self):
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for imagename in self.image_list:
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yield self._load_image(imagename)
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def __len__(self):
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return len(self.image_list)
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@staticmethod
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def _load_image(path_to_image):
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return cv2.imread(path_to_image)
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||||||
@ -0,0 +1,37 @@
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|||||||
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# Copyright (C) 2018 Intel Corporation
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||||||
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#
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||||||
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# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
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from openvino.inference_engine import IENetwork, IEPlugin
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||||||
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import subprocess
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import os
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||||||
|
|
||||||
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_IE_PLUGINS_PATH = os.getenv("IE_PLUGINS_PATH", None)
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|
||||||
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||||||
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def _check_instruction(instruction):
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|
return instruction == str.strip(
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|
subprocess.check_output(
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|
'lscpu | grep -o "{}" | head -1'.format(instruction), shell=True
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).decode('utf-8')
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)
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def make_plugin():
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if _IE_PLUGINS_PATH is None:
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raise OSError('Inference engine plugin path env not found in the system.')
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||||||
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plugin = IEPlugin(device='CPU', plugin_dirs=[_IE_PLUGINS_PATH])
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if (_check_instruction('avx2')):
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plugin.add_cpu_extension(os.path.join(_IE_PLUGINS_PATH, 'libcpu_extension_avx2.so'))
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elif (_check_instruction('sse4')):
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plugin.add_cpu_extension(os.path.join(_IE_PLUGINS_PATH, 'libcpu_extension_sse4.so'))
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||||||
|
else:
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raise Exception('Inference engine requires a support of avx2 or sse4.')
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||||||
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return plugin
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|
||||||
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|
||||||
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def make_network(model, weights):
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return IENetwork.from_ir(model = model, weights = weights)
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@ -0,0 +1,39 @@
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|||||||
|
# Generated by Django 2.1.3 on 2019-01-24 14:05
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|
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import cvat.apps.auto_annotation.models
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from django.conf import settings
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|
import django.core.files.storage
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|
from django.db import migrations, models
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||||||
|
import django.db.models.deletion
|
||||||
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|
||||||
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|
||||||
|
class Migration(migrations.Migration):
|
||||||
|
|
||||||
|
initial = True
|
||||||
|
|
||||||
|
dependencies = [
|
||||||
|
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
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||||||
|
]
|
||||||
|
|
||||||
|
operations = [
|
||||||
|
migrations.CreateModel(
|
||||||
|
name='AnnotationModel',
|
||||||
|
fields=[
|
||||||
|
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
|
||||||
|
('name', cvat.apps.auto_annotation.models.SafeCharField(max_length=256)),
|
||||||
|
('created_date', models.DateTimeField(auto_now_add=True)),
|
||||||
|
('updated_date', models.DateTimeField(auto_now_add=True)),
|
||||||
|
('model_file', models.FileField(storage=django.core.files.storage.FileSystemStorage(), upload_to=cvat.apps.auto_annotation.models.upload_path_handler)),
|
||||||
|
('weights_file', models.FileField(storage=django.core.files.storage.FileSystemStorage(), upload_to=cvat.apps.auto_annotation.models.upload_path_handler)),
|
||||||
|
('labelmap_file', models.FileField(storage=django.core.files.storage.FileSystemStorage(), upload_to=cvat.apps.auto_annotation.models.upload_path_handler)),
|
||||||
|
('interpretation_file', models.FileField(storage=django.core.files.storage.FileSystemStorage(), upload_to=cvat.apps.auto_annotation.models.upload_path_handler)),
|
||||||
|
('shared', models.BooleanField(default=False)),
|
||||||
|
('primary', models.BooleanField(default=False)),
|
||||||
|
('framework', models.CharField(default=cvat.apps.auto_annotation.models.FrameworkChoice('openvino'), max_length=32)),
|
||||||
|
('owner', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL)),
|
||||||
|
],
|
||||||
|
options={
|
||||||
|
'default_permissions': (),
|
||||||
|
},
|
||||||
|
),
|
||||||
|
]
|
||||||
@ -0,0 +1,47 @@
|
|||||||
|
|
||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
import json
|
||||||
|
import cv2
|
||||||
|
import os
|
||||||
|
import subprocess
|
||||||
|
|
||||||
|
from cvat.apps.auto_annotation.inference_engine import make_plugin, make_network
|
||||||
|
|
||||||
|
class ModelLoader():
|
||||||
|
def __init__(self, model, weights):
|
||||||
|
self._model = model
|
||||||
|
self._weights = weights
|
||||||
|
|
||||||
|
IE_PLUGINS_PATH = os.getenv("IE_PLUGINS_PATH")
|
||||||
|
if not IE_PLUGINS_PATH:
|
||||||
|
raise OSError("Inference engine plugin path env not found in the system.")
|
||||||
|
|
||||||
|
plugin = make_plugin()
|
||||||
|
network = make_network(self._model, self._weights)
|
||||||
|
|
||||||
|
supported_layers = plugin.get_supported_layers(network)
|
||||||
|
not_supported_layers = [l for l in network.layers.keys() if l not in supported_layers]
|
||||||
|
if len(not_supported_layers) != 0:
|
||||||
|
raise Exception("Following layers are not supported by the plugin for specified device {}:\n {}".
|
||||||
|
format(plugin.device, ", ".join(not_supported_layers)))
|
||||||
|
|
||||||
|
self._input_blob_name = next(iter(network.inputs))
|
||||||
|
self._output_blob_name = next(iter(network.outputs))
|
||||||
|
|
||||||
|
self._net = plugin.load(network=network, num_requests=2)
|
||||||
|
input_type = network.inputs[self._input_blob_name]
|
||||||
|
self._input_layout = input_type if isinstance(input_type, list) else input_type.shape
|
||||||
|
|
||||||
|
def infer(self, image):
|
||||||
|
_, _, h, w = self._input_layout
|
||||||
|
in_frame = image if image.shape[:-1] == (h, w) else cv2.resize(image, (w, h))
|
||||||
|
in_frame = in_frame.transpose((2, 0, 1)) # Change data layout from HWC to CHW
|
||||||
|
return self._net.infer(inputs={self._input_blob_name: in_frame})[self._output_blob_name].copy()
|
||||||
|
|
||||||
|
|
||||||
|
def load_label_map(labels_path):
|
||||||
|
with open(labels_path, "r") as f:
|
||||||
|
return json.load(f)["label_map"]
|
||||||
@ -0,0 +1,390 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
import django_rq
|
||||||
|
import fnmatch
|
||||||
|
import numpy as np
|
||||||
|
import os
|
||||||
|
import rq
|
||||||
|
import shutil
|
||||||
|
import tempfile
|
||||||
|
|
||||||
|
from django.db import transaction
|
||||||
|
from django.utils import timezone
|
||||||
|
from django.conf import settings
|
||||||
|
|
||||||
|
from cvat.apps.engine.log import slogger
|
||||||
|
from cvat.apps.engine.models import Task as TaskModel
|
||||||
|
from cvat.apps.engine.serializers import LabeledDataSerializer
|
||||||
|
from cvat.apps.engine.annotation import put_task_data, patch_task_data
|
||||||
|
|
||||||
|
from .models import AnnotationModel, FrameworkChoice
|
||||||
|
from .model_loader import ModelLoader
|
||||||
|
from .image_loader import ImageLoader
|
||||||
|
|
||||||
|
def _remove_old_file(model_file_field):
|
||||||
|
if model_file_field and os.path.exists(model_file_field.name):
|
||||||
|
os.remove(model_file_field.name)
|
||||||
|
|
||||||
|
def _update_dl_model_thread(dl_model_id, name, is_shared, model_file, weights_file, labelmap_file,
|
||||||
|
interpretation_file, run_tests, is_local_storage, delete_if_test_fails):
|
||||||
|
def _get_file_content(filename):
|
||||||
|
return os.path.basename(filename), open(filename, "rb")
|
||||||
|
|
||||||
|
def _delete_source_files():
|
||||||
|
for f in [model_file, weights_file, labelmap_file, interpretation_file]:
|
||||||
|
if f:
|
||||||
|
os.remove(f)
|
||||||
|
|
||||||
|
def _run_test(model_file, weights_file, labelmap_file, interpretation_file):
|
||||||
|
test_image = np.ones((1024, 1980, 3), np.uint8) * 255
|
||||||
|
try:
|
||||||
|
_run_inference_engine_annotation(
|
||||||
|
data=[test_image,],
|
||||||
|
model_file=model_file,
|
||||||
|
weights_file=weights_file,
|
||||||
|
labels_mapping=labelmap_file,
|
||||||
|
attribute_spec={},
|
||||||
|
convertation_file=interpretation_file,
|
||||||
|
)
|
||||||
|
except Exception as e:
|
||||||
|
return False, str(e)
|
||||||
|
|
||||||
|
return True, ""
|
||||||
|
|
||||||
|
job = rq.get_current_job()
|
||||||
|
job.meta["progress"] = "Saving data"
|
||||||
|
job.save_meta()
|
||||||
|
|
||||||
|
with transaction.atomic():
|
||||||
|
dl_model = AnnotationModel.objects.select_for_update().get(pk=dl_model_id)
|
||||||
|
|
||||||
|
test_res = True
|
||||||
|
message = ""
|
||||||
|
if run_tests:
|
||||||
|
job.meta["progress"] = "Test started"
|
||||||
|
job.save_meta()
|
||||||
|
|
||||||
|
test_res, message = _run_test(
|
||||||
|
model_file=model_file or dl_model.model_file.name,
|
||||||
|
weights_file=weights_file or dl_model.weights_file.name,
|
||||||
|
labelmap_file=labelmap_file or dl_model.labelmap_file.name,
|
||||||
|
interpretation_file=interpretation_file or dl_model.interpretation_file.name,
|
||||||
|
)
|
||||||
|
|
||||||
|
if not test_res:
|
||||||
|
job.meta["progress"] = "Test failed"
|
||||||
|
if delete_if_test_fails:
|
||||||
|
shutil.rmtree(dl_model.get_dirname(), ignore_errors=True)
|
||||||
|
dl_model.delete()
|
||||||
|
else:
|
||||||
|
job.meta["progress"] = "Test passed"
|
||||||
|
job.save_meta()
|
||||||
|
|
||||||
|
# update DL model
|
||||||
|
if test_res:
|
||||||
|
if model_file:
|
||||||
|
_remove_old_file(dl_model.model_file)
|
||||||
|
dl_model.model_file.save(*_get_file_content(model_file))
|
||||||
|
if weights_file:
|
||||||
|
_remove_old_file(dl_model.weights_file)
|
||||||
|
dl_model.weights_file.save(*_get_file_content(weights_file))
|
||||||
|
if labelmap_file:
|
||||||
|
_remove_old_file(dl_model.labelmap_file)
|
||||||
|
dl_model.labelmap_file.save(*_get_file_content(labelmap_file))
|
||||||
|
if interpretation_file:
|
||||||
|
_remove_old_file(dl_model.interpretation_file)
|
||||||
|
dl_model.interpretation_file.save(*_get_file_content(interpretation_file))
|
||||||
|
|
||||||
|
if name:
|
||||||
|
dl_model.name = name
|
||||||
|
|
||||||
|
if is_shared != None:
|
||||||
|
dl_model.shared = is_shared
|
||||||
|
|
||||||
|
dl_model.updated_date = timezone.now()
|
||||||
|
dl_model.save()
|
||||||
|
|
||||||
|
if is_local_storage:
|
||||||
|
_delete_source_files()
|
||||||
|
|
||||||
|
if not test_res:
|
||||||
|
raise Exception("Model was not properly created/updated. Test failed: {}".format(message))
|
||||||
|
|
||||||
|
def create_or_update(dl_model_id, name, model_file, weights_file, labelmap_file, interpretation_file, owner, storage, is_shared):
|
||||||
|
def get_abs_path(share_path):
|
||||||
|
if not share_path:
|
||||||
|
return share_path
|
||||||
|
share_root = settings.SHARE_ROOT
|
||||||
|
relpath = os.path.normpath(share_path).lstrip('/')
|
||||||
|
if '..' in relpath.split(os.path.sep):
|
||||||
|
raise Exception('Permission denied')
|
||||||
|
abspath = os.path.abspath(os.path.join(share_root, relpath))
|
||||||
|
if os.path.commonprefix([share_root, abspath]) != share_root:
|
||||||
|
raise Exception('Bad file path on share: ' + abspath)
|
||||||
|
return abspath
|
||||||
|
|
||||||
|
def save_file_as_tmp(data):
|
||||||
|
if not data:
|
||||||
|
return None
|
||||||
|
fd, filename = tempfile.mkstemp()
|
||||||
|
with open(filename, 'wb') as tmp_file:
|
||||||
|
for chunk in data.chunks():
|
||||||
|
tmp_file.write(chunk)
|
||||||
|
os.close(fd)
|
||||||
|
return filename
|
||||||
|
is_create_request = dl_model_id is None
|
||||||
|
if is_create_request:
|
||||||
|
dl_model_id = create_empty(owner=owner)
|
||||||
|
|
||||||
|
run_tests = bool(model_file or weights_file or labelmap_file or interpretation_file)
|
||||||
|
if storage != "local":
|
||||||
|
model_file = get_abs_path(model_file)
|
||||||
|
weights_file = get_abs_path(weights_file)
|
||||||
|
labelmap_file = get_abs_path(labelmap_file)
|
||||||
|
interpretation_file = get_abs_path(interpretation_file)
|
||||||
|
else:
|
||||||
|
model_file = save_file_as_tmp(model_file)
|
||||||
|
weights_file = save_file_as_tmp(weights_file)
|
||||||
|
labelmap_file = save_file_as_tmp(labelmap_file)
|
||||||
|
interpretation_file = save_file_as_tmp(interpretation_file)
|
||||||
|
|
||||||
|
rq_id = "auto_annotation.create.{}".format(dl_model_id)
|
||||||
|
queue = django_rq.get_queue("default")
|
||||||
|
queue.enqueue_call(
|
||||||
|
func=_update_dl_model_thread,
|
||||||
|
args=(
|
||||||
|
dl_model_id,
|
||||||
|
name,
|
||||||
|
is_shared,
|
||||||
|
model_file,
|
||||||
|
weights_file,
|
||||||
|
labelmap_file,
|
||||||
|
interpretation_file,
|
||||||
|
run_tests,
|
||||||
|
storage == "local",
|
||||||
|
is_create_request,
|
||||||
|
),
|
||||||
|
job_id=rq_id
|
||||||
|
)
|
||||||
|
|
||||||
|
return rq_id
|
||||||
|
|
||||||
|
@transaction.atomic
|
||||||
|
def create_empty(owner, framework=FrameworkChoice.OPENVINO):
|
||||||
|
db_model = AnnotationModel(
|
||||||
|
owner=owner,
|
||||||
|
)
|
||||||
|
db_model.save()
|
||||||
|
|
||||||
|
model_path = db_model.get_dirname()
|
||||||
|
if os.path.isdir(model_path):
|
||||||
|
shutil.rmtree(model_path)
|
||||||
|
os.mkdir(model_path)
|
||||||
|
|
||||||
|
return db_model.id
|
||||||
|
|
||||||
|
@transaction.atomic
|
||||||
|
def delete(dl_model_id):
|
||||||
|
dl_model = AnnotationModel.objects.select_for_update().get(pk=dl_model_id)
|
||||||
|
if dl_model:
|
||||||
|
if dl_model.primary:
|
||||||
|
raise Exception("Can not delete primary model {}".format(dl_model_id))
|
||||||
|
|
||||||
|
shutil.rmtree(dl_model.get_dirname(), ignore_errors=True)
|
||||||
|
dl_model.delete()
|
||||||
|
else:
|
||||||
|
raise Exception("Requested DL model {} doesn't exist".format(dl_model_id))
|
||||||
|
|
||||||
|
def get_image_data(path_to_data):
|
||||||
|
def get_image_key(item):
|
||||||
|
return int(os.path.splitext(os.path.basename(item))[0])
|
||||||
|
|
||||||
|
image_list = []
|
||||||
|
for root, _, filenames in os.walk(path_to_data):
|
||||||
|
for filename in fnmatch.filter(filenames, "*.jpg"):
|
||||||
|
image_list.append(os.path.join(root, filename))
|
||||||
|
|
||||||
|
image_list.sort(key=get_image_key)
|
||||||
|
return ImageLoader(image_list)
|
||||||
|
|
||||||
|
class Results():
|
||||||
|
def __init__(self):
|
||||||
|
self._results = {
|
||||||
|
"shapes": [],
|
||||||
|
"tracks": []
|
||||||
|
}
|
||||||
|
|
||||||
|
def add_box(self, xtl, ytl, xbr, ybr, label, frame_number, attributes=None):
|
||||||
|
self.get_shapes().append({
|
||||||
|
"label": label,
|
||||||
|
"frame": frame_number,
|
||||||
|
"points": [xtl, ytl, xbr, ybr],
|
||||||
|
"type": "rectangle",
|
||||||
|
"attributes": attributes or {},
|
||||||
|
})
|
||||||
|
|
||||||
|
def add_points(self, points, label, frame_number, attributes=None):
|
||||||
|
points = self._create_polyshape(points, label, frame_number, attributes)
|
||||||
|
points["type"] = "points"
|
||||||
|
self.get_shapes().append(points)
|
||||||
|
|
||||||
|
def add_polygon(self, points, label, frame_number, attributes=None):
|
||||||
|
polygon = self._create_polyshape(points, label, frame_number, attributes)
|
||||||
|
polygon["type"] = "polygon"
|
||||||
|
self.get_shapes().append(polygon)
|
||||||
|
|
||||||
|
def add_polyline(self, points, label, frame_number, attributes=None):
|
||||||
|
polyline = self._create_polyshape(points, label, frame_number, attributes)
|
||||||
|
polyline["type"] = "polyline"
|
||||||
|
self.get_shapes().append(polyline)
|
||||||
|
|
||||||
|
def get_shapes(self):
|
||||||
|
return self._results["shapes"]
|
||||||
|
|
||||||
|
def get_tracks(self):
|
||||||
|
return self._results["tracks"]
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _create_polyshape(self, points, label, frame_number, attributes=None):
|
||||||
|
return {
|
||||||
|
"label": label,
|
||||||
|
"frame": frame_number,
|
||||||
|
"points": " ".join("{},{}".format(pair[0], pair[1]) for pair in points),
|
||||||
|
"attributes": attributes or {},
|
||||||
|
}
|
||||||
|
|
||||||
|
def _process_detections(detections, path_to_conv_script):
|
||||||
|
results = Results()
|
||||||
|
global_vars = {
|
||||||
|
"__builtins__": {
|
||||||
|
"str": str,
|
||||||
|
"int": int,
|
||||||
|
"float": float,
|
||||||
|
"max": max,
|
||||||
|
"min": min,
|
||||||
|
"range": range,
|
||||||
|
},
|
||||||
|
}
|
||||||
|
local_vars = {
|
||||||
|
"detections": detections,
|
||||||
|
"results": results,
|
||||||
|
}
|
||||||
|
exec (open(path_to_conv_script).read(), global_vars, local_vars)
|
||||||
|
return results
|
||||||
|
|
||||||
|
def _run_inference_engine_annotation(data, model_file, weights_file,
|
||||||
|
labels_mapping, attribute_spec, convertation_file, job=None, update_progress=None):
|
||||||
|
def process_attributes(shape_attributes, label_attr_spec):
|
||||||
|
attributes = []
|
||||||
|
for attr_text, attr_value in shape_attributes.items():
|
||||||
|
if attr_text in label_attr_spec:
|
||||||
|
attributes.append({
|
||||||
|
"id": label_attr_spec[attr_text],
|
||||||
|
"value": attr_value,
|
||||||
|
})
|
||||||
|
|
||||||
|
return attributes
|
||||||
|
|
||||||
|
def add_shapes(shapes, target_container):
|
||||||
|
for shape in shapes:
|
||||||
|
if shape["label"] not in labels_mapping:
|
||||||
|
continue
|
||||||
|
db_label = labels_mapping[shape["label"]]
|
||||||
|
|
||||||
|
target_container.append({
|
||||||
|
"label_id": db_label,
|
||||||
|
"frame": shape["frame"],
|
||||||
|
"points": shape["points"],
|
||||||
|
"type": shape["type"],
|
||||||
|
"z_order": 0,
|
||||||
|
"group": None,
|
||||||
|
"occluded": False,
|
||||||
|
"attributes": process_attributes(shape["attributes"], attribute_spec[db_label]),
|
||||||
|
})
|
||||||
|
|
||||||
|
result = {
|
||||||
|
"shapes": [],
|
||||||
|
"tracks": [],
|
||||||
|
"tags": [],
|
||||||
|
"version": 0
|
||||||
|
}
|
||||||
|
|
||||||
|
data_len = len(data)
|
||||||
|
model = ModelLoader(model=model_file, weights=weights_file)
|
||||||
|
|
||||||
|
frame_counter = 0
|
||||||
|
|
||||||
|
detections = []
|
||||||
|
for frame in data:
|
||||||
|
orig_rows, orig_cols = frame.shape[:2]
|
||||||
|
|
||||||
|
detections.append({
|
||||||
|
"frame_id": frame_counter,
|
||||||
|
"frame_height": orig_rows,
|
||||||
|
"frame_width": orig_cols,
|
||||||
|
"detections": model.infer(frame),
|
||||||
|
})
|
||||||
|
|
||||||
|
frame_counter += 1
|
||||||
|
if job and update_progress and not update_progress(job, frame_counter * 100 / data_len):
|
||||||
|
return None
|
||||||
|
|
||||||
|
processed_detections = _process_detections(detections, convertation_file)
|
||||||
|
|
||||||
|
add_shapes(processed_detections.get_shapes(), result["shapes"])
|
||||||
|
|
||||||
|
|
||||||
|
return result
|
||||||
|
|
||||||
|
def run_inference_thread(tid, model_file, weights_file, labels_mapping, attributes, convertation_file, reset, user):
|
||||||
|
def update_progress(job, progress):
|
||||||
|
job.refresh()
|
||||||
|
if "cancel" in job.meta:
|
||||||
|
del job.meta["cancel"]
|
||||||
|
job.save()
|
||||||
|
return False
|
||||||
|
job.meta["progress"] = progress
|
||||||
|
job.save_meta()
|
||||||
|
return True
|
||||||
|
|
||||||
|
try:
|
||||||
|
job = rq.get_current_job()
|
||||||
|
job.meta["progress"] = 0
|
||||||
|
job.save_meta()
|
||||||
|
db_task = TaskModel.objects.get(pk=tid)
|
||||||
|
|
||||||
|
result = None
|
||||||
|
slogger.glob.info("auto annotation with openvino toolkit for task {}".format(tid))
|
||||||
|
result = _run_inference_engine_annotation(
|
||||||
|
data=get_image_data(db_task.get_data_dirname()),
|
||||||
|
model_file=model_file,
|
||||||
|
weights_file=weights_file,
|
||||||
|
labels_mapping=labels_mapping,
|
||||||
|
attribute_spec=attributes,
|
||||||
|
convertation_file= convertation_file,
|
||||||
|
job=job,
|
||||||
|
update_progress=update_progress,
|
||||||
|
)
|
||||||
|
|
||||||
|
if result is None:
|
||||||
|
slogger.glob.info("auto annotation for task {} canceled by user".format(tid))
|
||||||
|
return
|
||||||
|
|
||||||
|
serializer = LabeledDataSerializer(data = result)
|
||||||
|
if serializer.is_valid(raise_exception=True):
|
||||||
|
if reset:
|
||||||
|
put_task_data(tid, user, result)
|
||||||
|
else:
|
||||||
|
patch_task_data(tid, user, result, "create")
|
||||||
|
|
||||||
|
slogger.glob.info("auto annotation for task {} done".format(tid))
|
||||||
|
except Exception as e:
|
||||||
|
try:
|
||||||
|
slogger.task[tid].exception("exception was occurred during auto annotation of the task", exc_info=True)
|
||||||
|
except Exception as ex:
|
||||||
|
slogger.glob.exception("exception was occurred during auto annotation of the task {}: {}".format(tid, str(ex)), exc_info=True)
|
||||||
|
raise ex
|
||||||
|
|
||||||
|
raise e
|
||||||
@ -0,0 +1,55 @@
|
|||||||
|
|
||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from enum import Enum
|
||||||
|
|
||||||
|
from django.db import models
|
||||||
|
from django.conf import settings
|
||||||
|
from django.contrib.auth.models import User
|
||||||
|
from django.core.files.storage import FileSystemStorage
|
||||||
|
|
||||||
|
fs = FileSystemStorage()
|
||||||
|
|
||||||
|
def upload_path_handler(instance, filename):
|
||||||
|
return "{models_root}/{id}/{file}".format(models_root=settings.MODELS_ROOT, id=instance.id, file=filename)
|
||||||
|
|
||||||
|
class FrameworkChoice(Enum):
|
||||||
|
OPENVINO = 'openvino'
|
||||||
|
TENSORFLOW = 'tensorflow'
|
||||||
|
PYTORCH = 'pytorch'
|
||||||
|
|
||||||
|
def __str__(self):
|
||||||
|
return self.value
|
||||||
|
|
||||||
|
|
||||||
|
class SafeCharField(models.CharField):
|
||||||
|
def get_prep_value(self, value):
|
||||||
|
value = super().get_prep_value(value)
|
||||||
|
if value:
|
||||||
|
return value[:self.max_length]
|
||||||
|
return value
|
||||||
|
|
||||||
|
class AnnotationModel(models.Model):
|
||||||
|
name = SafeCharField(max_length=256)
|
||||||
|
owner = models.ForeignKey(User, null=True, blank=True,
|
||||||
|
on_delete=models.SET_NULL)
|
||||||
|
created_date = models.DateTimeField(auto_now_add=True)
|
||||||
|
updated_date = models.DateTimeField(auto_now_add=True)
|
||||||
|
model_file = models.FileField(upload_to=upload_path_handler, storage=fs)
|
||||||
|
weights_file = models.FileField(upload_to=upload_path_handler, storage=fs)
|
||||||
|
labelmap_file = models.FileField(upload_to=upload_path_handler, storage=fs)
|
||||||
|
interpretation_file = models.FileField(upload_to=upload_path_handler, storage=fs)
|
||||||
|
shared = models.BooleanField(default=False)
|
||||||
|
primary = models.BooleanField(default=False)
|
||||||
|
framework = models.CharField(max_length=32, default=FrameworkChoice.OPENVINO)
|
||||||
|
|
||||||
|
class Meta:
|
||||||
|
default_permissions = ()
|
||||||
|
|
||||||
|
def get_dirname(self):
|
||||||
|
return "{models_root}/{id}".format(models_root=settings.MODELS_ROOT, id=self.id)
|
||||||
|
|
||||||
|
def __str__(self):
|
||||||
|
return self.name
|
||||||
@ -0,0 +1,29 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
import rules
|
||||||
|
|
||||||
|
from cvat.apps.authentication.auth import has_admin_role, has_user_role
|
||||||
|
|
||||||
|
@rules.predicate
|
||||||
|
def is_model_owner(db_user, db_dl_model):
|
||||||
|
return db_dl_model.owner == db_user
|
||||||
|
|
||||||
|
@rules.predicate
|
||||||
|
def is_shared_model(_, db_dl_model):
|
||||||
|
return db_dl_model.shared
|
||||||
|
|
||||||
|
@rules.predicate
|
||||||
|
def is_primary_model(_, db_dl_model):
|
||||||
|
return db_dl_model.primary
|
||||||
|
|
||||||
|
def setup_permissions():
|
||||||
|
rules.add_perm('auto_annotation.model.create', has_admin_role | has_user_role)
|
||||||
|
|
||||||
|
rules.add_perm('auto_annotation.model.update', (has_admin_role | is_model_owner) & ~is_primary_model)
|
||||||
|
|
||||||
|
rules.add_perm('auto_annotation.model.delete', (has_admin_role | is_model_owner) & ~is_primary_model)
|
||||||
|
|
||||||
|
rules.add_perm('auto_annotation.model.access', has_admin_role | is_model_owner |
|
||||||
|
is_shared_model | is_primary_model)
|
||||||
@ -0,0 +1,780 @@
|
|||||||
|
/*
|
||||||
|
* Copyright (C) 2018 Intel Corporation
|
||||||
|
*
|
||||||
|
* SPDX-License-Identifier: MIT
|
||||||
|
*/
|
||||||
|
|
||||||
|
/* global
|
||||||
|
showMessage
|
||||||
|
showOverlay
|
||||||
|
userConfirm
|
||||||
|
*/
|
||||||
|
|
||||||
|
window.cvat = window.cvat || {};
|
||||||
|
|
||||||
|
const AutoAnnotationServer = {
|
||||||
|
start(modelId, taskId, data, success, error, progress, check) {
|
||||||
|
$.ajax({
|
||||||
|
url: `/auto_annotation/start/${modelId}/${taskId}`,
|
||||||
|
type: 'POST',
|
||||||
|
data: JSON.stringify(data),
|
||||||
|
contentType: 'application/json',
|
||||||
|
success: (responseData) => {
|
||||||
|
check(responseData.id, success, error, progress);
|
||||||
|
},
|
||||||
|
error: (responseData) => {
|
||||||
|
const message = `Starting request has been failed. Code: ${responseData.status}. Message: ${responseData.responseText || responseData.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
|
||||||
|
update(data, success, error, progress, check, modelId) {
|
||||||
|
let url = '';
|
||||||
|
if (modelId === null) {
|
||||||
|
url = '/auto_annotation/create';
|
||||||
|
} else {
|
||||||
|
url = `/auto_annotation/update/${modelId}`;
|
||||||
|
}
|
||||||
|
|
||||||
|
$.ajax({
|
||||||
|
url,
|
||||||
|
type: 'POST',
|
||||||
|
data,
|
||||||
|
contentType: false,
|
||||||
|
processData: false,
|
||||||
|
success: (responseData) => {
|
||||||
|
check(responseData.id, success, error, progress);
|
||||||
|
},
|
||||||
|
error: (responseData) => {
|
||||||
|
const message = `Creating request has been failed. Code: ${responseData.status}. Message: ${responseData.responseText || responseData.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
|
||||||
|
delete(modelId, success, error) {
|
||||||
|
$.ajax({
|
||||||
|
url: `/auto_annotation/delete/${modelId}`,
|
||||||
|
type: 'DELETE',
|
||||||
|
success,
|
||||||
|
error: (data) => {
|
||||||
|
const message = `Deleting request has been failed. Code: ${data.status}. Message: ${data.responseText || data.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
|
||||||
|
check(workerId, success, error, progress) {
|
||||||
|
function updateProgress(data) {
|
||||||
|
if (data.progress && progress) {
|
||||||
|
progress(data.progress);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
function checkCallback() {
|
||||||
|
$.ajax({
|
||||||
|
url: `/auto_annotation/check/${workerId}`,
|
||||||
|
type: 'GET',
|
||||||
|
success: (data) => {
|
||||||
|
updateProgress(data, progress);
|
||||||
|
|
||||||
|
switch (data.status) {
|
||||||
|
case 'failed':
|
||||||
|
error(`Checking request has returned the "${data.status}" status. Message: ${data.error}`);
|
||||||
|
break;
|
||||||
|
|
||||||
|
case 'unknown':
|
||||||
|
error(`Checking request has returned the "${data.status}" status.`);
|
||||||
|
break;
|
||||||
|
|
||||||
|
case 'finished':
|
||||||
|
success();
|
||||||
|
break;
|
||||||
|
|
||||||
|
default:
|
||||||
|
setTimeout(checkCallback, 1000);
|
||||||
|
}
|
||||||
|
},
|
||||||
|
error: (data) => {
|
||||||
|
const message = `Checking request has been failed. Code: ${data.status}. Message: ${data.responseText || data.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
setTimeout(checkCallback, 1000);
|
||||||
|
},
|
||||||
|
|
||||||
|
meta(tids, success, error) {
|
||||||
|
$.ajax({
|
||||||
|
url: '/auto_annotation/meta/get',
|
||||||
|
type: 'POST',
|
||||||
|
data: JSON.stringify(tids),
|
||||||
|
contentType: 'application/json',
|
||||||
|
success,
|
||||||
|
error: (data) => {
|
||||||
|
const message = `Getting meta request has been failed. Code: ${data.status}. Message: ${data.responseText || data.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
|
||||||
|
cancel(tid, success, error) {
|
||||||
|
$.ajax({
|
||||||
|
url: `/auto_annotation/cancel/${tid}`,
|
||||||
|
type: 'GET',
|
||||||
|
success,
|
||||||
|
error: (data) => {
|
||||||
|
const message = `Getting meta request has been failed. Code: ${data.status}. Message: ${data.responseText || data.statusText}`;
|
||||||
|
error(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
},
|
||||||
|
};
|
||||||
|
|
||||||
|
|
||||||
|
class AutoAnnotationModelManagerView {
|
||||||
|
constructor() {
|
||||||
|
const html = `<div class="modal hidden" id="${window.cvat.autoAnnotation.managerWindowId}">
|
||||||
|
<div class="modal-content" id="${window.cvat.autoAnnotation.managerContentId}">
|
||||||
|
<div style="float: left; width: 55%; height: 100%;">
|
||||||
|
<center>
|
||||||
|
<label class="regular h1"> Uploaded Models </label>
|
||||||
|
</center>
|
||||||
|
<div style="overflow: auto; height: 90%; margin-top: 2%;">
|
||||||
|
<table class="regular modelsTable">
|
||||||
|
<thead>
|
||||||
|
<tr>
|
||||||
|
<th> Name </th>
|
||||||
|
<th> Upload Date </th>
|
||||||
|
<th> Actions </th>
|
||||||
|
</tr>
|
||||||
|
</thead>
|
||||||
|
<tbody id="${window.cvat.autoAnnotation.managerUploadedModelsId}"> </tbody>
|
||||||
|
</table>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<div class="regular" id="${window.cvat.autoAnnotation.uploadContentId}">
|
||||||
|
<center>
|
||||||
|
<label class="regular h1" id="${window.cvat.autoAnnotation.uploadTitleId}"> Create Model </label>
|
||||||
|
</center>
|
||||||
|
<table>
|
||||||
|
<tr>
|
||||||
|
<td style="width: 25%"> <label class="regular h3"> Name: </label> </td>
|
||||||
|
<td> <input type="text" id="${window.cvat.autoAnnotation.uploadNameInputId}" class="regular h3" style="width: 100%"> </td>
|
||||||
|
</tr>
|
||||||
|
<tr>
|
||||||
|
<td> <label class="regular h3"> Source: </label> </td>
|
||||||
|
<td>
|
||||||
|
<input id="${window.cvat.autoAnnotation.uploadLocalSourceId}" type="radio" name="modelSourceType" value="local" checked>
|
||||||
|
<label for="${window.cvat.autoAnnotation.uploadLocalSourceId}" class="regular h3"> Local </label>
|
||||||
|
<br>
|
||||||
|
<input id="${window.cvat.autoAnnotation.uploadShareSourceId}" type="radio" name="modelSourceType" value="shared">
|
||||||
|
<label for="${window.cvat.autoAnnotation.uploadShareSourceId}" class="regular h3"> Share </label>
|
||||||
|
</td>
|
||||||
|
</tr>
|
||||||
|
<tr id="${window.cvat.autoAnnotation.uploadGloballyBlockId}">
|
||||||
|
<td> <label class="regular h3"> Upload Globally </label> </td>
|
||||||
|
<td> <input type="checkbox" id="${window.cvat.autoAnnotation.uploadGloballyId}"> </td>
|
||||||
|
</tr>
|
||||||
|
</table>
|
||||||
|
<div style="text-align: left;">
|
||||||
|
<div>
|
||||||
|
<button id="${window.cvat.autoAnnotation.selectFilesButtonId}" class="regular h3"> Select Files </button>
|
||||||
|
<label id="${window.cvat.autoAnnotation.selectedFilesId}" class="regular h3" style="margin-left: 10px"> No Files </label>
|
||||||
|
<input id="${window.cvat.autoAnnotation.localFileSelectorId}" type="file" accept=".bin,.xml,.json,.py" style="display: none" multiple>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<div>
|
||||||
|
<div style="float: right; width: 50%; height: 50px;">
|
||||||
|
<button class="regular h3" id="${window.cvat.autoAnnotation.submitUploadButtonId}"> Submit </button>
|
||||||
|
<button class="regular h3" id="${window.cvat.autoAnnotation.cancelUploadButtonId}"> Cancel </button>
|
||||||
|
</div>
|
||||||
|
<div style="float: left; overflow-y: auto; height: 75px; overflow: auto; width: 100%; word-break: break-word;">
|
||||||
|
<label class="regular h3 selectable" style="float: left;" id="${window.cvat.autoAnnotation.uploadMessageId}"> </label>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
</div>`;
|
||||||
|
|
||||||
|
this.el = $(html);
|
||||||
|
|
||||||
|
this.table = this.el.find(`#${window.cvat.autoAnnotation.managerUploadedModelsId}`);
|
||||||
|
this.globallyBlock = this.el.find(`#${window.cvat.autoAnnotation.uploadGloballyBlockId}`);
|
||||||
|
this.uploadTitle = this.el.find(`#${window.cvat.autoAnnotation.uploadTitleId}`);
|
||||||
|
this.uploadNameInput = this.el.find(`#${window.cvat.autoAnnotation.uploadNameInputId}`);
|
||||||
|
this.uploadMessage = this.el.find(`#${window.cvat.autoAnnotation.uploadMessageId}`);
|
||||||
|
this.selectedFilesLabel = this.el.find(`#${window.cvat.autoAnnotation.selectedFilesId}`);
|
||||||
|
this.modelNameInput = this.el.find(`#${window.cvat.autoAnnotation.uploadNameInputId}`);
|
||||||
|
this.localSource = this.el.find(`#${window.cvat.autoAnnotation.uploadLocalSourceId}`);
|
||||||
|
this.shareSource = this.el.find(`#${window.cvat.autoAnnotation.uploadShareSourceId}`);
|
||||||
|
this.cancelButton = this.el.find(`#${window.cvat.autoAnnotation.cancelUploadButtonId}`);
|
||||||
|
this.submitButton = this.el.find(`#${window.cvat.autoAnnotation.submitUploadButtonId}`);
|
||||||
|
this.globallyBox = this.el.find(`#${window.cvat.autoAnnotation.uploadGloballyId}`);
|
||||||
|
this.selectButton = this.el.find(`#${window.cvat.autoAnnotation.selectFilesButtonId}`);
|
||||||
|
this.localSelector = this.el.find(`#${window.cvat.autoAnnotation.localFileSelectorId}`);
|
||||||
|
this.shareSelector = $('#dashboardShareBrowseModal');
|
||||||
|
this.shareBrowseTree = $('#dashboardShareBrowser');
|
||||||
|
this.submitShare = $('#dashboardSubmitBrowseServer');
|
||||||
|
|
||||||
|
this.id = null;
|
||||||
|
this.source = this.localSource.prop('checked') ? 'local' : 'shared';
|
||||||
|
this.files = [];
|
||||||
|
|
||||||
|
function filesLabel(source, files) {
|
||||||
|
const fileLabels = source === 'local' ? [...files].map(el => el.name) : files;
|
||||||
|
if (fileLabels.length) {
|
||||||
|
const labelStr = fileLabels.join(', ');
|
||||||
|
if (labelStr.length > 30) {
|
||||||
|
return `${labelStr.substr(0, 30)}..`;
|
||||||
|
}
|
||||||
|
|
||||||
|
return labelStr;
|
||||||
|
}
|
||||||
|
|
||||||
|
return 'No Files';
|
||||||
|
}
|
||||||
|
|
||||||
|
function extractFiles(extensions, files, source) {
|
||||||
|
const extractedFiles = {};
|
||||||
|
function getExt(file) {
|
||||||
|
return source === 'local' ? file.name.split('.').pop() : file.split('.').pop();
|
||||||
|
}
|
||||||
|
|
||||||
|
function addFile(file, extention) {
|
||||||
|
if (extention in files) {
|
||||||
|
throw Error(`More than one file with the extension .${extention} have been found`);
|
||||||
|
}
|
||||||
|
|
||||||
|
extractedFiles[extention] = file;
|
||||||
|
}
|
||||||
|
|
||||||
|
files.forEach((file) => {
|
||||||
|
const fileExt = getExt(file);
|
||||||
|
if (extensions.includes(fileExt)) {
|
||||||
|
addFile(file, fileExt);
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
return extractedFiles;
|
||||||
|
}
|
||||||
|
|
||||||
|
function validateFiles(isUpdate, files, source) {
|
||||||
|
const extensions = ['xml', 'bin', 'py', 'json'];
|
||||||
|
const extractedFiles = extractFiles(extensions, files, source);
|
||||||
|
|
||||||
|
if (!isUpdate) {
|
||||||
|
extensions.forEach((extension) => {
|
||||||
|
if (!(extension in extractedFiles)) {
|
||||||
|
throw Error(`Please specify a .${extension} file`);
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
return extractedFiles;
|
||||||
|
}
|
||||||
|
|
||||||
|
this.localSource.on('click', () => {
|
||||||
|
if (this.source !== 'local') {
|
||||||
|
this.source = 'local';
|
||||||
|
this.files = [];
|
||||||
|
this.selectedFilesLabel.text(filesLabel(this.source, this.files));
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
this.shareSource.on('click', () => {
|
||||||
|
if (this.source !== 'shared') {
|
||||||
|
this.source = 'shared';
|
||||||
|
this.files = [];
|
||||||
|
this.selectedFilesLabel.text(filesLabel(this.source, this.files));
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
this.selectButton.on('click', () => {
|
||||||
|
if (this.source === 'local') {
|
||||||
|
this.localSelector.click();
|
||||||
|
} else {
|
||||||
|
this.shareSelector.appendTo('body');
|
||||||
|
this.shareBrowseTree.jstree('refresh');
|
||||||
|
this.shareSelector.removeClass('hidden');
|
||||||
|
this.shareBrowseTree.jstree({
|
||||||
|
core: {
|
||||||
|
data: {
|
||||||
|
url: 'get_share_nodes',
|
||||||
|
data: node => ({ id: node.id }),
|
||||||
|
},
|
||||||
|
},
|
||||||
|
plugins: ['checkbox', 'sort'],
|
||||||
|
});
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
this.submitShare.on('click', () => {
|
||||||
|
if (!this.el.hasClass('hidden')) {
|
||||||
|
this.shareSelector.addClass('hidden');
|
||||||
|
this.files = this.shareBrowseTree.jstree(true).get_selected();
|
||||||
|
this.selectedFilesLabel.text(filesLabel(this.source, this.files));
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
this.localSelector.on('change', (e) => {
|
||||||
|
this.files = Array.from(e.target.files);
|
||||||
|
this.selectedFilesLabel.text(filesLabel(this.source, this.files));
|
||||||
|
});
|
||||||
|
|
||||||
|
this.cancelButton.on('click', () => this.el.addClass('hidden'));
|
||||||
|
this.submitButton.on('click', () => {
|
||||||
|
try {
|
||||||
|
this.submitButton.prop('disabled', true);
|
||||||
|
|
||||||
|
const name = $.trim(this.modelNameInput.prop('value'));
|
||||||
|
if (!name.length) {
|
||||||
|
this.uploadMessage.css('color', 'red');
|
||||||
|
this.uploadMessage.text('Please specify a model name');
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
let validatedFiles = {};
|
||||||
|
try {
|
||||||
|
validatedFiles = validateFiles(this.id !== null, this.files, this.source);
|
||||||
|
} catch (err) {
|
||||||
|
this.uploadMessage.css('color', 'red');
|
||||||
|
this.uploadMessage.text(err);
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
const modelData = new FormData();
|
||||||
|
modelData.append('name', name);
|
||||||
|
modelData.append('storage', this.source);
|
||||||
|
modelData.append('shared', this.globallyBox.prop('checked'));
|
||||||
|
|
||||||
|
['xml', 'bin', 'json', 'py'].filter(e => e in validatedFiles).forEach((ext) => {
|
||||||
|
modelData.append(ext, validatedFiles[ext]);
|
||||||
|
});
|
||||||
|
|
||||||
|
this.uploadMessage.text('');
|
||||||
|
const overlay = showOverlay('Send request to the server..');
|
||||||
|
window.cvat.autoAnnotation.server.update(modelData, () => {
|
||||||
|
window.location.reload();
|
||||||
|
}, (message) => {
|
||||||
|
overlay.remove();
|
||||||
|
showMessage(message);
|
||||||
|
}, (progress) => {
|
||||||
|
overlay.setMessage(progress);
|
||||||
|
}, window.cvat.autoAnnotation.server.check, this.id);
|
||||||
|
} finally {
|
||||||
|
this.submitButton.prop('disabled', false);
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
reset() {
|
||||||
|
const setBlocked = () => {
|
||||||
|
if (window.cvat.autoAnnotation.data.admin) {
|
||||||
|
this.globallyBlock.removeClass('hidden');
|
||||||
|
} else {
|
||||||
|
this.globallyBlock.addClass('hidden');
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
setBlocked();
|
||||||
|
this.uploadTitle.text('Create Model');
|
||||||
|
this.uploadNameInput.prop('value', '');
|
||||||
|
this.uploadMessage.css('color', '');
|
||||||
|
this.uploadMessage.text('');
|
||||||
|
this.selectedFilesLabel.text('No Files');
|
||||||
|
this.localSource.prop('checked', true);
|
||||||
|
this.globallyBox.prop('checked', false);
|
||||||
|
this.table.empty();
|
||||||
|
|
||||||
|
this.id = null;
|
||||||
|
this.source = this.localSource.prop('checked') ? 'local' : 'share';
|
||||||
|
this.files = [];
|
||||||
|
|
||||||
|
const updateButtonClickHandler = (event) => {
|
||||||
|
this.reset();
|
||||||
|
|
||||||
|
this.uploadTitle.text('Update Model');
|
||||||
|
this.uploadNameInput.prop('value', `${event.data.model.name}`);
|
||||||
|
this.id = event.data.model.id;
|
||||||
|
};
|
||||||
|
|
||||||
|
const deleteButtonClickHandler = (event) => {
|
||||||
|
userConfirm(`Do you actually want to delete the "${event.data.model.name}" model. Are you sure?`, () => {
|
||||||
|
window.cvat.autoAnnotation.server.delete(event.data.model.id, () => {
|
||||||
|
const filtered = window.cvat.autoAnnotation.data.models.filter(
|
||||||
|
item => item !== event.data.model,
|
||||||
|
);
|
||||||
|
window.cvat.autoAnnotation.data.models = filtered;
|
||||||
|
this.reset();
|
||||||
|
}, (message) => {
|
||||||
|
showMessage(message);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
};
|
||||||
|
|
||||||
|
const getModelModifyButtons = (model) => {
|
||||||
|
if (model.primary) {
|
||||||
|
return '<td> <label class="h1 regular"> Primary Model </label> </td>';
|
||||||
|
}
|
||||||
|
|
||||||
|
const updateButtonHtml = '<button class="regular h3" style="width: 7em;"> Update </button>';
|
||||||
|
const deleteButtonHtml = '<button class="regular h3" style="width: 7em; margin-top: 5%;"> Delete </button>';
|
||||||
|
|
||||||
|
return $('<td> </td>').append(
|
||||||
|
$(updateButtonHtml).on('click', { model }, updateButtonClickHandler),
|
||||||
|
$(deleteButtonHtml).on('click', { model }, deleteButtonClickHandler),
|
||||||
|
);
|
||||||
|
};
|
||||||
|
|
||||||
|
window.cvat.autoAnnotation.data.models.forEach((model) => {
|
||||||
|
const rowHtml = `<tr>
|
||||||
|
<td> ${model.name} </td>
|
||||||
|
<td> ${model.uploadDate} </td>
|
||||||
|
</tr>`;
|
||||||
|
|
||||||
|
this.table.append(
|
||||||
|
$(rowHtml).append(getModelModifyButtons(model)),
|
||||||
|
);
|
||||||
|
});
|
||||||
|
|
||||||
|
return this;
|
||||||
|
}
|
||||||
|
|
||||||
|
show() {
|
||||||
|
this.el.removeClass('hidden');
|
||||||
|
return this;
|
||||||
|
}
|
||||||
|
|
||||||
|
get element() {
|
||||||
|
return this.el;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
class AutoAnnotationModelRunnerView {
|
||||||
|
constructor() {
|
||||||
|
const html = `<div class="modal hidden" id="${window.cvat.autoAnnotation.runnerWindowId}">
|
||||||
|
<div class="modal-content" id="${window.cvat.autoAnnotation.runnerContentId}">
|
||||||
|
<div style="width: 55%; height: 100%; float: left;">
|
||||||
|
<center style="height: 10%;">
|
||||||
|
<label class="regular h1"> Uploaded Models </label>
|
||||||
|
</center>
|
||||||
|
<div style="height: 70%; overflow: auto; margin-top: 2%;">
|
||||||
|
<table class="modelsTable" id="${window.cvat.autoAnnotation.runnerUploadedModelsId}"> </table>
|
||||||
|
</div>
|
||||||
|
<div>
|
||||||
|
<input type="checkbox" id="${window.cvat.autoAnnotation.removeCurrentAnnotationId}"/>
|
||||||
|
<label class="regular h3" for="${window.cvat.autoAnnotation.removeCurrentAnnotationId}"> Remove current annotation </label>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<div style="width: 40%; height: 100%; float: left; margin-left: 3%;">
|
||||||
|
<center style="height: 10%;">
|
||||||
|
<label class="regular h1"> Annotation Labels </label>
|
||||||
|
</center>
|
||||||
|
<div style="height: 70%; overflow: auto; margin-top: 2%;">
|
||||||
|
<table class="regular" style="text-align: center; word-break: break-all; width: 100%;">
|
||||||
|
<thead>
|
||||||
|
<tr style="width: 100%;">
|
||||||
|
<th style="width: 45%;"> Task Label </th>
|
||||||
|
<th style="width: 45%;"> DL Model Label </th>
|
||||||
|
<th style="width: 10%;"> </th>
|
||||||
|
</tr>
|
||||||
|
</thead>
|
||||||
|
<tbody id="${window.cvat.autoAnnotation.annotationLabelsId}">
|
||||||
|
|
||||||
|
</tbody>
|
||||||
|
</table>
|
||||||
|
</div>
|
||||||
|
<div style="float:right;">
|
||||||
|
<button class="regular h3" style="width: 6em;" id="${window.cvat.autoAnnotation.submitAnnotationId}"> Start </button>
|
||||||
|
<button class="regular h3" style="width: 6em;" id="${window.cvat.autoAnnotation.cancelAnnotationId}"> Cancel </button>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
</div>`;
|
||||||
|
|
||||||
|
this.el = $(html);
|
||||||
|
this.id = null;
|
||||||
|
this.tid = null;
|
||||||
|
this.initButton = null;
|
||||||
|
this.modelsTable = this.el.find(`#${window.cvat.autoAnnotation.runnerUploadedModelsId}`);
|
||||||
|
this.labelsTable = this.el.find(`#${window.cvat.autoAnnotation.annotationLabelsId}`);
|
||||||
|
this.active = null;
|
||||||
|
|
||||||
|
this.el.find(`#${window.cvat.autoAnnotation.cancelAnnotationId}`).on('click', () => {
|
||||||
|
this.el.addClass('hidden');
|
||||||
|
});
|
||||||
|
|
||||||
|
this.el.find(`#${window.cvat.autoAnnotation.submitAnnotationId}`).on('click', () => {
|
||||||
|
try {
|
||||||
|
if (this.id === null) {
|
||||||
|
throw Error('Please specify a model for an annotation process');
|
||||||
|
}
|
||||||
|
|
||||||
|
const mapping = {};
|
||||||
|
$('.annotatorMappingRow').each((_, element) => {
|
||||||
|
const dlModelLabel = $(element).find('.annotatorDlLabelSelector')[0].value;
|
||||||
|
const taskLabel = $(element).find('.annotatorTaskLabelSelector')[0].value;
|
||||||
|
if (dlModelLabel in mapping) {
|
||||||
|
throw Error(`The label "${dlModelLabel}" has been specified twice or more`);
|
||||||
|
}
|
||||||
|
mapping[dlModelLabel] = taskLabel;
|
||||||
|
});
|
||||||
|
|
||||||
|
if (!Object.keys(mapping).length) {
|
||||||
|
throw Error('Labels for an annotation process haven\'t been found');
|
||||||
|
}
|
||||||
|
|
||||||
|
const overlay = showOverlay('Request has been sent');
|
||||||
|
window.cvat.autoAnnotation.server.start(this.id, this.tid, {
|
||||||
|
reset: $(`#${window.cvat.autoAnnotation.removeCurrentAnnotationId}`).prop('checked'),
|
||||||
|
labels: mapping,
|
||||||
|
}, () => {
|
||||||
|
overlay.remove();
|
||||||
|
this.initButton[0].setupRun();
|
||||||
|
window.cvat.autoAnnotation.runner.hide();
|
||||||
|
}, (message) => {
|
||||||
|
overlay.remove();
|
||||||
|
this.initButton[0].setupRun();
|
||||||
|
showMessage(message);
|
||||||
|
}, () => {
|
||||||
|
window.location.reload();
|
||||||
|
}, window.cvat.autoAnnotation.server.check);
|
||||||
|
} catch (error) {
|
||||||
|
showMessage(error);
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
reset(data, initButton) {
|
||||||
|
function labelsSelect(labels, elClass) {
|
||||||
|
const select = $(`<select class="regular h3 ${elClass}" style="width:100%;"> </select>`);
|
||||||
|
labels.forEach(label => select.append($(`<option value="${label}"> ${label} </option>`)));
|
||||||
|
select.prop('value', null);
|
||||||
|
|
||||||
|
return select;
|
||||||
|
}
|
||||||
|
|
||||||
|
function makeCreator(dlSelect, taskSelect, callback) {
|
||||||
|
let dlIsFilled = false;
|
||||||
|
let taskIsFilled = false;
|
||||||
|
const creator = $('<tr style="margin-bottom: 5px;"> </tr>').append(
|
||||||
|
$('<td style="width: 45%;"> </td>').append(taskSelect),
|
||||||
|
$('<td style="width: 45%;"> </td>').append(dlSelect),
|
||||||
|
);
|
||||||
|
|
||||||
|
const onSelectHandler = () => {
|
||||||
|
$('<td style="width: 10%; position: relative;"> </td>').append(
|
||||||
|
$('<a class="close"></a>').css('top', '0px').on('click', (e) => {
|
||||||
|
$(e.target.parentNode.parentNode).remove();
|
||||||
|
}),
|
||||||
|
).appendTo(creator);
|
||||||
|
|
||||||
|
creator.addClass('annotatorMappingRow');
|
||||||
|
callback();
|
||||||
|
};
|
||||||
|
|
||||||
|
dlSelect.on('change', (e) => {
|
||||||
|
if (e.target.value && taskIsFilled) {
|
||||||
|
dlSelect.off('change');
|
||||||
|
taskSelect.off('change');
|
||||||
|
onSelectHandler();
|
||||||
|
}
|
||||||
|
dlIsFilled = Boolean(e.target.value);
|
||||||
|
});
|
||||||
|
|
||||||
|
taskSelect.on('change', (e) => {
|
||||||
|
if (e.target.value && dlIsFilled) {
|
||||||
|
dlSelect.off('change');
|
||||||
|
taskSelect.off('change');
|
||||||
|
onSelectHandler();
|
||||||
|
}
|
||||||
|
|
||||||
|
taskIsFilled = Boolean(e.target.value);
|
||||||
|
});
|
||||||
|
|
||||||
|
return creator;
|
||||||
|
}
|
||||||
|
|
||||||
|
this.id = null;
|
||||||
|
this.initButton = initButton;
|
||||||
|
this.tid = data.id;
|
||||||
|
this.modelsTable.empty();
|
||||||
|
this.labelsTable.empty();
|
||||||
|
this.active = null;
|
||||||
|
|
||||||
|
const modelItemClickHandler = (event) => {
|
||||||
|
if (this.active) {
|
||||||
|
this.active.style.color = '';
|
||||||
|
}
|
||||||
|
|
||||||
|
this.id = event.data.model.id;
|
||||||
|
this.active = event.target;
|
||||||
|
this.active.style.color = 'darkblue';
|
||||||
|
|
||||||
|
this.labelsTable.empty();
|
||||||
|
const labels = event.data.data.labels.map(x => x.name);
|
||||||
|
const intersection = labels.filter(el => event.data.model.labels.indexOf(el) !== -1);
|
||||||
|
intersection.forEach((label) => {
|
||||||
|
const dlSelect = labelsSelect(event.data.model.labels, 'annotatorDlLabelSelector');
|
||||||
|
dlSelect.prop('value', label);
|
||||||
|
const taskSelect = labelsSelect(labels, 'annotatorTaskLabelSelector');
|
||||||
|
taskSelect.prop('value', label);
|
||||||
|
$('<tr class="annotatorMappingRow" style="margin-bottom: 5px;"> </tr>').append(
|
||||||
|
$('<td style="width: 45%;"> </td>').append(taskSelect),
|
||||||
|
$('<td style="width: 45%;"> </td>').append(dlSelect),
|
||||||
|
$('<td style="width: 10%; position: relative;"> </td>').append(
|
||||||
|
$('<a class="close"></a>').css('top', '0px').on('click', (e) => {
|
||||||
|
$(e.target.parentNode.parentNode).remove();
|
||||||
|
}),
|
||||||
|
),
|
||||||
|
).appendTo(this.labelsTable);
|
||||||
|
});
|
||||||
|
|
||||||
|
const dlSelect = labelsSelect(event.data.model.labels, 'annotatorDlLabelSelector');
|
||||||
|
const taskSelect = labelsSelect(labels, 'annotatorTaskLabelSelector');
|
||||||
|
|
||||||
|
const callback = () => {
|
||||||
|
makeCreator(
|
||||||
|
labelsSelect(event.data.model.labels, 'annotatorDlLabelSelector'),
|
||||||
|
labelsSelect(labels, 'annotatorTaskLabelSelector'),
|
||||||
|
callback,
|
||||||
|
).appendTo(this.labelsTable);
|
||||||
|
};
|
||||||
|
|
||||||
|
makeCreator(dlSelect, taskSelect, callback).appendTo(this.labelsTable);
|
||||||
|
};
|
||||||
|
|
||||||
|
window.cvat.autoAnnotation.data.models.forEach((model) => {
|
||||||
|
this.modelsTable.append(
|
||||||
|
$(`<tr> <td> <label class="regular h3"> ${model.name} (${model.uploadDate}) </label> </td> </tr>`).on(
|
||||||
|
'click', { model, data }, modelItemClickHandler,
|
||||||
|
),
|
||||||
|
);
|
||||||
|
});
|
||||||
|
|
||||||
|
return this;
|
||||||
|
}
|
||||||
|
|
||||||
|
show() {
|
||||||
|
this.el.removeClass('hidden');
|
||||||
|
return this;
|
||||||
|
}
|
||||||
|
|
||||||
|
hide() {
|
||||||
|
this.el.addClass('hidden');
|
||||||
|
return this;
|
||||||
|
}
|
||||||
|
|
||||||
|
get element() {
|
||||||
|
return this.el;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
window.cvat.autoAnnotation = {
|
||||||
|
managerWindowId: 'annotatorManagerWindow',
|
||||||
|
managerContentId: 'annotatorManagerContent',
|
||||||
|
managerUploadedModelsId: 'annotatorManagerUploadedModels',
|
||||||
|
uploadContentId: 'annotatorManagerUploadModel',
|
||||||
|
uploadTitleId: 'annotatorManagerUploadTitle',
|
||||||
|
uploadNameInputId: 'annotatorManagerUploadNameInput',
|
||||||
|
uploadLocalSourceId: 'annotatorManagerUploadLocalSource',
|
||||||
|
uploadShareSourceId: 'annotatorManagerUploadShareSource',
|
||||||
|
uploadGloballyId: 'annotatorManagerUploadGlobally',
|
||||||
|
uploadGloballyBlockId: 'annotatorManagerUploadGloballyblock',
|
||||||
|
selectFilesButtonId: 'annotatorManagerUploadSelector',
|
||||||
|
selectedFilesId: 'annotatorManagerUploadSelectedFiles',
|
||||||
|
localFileSelectorId: 'annotatorManagerUploadLocalSelector',
|
||||||
|
shareFileSelectorId: 'annotatorManagerUploadShareSelector',
|
||||||
|
submitUploadButtonId: 'annotatorManagerSubmitUploadButton',
|
||||||
|
cancelUploadButtonId: 'annotatorManagerCancelUploadButton',
|
||||||
|
uploadMessageId: 'annotatorUploadStatusMessage',
|
||||||
|
|
||||||
|
runnerWindowId: 'annotatorRunnerWindow',
|
||||||
|
runnerContentId: 'annotatorRunnerContent',
|
||||||
|
runnerUploadedModelsId: 'annotatorRunnerUploadedModels',
|
||||||
|
removeCurrentAnnotationId: 'annotatorRunnerRemoveCurrentAnnotationBox',
|
||||||
|
annotationLabelsId: 'annotatorRunnerAnnotationLabels',
|
||||||
|
submitAnnotationId: 'annotatorRunnerSubmitAnnotationButton',
|
||||||
|
cancelAnnotationId: 'annotatorRunnerCancelAnnotationButton',
|
||||||
|
|
||||||
|
managerButtonId: 'annotatorManagerButton',
|
||||||
|
};
|
||||||
|
|
||||||
|
window.addEventListener('DOMContentLoaded', () => {
|
||||||
|
window.cvat.autoAnnotation.server = AutoAnnotationServer;
|
||||||
|
window.cvat.autoAnnotation.manager = new AutoAnnotationModelManagerView();
|
||||||
|
window.cvat.autoAnnotation.runner = new AutoAnnotationModelRunnerView();
|
||||||
|
|
||||||
|
$('body').append(window.cvat.autoAnnotation.manager.element, window.cvat.autoAnnotation.runner.element);
|
||||||
|
$(`<button id="${window.cvat.autoAnnotation.managerButtonId}" class="regular h1" style=""> Model Manager</button>`)
|
||||||
|
.on('click', () => {
|
||||||
|
const overlay = showOverlay('The manager are being setup..');
|
||||||
|
window.cvat.autoAnnotation.manager.reset().show();
|
||||||
|
overlay.remove();
|
||||||
|
}).appendTo('#dashboardManageButtons');
|
||||||
|
});
|
||||||
|
|
||||||
|
window.addEventListener('dashboardReady', (event) => {
|
||||||
|
const elements = $('.dashboardItem');
|
||||||
|
const tids = Array.from(elements, el => +el.getAttribute('tid'));
|
||||||
|
|
||||||
|
window.cvat.autoAnnotation.server.meta(tids, (data) => {
|
||||||
|
window.cvat.autoAnnotation.data = data;
|
||||||
|
|
||||||
|
elements.each(function setupDashboardItem() {
|
||||||
|
const elem = $(this);
|
||||||
|
const tid = +elem.attr('tid');
|
||||||
|
|
||||||
|
const button = $('<button> Run Auto Annotation </button>').addClass('regular dashboardButtonUI');
|
||||||
|
button[0].setupRun = function setupRun() {
|
||||||
|
const self = $(this);
|
||||||
|
const taskInfo = event.detail.filter(task => task.id === tid)[0];
|
||||||
|
self.text('Run Auto Annotation').off('click').on('click', () => {
|
||||||
|
window.cvat.autoAnnotation.runner.reset(taskInfo, self).show();
|
||||||
|
});
|
||||||
|
};
|
||||||
|
|
||||||
|
button[0].setupCancel = function setupCancel() {
|
||||||
|
const self = $(this);
|
||||||
|
self.off('click').text('Cancel Auto Annotation').on('click', () => {
|
||||||
|
userConfirm('Process will be canceled. Are you sure?', () => {
|
||||||
|
window.cvat.autoAnnotation.server.cancel(tid, () => {
|
||||||
|
this.setupRun();
|
||||||
|
}, (message) => {
|
||||||
|
showMessage(message);
|
||||||
|
});
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
window.cvat.autoAnnotation.server.check(
|
||||||
|
window.cvat.autoAnnotation.data.run[tid].rq_id,
|
||||||
|
() => {
|
||||||
|
this.setupRun();
|
||||||
|
},
|
||||||
|
(error) => {
|
||||||
|
button[0].setupRun();
|
||||||
|
button.text('Annotation has failed');
|
||||||
|
button.title(error);
|
||||||
|
},
|
||||||
|
(progress) => {
|
||||||
|
button.text(`Cancel Auto Annotation (${progress.toString().slice(0, 4)})%`);
|
||||||
|
},
|
||||||
|
);
|
||||||
|
};
|
||||||
|
|
||||||
|
const taskStatus = window.cvat.autoAnnotation.data.run[tid];
|
||||||
|
if (taskStatus && ['queued', 'started'].includes(taskStatus.status)) {
|
||||||
|
button[0].setupCancel();
|
||||||
|
} else {
|
||||||
|
button[0].setupRun();
|
||||||
|
}
|
||||||
|
|
||||||
|
button.appendTo(elem.find('div.dashboardButtonsUI')[0]);
|
||||||
|
});
|
||||||
|
}, (error) => {
|
||||||
|
showMessage(`Cannot get models meta information: ${error}`);
|
||||||
|
});
|
||||||
|
});
|
||||||
@ -0,0 +1,83 @@
|
|||||||
|
#annotatorManagerContent, #annotatorRunnerContent {
|
||||||
|
width: 800px;
|
||||||
|
height: 300px;
|
||||||
|
}
|
||||||
|
|
||||||
|
#annotatorManagerButton {
|
||||||
|
padding: 7px;
|
||||||
|
margin-left: 4px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable {
|
||||||
|
width: 100%;
|
||||||
|
color:#666;
|
||||||
|
text-shadow: 1px 1px 0px #fff;
|
||||||
|
background:#D2D3D4;
|
||||||
|
border:#ccc 1px solid;
|
||||||
|
border-radius: 3px;
|
||||||
|
box-shadow: 0 1px 2px black;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable th {
|
||||||
|
border-top: 1px solid #fafafa;
|
||||||
|
border-bottom: 1px solid #e0e0e0;
|
||||||
|
background: #ededed;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable th:first-child {
|
||||||
|
text-align: left;
|
||||||
|
padding-left:20px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:first-child th:first-child {
|
||||||
|
border-top-left-radius:3px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:first-child th:last-child {
|
||||||
|
border-top-right-radius:3px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr {
|
||||||
|
text-align: center;
|
||||||
|
padding-left: 20px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable td:first-child {
|
||||||
|
text-align: left;
|
||||||
|
padding-left: 20px;
|
||||||
|
border-left: 0;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable td {
|
||||||
|
padding: 18px;
|
||||||
|
border-top: 1px solid #ffffff;
|
||||||
|
border-bottom:1px solid #e0e0e0;
|
||||||
|
border-left: 1px solid #e0e0e0;
|
||||||
|
background: #fafafa;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr.even td {
|
||||||
|
background: #f6f6f6;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:last-child td {
|
||||||
|
border-bottom:0;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:last-child td:first-child {
|
||||||
|
border-bottom-left-radius:3px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:last-child td:last-child {
|
||||||
|
border-bottom-right-radius:3px;
|
||||||
|
}
|
||||||
|
|
||||||
|
.modelsTable tr:hover td {
|
||||||
|
background: #f2f2f2;
|
||||||
|
}
|
||||||
|
|
||||||
|
#annotatorManagerUploadModel {
|
||||||
|
float: left;
|
||||||
|
padding-left: 3%;
|
||||||
|
width: 40%;
|
||||||
|
}
|
||||||
@ -0,0 +1,19 @@
|
|||||||
|
|
||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from django.urls import path
|
||||||
|
from . import views
|
||||||
|
|
||||||
|
urlpatterns = [
|
||||||
|
path("create", views.create_model),
|
||||||
|
path("update/<int:mid>", views.update_model),
|
||||||
|
path("delete/<int:mid>", views.delete_model),
|
||||||
|
|
||||||
|
path("start/<int:mid>/<int:tid>", views.start_annotation),
|
||||||
|
path("check/<str:rq_id>", views.check),
|
||||||
|
path("cancel/<int:tid>", views.cancel),
|
||||||
|
|
||||||
|
path("meta/get", views.get_meta_info),
|
||||||
|
]
|
||||||
@ -0,0 +1,260 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
import django_rq
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
|
||||||
|
from django.http import HttpResponse, JsonResponse, HttpResponseBadRequest
|
||||||
|
from django.db.models import Q
|
||||||
|
from rules.contrib.views import permission_required, objectgetter
|
||||||
|
|
||||||
|
from cvat.apps.authentication.decorators import login_required
|
||||||
|
from cvat.apps.engine.models import Task as TaskModel
|
||||||
|
from cvat.apps.authentication.auth import has_admin_role
|
||||||
|
from cvat.apps.engine.log import slogger
|
||||||
|
|
||||||
|
from .model_loader import load_label_map
|
||||||
|
from . import model_manager
|
||||||
|
from .models import AnnotationModel
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["engine.task.change"],
|
||||||
|
fn=objectgetter(TaskModel, "tid"), raise_exception=True)
|
||||||
|
def cancel(request, tid):
|
||||||
|
try:
|
||||||
|
queue = django_rq.get_queue("low")
|
||||||
|
job = queue.fetch_job("auto_annotation.run.{}".format(tid))
|
||||||
|
if job is None or job.is_finished or job.is_failed:
|
||||||
|
raise Exception("Task is not being annotated currently")
|
||||||
|
elif "cancel" not in job.meta:
|
||||||
|
job.meta["cancel"] = True
|
||||||
|
job.save()
|
||||||
|
|
||||||
|
except Exception as ex:
|
||||||
|
try:
|
||||||
|
slogger.task[tid].exception("cannot cancel auto annotation for task #{}".format(tid), exc_info=True)
|
||||||
|
except Exception as logger_ex:
|
||||||
|
slogger.glob.exception("exception was occured during cancel auto annotation request for task {}: {}".format(tid, str(logger_ex)), exc_info=True)
|
||||||
|
return HttpResponseBadRequest(str(ex))
|
||||||
|
|
||||||
|
return HttpResponse()
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["auto_annotation.model.create"], raise_exception=True)
|
||||||
|
def create_model(request):
|
||||||
|
if request.method != 'POST':
|
||||||
|
return HttpResponseBadRequest("Only POST requests are accepted")
|
||||||
|
|
||||||
|
try:
|
||||||
|
params = request.POST
|
||||||
|
storage = params["storage"]
|
||||||
|
name = params["name"]
|
||||||
|
is_shared = params["shared"].lower() == "true"
|
||||||
|
if is_shared and not has_admin_role(request.user):
|
||||||
|
raise Exception("Only admin can create shared models")
|
||||||
|
|
||||||
|
files = request.FILES if storage == "local" else params
|
||||||
|
model = files["xml"]
|
||||||
|
weights = files["bin"]
|
||||||
|
labelmap = files["json"]
|
||||||
|
interpretation_script = files["py"]
|
||||||
|
owner = request.user
|
||||||
|
|
||||||
|
rq_id = model_manager.create_or_update(
|
||||||
|
dl_model_id=None,
|
||||||
|
name=name,
|
||||||
|
model_file=model,
|
||||||
|
weights_file=weights,
|
||||||
|
labelmap_file=labelmap,
|
||||||
|
interpretation_file=interpretation_script,
|
||||||
|
owner=owner,
|
||||||
|
storage=storage,
|
||||||
|
is_shared=is_shared,
|
||||||
|
)
|
||||||
|
|
||||||
|
return JsonResponse({"id": rq_id})
|
||||||
|
except Exception as e:
|
||||||
|
return HttpResponseBadRequest(str(e))
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["auto_annotation.model.update"],
|
||||||
|
fn=objectgetter(AnnotationModel, "mid"), raise_exception=True)
|
||||||
|
def update_model(request, mid):
|
||||||
|
if request.method != 'POST':
|
||||||
|
return HttpResponseBadRequest("Only POST requests are accepted")
|
||||||
|
|
||||||
|
try:
|
||||||
|
params = request.POST
|
||||||
|
storage = params["storage"]
|
||||||
|
name = params.get("name")
|
||||||
|
is_shared = params.get("shared")
|
||||||
|
is_shared = is_shared.lower() == "true" if is_shared else None
|
||||||
|
if is_shared and not has_admin_role(request.user):
|
||||||
|
raise Exception("Only admin can create shared models")
|
||||||
|
files = request.FILES
|
||||||
|
model = files.get("xml")
|
||||||
|
weights = files.get("bin")
|
||||||
|
labelmap = files.get("json")
|
||||||
|
interpretation_script = files.get("py")
|
||||||
|
|
||||||
|
rq_id = model_manager.create_or_update(
|
||||||
|
dl_model_id=mid,
|
||||||
|
name=name,
|
||||||
|
model_file=model,
|
||||||
|
weights_file=weights,
|
||||||
|
labelmap_file=labelmap,
|
||||||
|
interpretation_file=interpretation_script,
|
||||||
|
owner=None,
|
||||||
|
storage=storage,
|
||||||
|
is_shared=is_shared,
|
||||||
|
)
|
||||||
|
|
||||||
|
return JsonResponse({"id": rq_id})
|
||||||
|
except Exception as e:
|
||||||
|
return HttpResponseBadRequest(str(e))
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["auto_annotation.model.delete"],
|
||||||
|
fn=objectgetter(AnnotationModel, "mid"), raise_exception=True)
|
||||||
|
def delete_model(request, mid):
|
||||||
|
if request.method != 'DELETE':
|
||||||
|
return HttpResponseBadRequest("Only DELETE requests are accepted")
|
||||||
|
model_manager.delete(mid)
|
||||||
|
return HttpResponse()
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
def get_meta_info(request):
|
||||||
|
try:
|
||||||
|
tids = json.loads(request.body.decode('utf-8'))
|
||||||
|
response = {
|
||||||
|
"admin": has_admin_role(request.user),
|
||||||
|
"models": [],
|
||||||
|
"run": {},
|
||||||
|
}
|
||||||
|
dl_model_list = list(AnnotationModel.objects.filter(Q(owner=request.user) | Q(primary=True) | Q(shared=True)).order_by('-created_date'))
|
||||||
|
for dl_model in dl_model_list:
|
||||||
|
labels = []
|
||||||
|
if dl_model.labelmap_file and os.path.exists(dl_model.labelmap_file.name):
|
||||||
|
with dl_model.labelmap_file.open('r') as f:
|
||||||
|
labels = list(json.load(f)["label_map"].values())
|
||||||
|
|
||||||
|
response["models"].append({
|
||||||
|
"id": dl_model.id,
|
||||||
|
"name": dl_model.name,
|
||||||
|
"primary": dl_model.primary,
|
||||||
|
"uploadDate": dl_model.created_date,
|
||||||
|
"updateDate": dl_model.updated_date,
|
||||||
|
"labels": labels,
|
||||||
|
})
|
||||||
|
|
||||||
|
queue = django_rq.get_queue("low")
|
||||||
|
for tid in tids:
|
||||||
|
rq_id = "auto_annotation.run.{}".format(tid)
|
||||||
|
job = queue.fetch_job(rq_id)
|
||||||
|
if job is not None:
|
||||||
|
response["run"][tid] = {
|
||||||
|
"status": job.get_status(),
|
||||||
|
"rq_id": rq_id,
|
||||||
|
}
|
||||||
|
|
||||||
|
return JsonResponse(response)
|
||||||
|
except Exception as e:
|
||||||
|
return HttpResponseBadRequest(str(e))
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["engine.task.change"],
|
||||||
|
fn=objectgetter(TaskModel, "tid"), raise_exception=True)
|
||||||
|
@permission_required(perm=["auto_annotation.model.access"],
|
||||||
|
fn=objectgetter(AnnotationModel, "mid"), raise_exception=True)
|
||||||
|
def start_annotation(request, mid, tid):
|
||||||
|
slogger.glob.info("auto annotation create request for task {} via DL model {}".format(tid, mid))
|
||||||
|
try:
|
||||||
|
db_task = TaskModel.objects.get(pk=tid)
|
||||||
|
queue = django_rq.get_queue("low")
|
||||||
|
job = queue.fetch_job("auto_annotation.run.{}".format(tid))
|
||||||
|
if job is not None and (job.is_started or job.is_queued):
|
||||||
|
raise Exception("The process is already running")
|
||||||
|
|
||||||
|
data = json.loads(request.body.decode('utf-8'))
|
||||||
|
|
||||||
|
should_reset = data["reset"]
|
||||||
|
user_defined_labels_mapping = data["labels"]
|
||||||
|
|
||||||
|
dl_model = AnnotationModel.objects.get(pk=mid)
|
||||||
|
|
||||||
|
model_file_path = dl_model.model_file.name
|
||||||
|
weights_file_path = dl_model.weights_file.name
|
||||||
|
labelmap_file = dl_model.labelmap_file.name
|
||||||
|
convertation_file_path = dl_model.interpretation_file.name
|
||||||
|
|
||||||
|
db_labels = db_task.label_set.prefetch_related("attributespec_set").all()
|
||||||
|
db_attributes = {db_label.id:
|
||||||
|
{db_attr.name: db_attr.id for db_attr in db_label.attributespec_set.all()} for db_label in db_labels}
|
||||||
|
db_labels = {db_label.name:db_label.id for db_label in db_labels}
|
||||||
|
|
||||||
|
model_labels = {value: key for key, value in load_label_map(labelmap_file).items()}
|
||||||
|
|
||||||
|
labels_mapping = {}
|
||||||
|
for user_model_label, user_db_label in user_defined_labels_mapping.items():
|
||||||
|
if user_model_label in model_labels and user_db_label in db_labels:
|
||||||
|
labels_mapping[int(model_labels[user_model_label])] = db_labels[user_db_label]
|
||||||
|
|
||||||
|
if not labels_mapping:
|
||||||
|
raise Exception("No labels found for annotation")
|
||||||
|
|
||||||
|
rq_id="auto_annotation.run.{}".format(tid)
|
||||||
|
queue.enqueue_call(func=model_manager.run_inference_thread,
|
||||||
|
args=(
|
||||||
|
tid,
|
||||||
|
model_file_path,
|
||||||
|
weights_file_path,
|
||||||
|
labels_mapping,
|
||||||
|
db_attributes,
|
||||||
|
convertation_file_path,
|
||||||
|
should_reset,
|
||||||
|
request.user,
|
||||||
|
),
|
||||||
|
job_id = rq_id,
|
||||||
|
timeout=604800) # 7 days
|
||||||
|
|
||||||
|
slogger.task[tid].info("auto annotation job enqueued")
|
||||||
|
|
||||||
|
except Exception as ex:
|
||||||
|
try:
|
||||||
|
slogger.task[tid].exception("exception was occurred during annotation request", exc_info=True)
|
||||||
|
except Exception as logger_ex:
|
||||||
|
slogger.glob.exception("exception was occurred during create auto annotation request for task {}: {}".format(tid, str(logger_ex)), exc_info=True)
|
||||||
|
return HttpResponseBadRequest(str(ex))
|
||||||
|
|
||||||
|
return JsonResponse({"id": rq_id})
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
def check(request, rq_id):
|
||||||
|
try:
|
||||||
|
target_queue = "low" if "auto_annotation.run" in rq_id else "default"
|
||||||
|
queue = django_rq.get_queue(target_queue)
|
||||||
|
job = queue.fetch_job(rq_id)
|
||||||
|
if job is not None and "cancel" in job.meta:
|
||||||
|
return JsonResponse({"status": "finished"})
|
||||||
|
data = {}
|
||||||
|
if job is None:
|
||||||
|
data["status"] = "unknown"
|
||||||
|
elif job.is_queued:
|
||||||
|
data["status"] = "queued"
|
||||||
|
elif job.is_started:
|
||||||
|
data["status"] = "started"
|
||||||
|
data["progress"] = job.meta["progress"] if "progress" in job.meta else ""
|
||||||
|
elif job.is_finished:
|
||||||
|
data["status"] = "finished"
|
||||||
|
job.delete()
|
||||||
|
else:
|
||||||
|
data["status"] = "failed"
|
||||||
|
data["error"] = job.exc_info
|
||||||
|
job.delete()
|
||||||
|
|
||||||
|
except Exception:
|
||||||
|
data["status"] = "unknown"
|
||||||
|
|
||||||
|
return JsonResponse(data)
|
||||||
File diff suppressed because it is too large
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|
Before Width: | Height: | Size: 1.5 KiB |
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|
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|
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|
Before Width: | Height: | Size: 3.0 KiB After Width: | Height: | Size: 5.5 KiB |
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|
Before Width: | Height: | Size: 1.8 KiB After Width: | Height: | Size: 2.2 KiB |
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Load Diff
File diff suppressed because one or more lines are too long
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|
Before Width: | Height: | Size: 1.7 KiB After Width: | Height: | Size: 1.4 KiB |
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Load Diff
@ -1,38 +0,0 @@
|
|||||||
<!--
|
|
||||||
Copyright (C) 2018 Intel Corporation
|
|
||||||
|
|
||||||
SPDX-License-Identifier: MIT
|
|
||||||
-->
|
|
||||||
<div class="dashboardTaskUI" id="dashboardTask_{{item.id}}">
|
|
||||||
<center class="dashboardTitleWrapper">
|
|
||||||
<label class="semiBold h1 dashboardTaskNameLabel selectable"> {{ item.name }} </label>
|
|
||||||
</center>
|
|
||||||
<center class="dashboardTitleWrapper">
|
|
||||||
<label class="regular dashboardStatusLabel"> {{ item.status }} </label>
|
|
||||||
</center>
|
|
||||||
<div class="dashboardTaskIntro" style='background-image: url("/get/task/{{item.id}}/frame/0")'> </div>
|
|
||||||
<div class="dashboardButtonsUI">
|
|
||||||
<button class="dashboardDumpAnnotation semiBold dashboardButtonUI"> Dump Annotation </button>
|
|
||||||
<button class="dashboardUploadAnnotation semiBold dashboardButtonUI"> Upload Annotation </button>
|
|
||||||
<button class="dashboardUpdateTask semiBold dashboardButtonUI"> Update Task </button>
|
|
||||||
<button class="dashboardDeleteTask semiBold dashboardButtonUI"> Delete Task </button>
|
|
||||||
{%if item.bug_tracker %}
|
|
||||||
<button class="dashboardOpenTrackerButton semiBold dashboardButtonUI"> Open Bug Tracker </button>
|
|
||||||
<a class="dashboardBugTrackerLink" href='{{item.bug_tracker}}' style="display: none;"> </a>
|
|
||||||
{% endif %}
|
|
||||||
</div>
|
|
||||||
<div class="dashboardJobsUI">
|
|
||||||
<center class="dashboardTitleWrapper">
|
|
||||||
<label class="regular h1"> Jobs </label>
|
|
||||||
</center>
|
|
||||||
<table class="dashboardJobList regular">
|
|
||||||
{% for segm in item.segment_set.all %}
|
|
||||||
{% for job in segm.job_set.all %}
|
|
||||||
<tr>
|
|
||||||
<td> <a href="{{base_url}}?id={{job.id}}"> {{base_url}}?id={{job.id}} </a> </td>
|
|
||||||
</tr>
|
|
||||||
{% endfor %}
|
|
||||||
{% endfor %}
|
|
||||||
</table>
|
|
||||||
</div>
|
|
||||||
</div>
|
|
||||||
@ -0,0 +1,31 @@
|
|||||||
|
# Semi-Automatic Segmentation with [Deep Extreme Cut](http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr/)
|
||||||
|
|
||||||
|
## About the application
|
||||||
|
|
||||||
|
The application allows to use deep learning models for semi-automatic semantic and instance segmentation.
|
||||||
|
You can get a segmentation polygon from four (or more) extreme points of an object.
|
||||||
|
This application uses the pre-trained DEXTR model which has been converted to Inference Engine format.
|
||||||
|
|
||||||
|
We are grateful to K.K. Maninis, S. Caelles, J. Pont-Tuset, and L. Van Gool who permitted using their models in our tool
|
||||||
|
|
||||||
|
## Build docker image
|
||||||
|
```bash
|
||||||
|
# OpenVINO component is also needed
|
||||||
|
docker-compose -f docker-compose.yml -f components/openvino/docker-compose.openvino.yml -f cvat/apps/dextr_segmentation/docker-compose.dextr.yml build
|
||||||
|
```
|
||||||
|
|
||||||
|
## Run docker container
|
||||||
|
```bash
|
||||||
|
docker-compose -f docker-compose.yml -f components/openvino/docker-compose.openvino.yml -f cvat/apps/dextr_segmentation/docker-compose.dextr.yml up -d
|
||||||
|
```
|
||||||
|
|
||||||
|
## Using
|
||||||
|
|
||||||
|
1. Open a job
|
||||||
|
2. Select "Auto Segmentation" in the list of shapes
|
||||||
|
3. Run the draw mode as usually (by press the "Create Shape" button or by "N" shortcut)
|
||||||
|
4. Click four-six (or more if it's need) extreme points of an object
|
||||||
|
5. Close the draw mode as usually (by shortcut or pressing the button "Stop Creation")
|
||||||
|
6. Wait a moment and you will get a class agnostic annotation polygon
|
||||||
|
7. You can close an annotation request if it is too long
|
||||||
|
(in case if it is queued to rq worker and all workers are busy)
|
||||||
@ -0,0 +1,7 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from cvat.settings.base import JS_3RDPARTY
|
||||||
|
|
||||||
|
JS_3RDPARTY['engine'] = JS_3RDPARTY.get('engine', []) + ['dextr_segmentation/js/enginePlugin.js']
|
||||||
@ -0,0 +1,8 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from django.apps import AppConfig
|
||||||
|
|
||||||
|
class DextrSegmentationConfig(AppConfig):
|
||||||
|
name = 'dextr_segmentation'
|
||||||
@ -0,0 +1,105 @@
|
|||||||
|
|
||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from cvat.apps.auto_annotation.inference_engine import make_plugin, make_network
|
||||||
|
|
||||||
|
import os
|
||||||
|
import cv2
|
||||||
|
import PIL
|
||||||
|
import numpy as np
|
||||||
|
|
||||||
|
_IE_CPU_EXTENSION = os.getenv("IE_CPU_EXTENSION", "libcpu_extension_avx2.so")
|
||||||
|
_IE_PLUGINS_PATH = os.getenv("IE_PLUGINS_PATH", None)
|
||||||
|
|
||||||
|
_DEXTR_MODEL_DIR = os.getenv("DEXTR_MODEL_DIR", None)
|
||||||
|
_DEXTR_PADDING = 50
|
||||||
|
_DEXTR_TRESHOLD = 0.9
|
||||||
|
_DEXTR_SIZE = 512
|
||||||
|
|
||||||
|
class DEXTR_HANDLER:
|
||||||
|
def __init__(self):
|
||||||
|
self._plugin = None
|
||||||
|
self._network = None
|
||||||
|
self._exec_network = None
|
||||||
|
self._input_blob = None
|
||||||
|
self._output_blob = None
|
||||||
|
if not _DEXTR_MODEL_DIR:
|
||||||
|
raise Exception("DEXTR_MODEL_DIR is not defined")
|
||||||
|
|
||||||
|
|
||||||
|
def handle(self, im_path, points):
|
||||||
|
# Lazy initialization
|
||||||
|
if not self._plugin:
|
||||||
|
self._plugin = make_plugin()
|
||||||
|
self._network = make_network(os.path.join(_DEXTR_MODEL_DIR, 'dextr.xml'),
|
||||||
|
os.path.join(_DEXTR_MODEL_DIR, 'dextr.bin'))
|
||||||
|
self._input_blob = next(iter(self._network.inputs))
|
||||||
|
self._output_blob = next(iter(self._network.outputs))
|
||||||
|
self._exec_network = self._plugin.load(network=self._network)
|
||||||
|
|
||||||
|
image = PIL.Image.open(im_path)
|
||||||
|
numpy_image = np.array(image)
|
||||||
|
points = np.asarray([[int(p["x"]), int(p["y"])] for p in points], dtype=int)
|
||||||
|
bounding_box = (
|
||||||
|
max(min(points[:, 0]) - _DEXTR_PADDING, 0),
|
||||||
|
max(min(points[:, 1]) - _DEXTR_PADDING, 0),
|
||||||
|
min(max(points[:, 0]) + _DEXTR_PADDING, numpy_image.shape[1] - 1),
|
||||||
|
min(max(points[:, 1]) + _DEXTR_PADDING, numpy_image.shape[0] - 1)
|
||||||
|
)
|
||||||
|
|
||||||
|
# Prepare an image
|
||||||
|
numpy_cropped = np.array(image.crop(bounding_box))
|
||||||
|
resized = cv2.resize(numpy_cropped, (_DEXTR_SIZE, _DEXTR_SIZE),
|
||||||
|
interpolation = cv2.INTER_CUBIC).astype(np.float32)
|
||||||
|
|
||||||
|
# Make a heatmap
|
||||||
|
points = points - [min(points[:, 0]), min(points[:, 1])] + [_DEXTR_PADDING, _DEXTR_PADDING]
|
||||||
|
points = (points * [_DEXTR_SIZE / numpy_cropped.shape[1], _DEXTR_SIZE / numpy_cropped.shape[0]]).astype(int)
|
||||||
|
heatmap = np.zeros(shape=resized.shape[:2], dtype=np.float64)
|
||||||
|
for point in points:
|
||||||
|
gaussian_x_axis = np.arange(0, _DEXTR_SIZE, 1, float) - point[0]
|
||||||
|
gaussian_y_axis = np.arange(0, _DEXTR_SIZE, 1, float)[:, np.newaxis] - point[1]
|
||||||
|
gaussian = np.exp(-4 * np.log(2) * ((gaussian_x_axis ** 2 + gaussian_y_axis ** 2) / 100)).astype(np.float64)
|
||||||
|
heatmap = np.maximum(heatmap, gaussian)
|
||||||
|
cv2.normalize(heatmap, heatmap, 0, 255, cv2.NORM_MINMAX)
|
||||||
|
|
||||||
|
# Concat an image and a heatmap
|
||||||
|
input_dextr = np.concatenate((resized, heatmap[:, :, np.newaxis].astype(resized.dtype)), axis=2)
|
||||||
|
input_dextr = input_dextr.transpose((2,0,1))
|
||||||
|
|
||||||
|
pred = self._exec_network.infer(inputs={self._input_blob: input_dextr[np.newaxis, ...]})[self._output_blob][0, 0, :, :]
|
||||||
|
pred = cv2.resize(pred, tuple(reversed(numpy_cropped.shape[:2])), interpolation = cv2.INTER_CUBIC)
|
||||||
|
result = np.zeros(numpy_image.shape[:2])
|
||||||
|
result[bounding_box[1]:bounding_box[1] + pred.shape[0], bounding_box[0]:bounding_box[0] + pred.shape[1]] = pred > _DEXTR_TRESHOLD
|
||||||
|
|
||||||
|
# Convert a mask to a polygon
|
||||||
|
result = np.array(result, dtype=np.uint8)
|
||||||
|
cv2.normalize(result,result,0,255,cv2.NORM_MINMAX)
|
||||||
|
contours = None
|
||||||
|
if int(cv2.__version__.split('.')[0]) > 3:
|
||||||
|
contours = cv2.findContours(result, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_KCOS)[0]
|
||||||
|
else:
|
||||||
|
contours = cv2.findContours(result, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_KCOS)[1]
|
||||||
|
|
||||||
|
contours = max(contours, key=lambda arr: arr.size)
|
||||||
|
if contours.shape.count(1):
|
||||||
|
contours = np.squeeze(contours)
|
||||||
|
if contours.size < 3 * 2:
|
||||||
|
raise Exception('Less then three point have been detected. Can not build a polygon.')
|
||||||
|
|
||||||
|
result = ""
|
||||||
|
for point in contours:
|
||||||
|
result += "{},{} ".format(int(point[0]), int(point[1]))
|
||||||
|
result = result[:-1]
|
||||||
|
|
||||||
|
return result
|
||||||
|
|
||||||
|
def __del__(self):
|
||||||
|
if self._exec_network:
|
||||||
|
del self._exec_network
|
||||||
|
if self._network:
|
||||||
|
del self._network
|
||||||
|
if self._plugin:
|
||||||
|
del self._plugin
|
||||||
@ -0,0 +1,14 @@
|
|||||||
|
#
|
||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
#
|
||||||
|
|
||||||
|
version: "2.3"
|
||||||
|
|
||||||
|
services:
|
||||||
|
cvat:
|
||||||
|
build:
|
||||||
|
context: .
|
||||||
|
args:
|
||||||
|
WITH_DEXTR: "yes"
|
||||||
@ -0,0 +1,213 @@
|
|||||||
|
/*
|
||||||
|
* Copyright (C) 2018 Intel Corporation
|
||||||
|
*
|
||||||
|
* SPDX-License-Identifier: MIT
|
||||||
|
*/
|
||||||
|
|
||||||
|
/* global
|
||||||
|
AREA_TRESHOLD:false
|
||||||
|
PolyShapeModel:false
|
||||||
|
ShapeCreatorModel:true
|
||||||
|
ShapeCreatorView:true
|
||||||
|
showMessage:false
|
||||||
|
*/
|
||||||
|
|
||||||
|
/* eslint no-underscore-dangle: 0 */
|
||||||
|
|
||||||
|
window.addEventListener('DOMContentLoaded', () => {
|
||||||
|
$('<option value="auto_segmentation" class="regular"> Auto Segmentation </option>').appendTo('#shapeTypeSelector');
|
||||||
|
|
||||||
|
const dextrCancelButtonId = 'dextrCancelButton';
|
||||||
|
const dextrOverlay = $(`
|
||||||
|
<div class="modal hidden force-modal">
|
||||||
|
<div class="modal-content" style="width: 300px; height: 70px;">
|
||||||
|
<center> <label class="regular h2"> Segmentation request is being processed </label></center>
|
||||||
|
<center style="margin-top: 5px;">
|
||||||
|
<button id="${dextrCancelButtonId}" class="regular h2" style="width: 250px;"> Cancel </button>
|
||||||
|
</center>
|
||||||
|
</div>
|
||||||
|
</div>`).appendTo('body');
|
||||||
|
|
||||||
|
const dextrCancelButton = $(`#${dextrCancelButtonId}`);
|
||||||
|
dextrCancelButton.on('click', () => {
|
||||||
|
dextrCancelButton.prop('disabled', true);
|
||||||
|
$.ajax({
|
||||||
|
url: `/dextr/cancel/${window.cvat.job.id}`,
|
||||||
|
type: 'GET',
|
||||||
|
error: (errorData) => {
|
||||||
|
const message = `Can not cancel segmentation. Code: ${errorData.status}.
|
||||||
|
Message: ${errorData.responseText || errorData.statusText}`;
|
||||||
|
showMessage(message);
|
||||||
|
},
|
||||||
|
complete: () => {
|
||||||
|
dextrCancelButton.prop('disabled', false);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
});
|
||||||
|
|
||||||
|
function ShapeCreatorModelWrapper(OriginalClass) {
|
||||||
|
// Constructor will patch some properties for a created instance
|
||||||
|
function constructorDecorator(...args) {
|
||||||
|
const instance = new OriginalClass(...args);
|
||||||
|
|
||||||
|
// Decorator for the defaultType property
|
||||||
|
Object.defineProperty(instance, 'defaultType', {
|
||||||
|
get: () => instance._defaultType,
|
||||||
|
set: (type) => {
|
||||||
|
if (!['box', 'points', 'polygon', 'polyline', 'auto_segmentation'].includes(type)) {
|
||||||
|
throw Error(`Unknown shape type found ${type}`);
|
||||||
|
}
|
||||||
|
instance._defaultType = type;
|
||||||
|
},
|
||||||
|
});
|
||||||
|
|
||||||
|
// Decorator for finish method.
|
||||||
|
const decoratedFinish = instance.finish;
|
||||||
|
instance.finish = (result) => {
|
||||||
|
if (instance._defaultType === 'auto_segmentation') {
|
||||||
|
try {
|
||||||
|
instance._defaultType = 'polygon';
|
||||||
|
decoratedFinish.call(instance, result);
|
||||||
|
} finally {
|
||||||
|
instance._defaultType = 'auto_segmentation';
|
||||||
|
}
|
||||||
|
} else {
|
||||||
|
decoratedFinish.call(instance, result);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
return instance;
|
||||||
|
}
|
||||||
|
|
||||||
|
constructorDecorator.prototype = OriginalClass.prototype;
|
||||||
|
constructorDecorator.prototype.constructor = constructorDecorator;
|
||||||
|
return constructorDecorator;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
function ShapeCreatorViewWrapper(OriginalClass) {
|
||||||
|
// Constructor will patch some properties for each instance
|
||||||
|
function constructorDecorator(...args) {
|
||||||
|
const instance = new OriginalClass(...args);
|
||||||
|
|
||||||
|
// Decorator for the _create() method.
|
||||||
|
// We save the decorated _create() and we will use it if type != 'auto_segmentation'
|
||||||
|
const decoratedCreate = instance._create;
|
||||||
|
instance._create = () => {
|
||||||
|
if (instance._type !== 'auto_segmentation') {
|
||||||
|
decoratedCreate.call(instance);
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
instance._drawInstance = instance._frameContent.polyline().draw({ snapToGrid: 0.1 }).addClass('shapeCreation').attr({
|
||||||
|
'stroke-width': 0,
|
||||||
|
z_order: Number.MAX_SAFE_INTEGER,
|
||||||
|
});
|
||||||
|
instance._createPolyEvents();
|
||||||
|
|
||||||
|
/* the _createPolyEvents method have added "drawdone"
|
||||||
|
* event handler which invalid for this case
|
||||||
|
* because of that reason we remove the handler and
|
||||||
|
* create the valid handler instead
|
||||||
|
*/
|
||||||
|
instance._drawInstance.off('drawdone').on('drawdone', (e) => {
|
||||||
|
let actualPoints = window.cvat.translate.points.canvasToActual(e.target.getAttribute('points'));
|
||||||
|
actualPoints = PolyShapeModel.convertStringToNumberArray(actualPoints);
|
||||||
|
|
||||||
|
if (actualPoints.length < 4) {
|
||||||
|
showMessage('It is need to specify minimum four extreme points for an object');
|
||||||
|
instance._controller.switchCreateMode(true);
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
const { frameWidth } = window.cvat.player.geometry;
|
||||||
|
const { frameHeight } = window.cvat.player.geometry;
|
||||||
|
for (let idx = 0; idx < actualPoints.length; idx += 1) {
|
||||||
|
const point = actualPoints[idx];
|
||||||
|
point.x = Math.clamp(point.x, 0, frameWidth);
|
||||||
|
point.y = Math.clamp(point.y, 0, frameHeight);
|
||||||
|
}
|
||||||
|
|
||||||
|
e.target.setAttribute('points',
|
||||||
|
window.cvat.translate.points.actualToCanvas(
|
||||||
|
PolyShapeModel.convertNumberArrayToString(actualPoints),
|
||||||
|
));
|
||||||
|
|
||||||
|
const polybox = e.target.getBBox();
|
||||||
|
const area = polybox.width * polybox.height;
|
||||||
|
|
||||||
|
if (area > AREA_TRESHOLD) {
|
||||||
|
$.ajax({
|
||||||
|
url: `/dextr/create/${window.cvat.job.id}`,
|
||||||
|
type: 'POST',
|
||||||
|
data: JSON.stringify({
|
||||||
|
frame: window.cvat.player.frames.current,
|
||||||
|
points: actualPoints,
|
||||||
|
}),
|
||||||
|
contentType: 'application/json',
|
||||||
|
success: () => {
|
||||||
|
function intervalCallback() {
|
||||||
|
$.ajax({
|
||||||
|
url: `/dextr/check/${window.cvat.job.id}`,
|
||||||
|
type: 'GET',
|
||||||
|
success: (jobData) => {
|
||||||
|
if (['queued', 'started'].includes(jobData.status)) {
|
||||||
|
if (jobData.status === 'queued') {
|
||||||
|
dextrCancelButton.prop('disabled', false);
|
||||||
|
}
|
||||||
|
setTimeout(intervalCallback, 1000);
|
||||||
|
} else {
|
||||||
|
dextrOverlay.addClass('hidden');
|
||||||
|
if (jobData.status === 'finished') {
|
||||||
|
if (jobData.result) {
|
||||||
|
instance._controller.finish({ points: jobData.result }, 'polygon');
|
||||||
|
}
|
||||||
|
} else if (jobData.status === 'failed') {
|
||||||
|
const message = `Segmentation has fallen. Error: '${jobData.stderr}'`;
|
||||||
|
showMessage(message);
|
||||||
|
} else {
|
||||||
|
let message = `Check segmentation request returned "${jobData.status}" status.`;
|
||||||
|
if (jobData.stderr) {
|
||||||
|
message += ` Error: ${jobData.stderr}`;
|
||||||
|
}
|
||||||
|
showMessage(message);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
error: (errorData) => {
|
||||||
|
dextrOverlay.addClass('hidden');
|
||||||
|
const message = `Can not check segmentation. Code: ${errorData.status}.`
|
||||||
|
+ ` Message: ${errorData.responseText || errorData.statusText}`;
|
||||||
|
showMessage(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
dextrCancelButton.prop('disabled', true);
|
||||||
|
dextrOverlay.removeClass('hidden');
|
||||||
|
setTimeout(intervalCallback, 1000);
|
||||||
|
},
|
||||||
|
error: (errorData) => {
|
||||||
|
const message = `Can not cancel ReID process. Code: ${errorData.status}.`
|
||||||
|
+ ` Message: ${errorData.responseText || errorData.statusText}`;
|
||||||
|
showMessage(message);
|
||||||
|
},
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
instance._controller.switchCreateMode(true);
|
||||||
|
}); // end of "drawdone" handler
|
||||||
|
}; // end of _create() method
|
||||||
|
|
||||||
|
return instance;
|
||||||
|
} // end of constructorDecorator()
|
||||||
|
|
||||||
|
constructorDecorator.prototype = OriginalClass.prototype;
|
||||||
|
constructorDecorator.prototype.constructor = constructorDecorator;
|
||||||
|
return constructorDecorator;
|
||||||
|
} // end of ShapeCreatorViewWrapper
|
||||||
|
|
||||||
|
// Apply patch for classes
|
||||||
|
ShapeCreatorModel = ShapeCreatorModelWrapper(ShapeCreatorModel);
|
||||||
|
ShapeCreatorView = ShapeCreatorViewWrapper(ShapeCreatorView);
|
||||||
|
});
|
||||||
@ -0,0 +1,12 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from django.urls import path
|
||||||
|
from . import views
|
||||||
|
|
||||||
|
urlpatterns = [
|
||||||
|
path('create/<int:jid>', views.create),
|
||||||
|
path('cancel/<int:jid>', views.cancel),
|
||||||
|
path('check/<int:jid>', views.check)
|
||||||
|
]
|
||||||
@ -0,0 +1,127 @@
|
|||||||
|
# Copyright (C) 2018 Intel Corporation
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: MIT
|
||||||
|
|
||||||
|
from django.http import HttpResponse, HttpResponseBadRequest, JsonResponse
|
||||||
|
from cvat.apps.authentication.decorators import login_required
|
||||||
|
from rules.contrib.views import permission_required, objectgetter
|
||||||
|
|
||||||
|
from cvat.apps.engine.models import Job
|
||||||
|
from cvat.apps.engine.log import slogger
|
||||||
|
from cvat.apps.dextr_segmentation.dextr import DEXTR_HANDLER
|
||||||
|
|
||||||
|
import django_rq
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
import rq
|
||||||
|
|
||||||
|
__RQ_QUEUE_NAME = "default"
|
||||||
|
__DEXTR_HANDLER = DEXTR_HANDLER()
|
||||||
|
|
||||||
|
def _dextr_thread(im_path, points):
|
||||||
|
job = rq.get_current_job()
|
||||||
|
job.meta["result"] = __DEXTR_HANDLER.handle(im_path, points)
|
||||||
|
job.save_meta()
|
||||||
|
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["engine.job.change"],
|
||||||
|
fn=objectgetter(Job, "jid"), raise_exception=True)
|
||||||
|
def create(request, jid):
|
||||||
|
try:
|
||||||
|
data = json.loads(request.body.decode("utf-8"))
|
||||||
|
|
||||||
|
points = data["points"]
|
||||||
|
frame = int(data["frame"])
|
||||||
|
username = request.user.username
|
||||||
|
|
||||||
|
slogger.job[jid].info("create dextr request for the JOB: {} ".format(jid)
|
||||||
|
+ "by the USER: {} on the FRAME: {}".format(username, frame))
|
||||||
|
|
||||||
|
db_task = Job.objects.select_related("segment__task").get(id=jid).segment.task
|
||||||
|
im_path = os.path.realpath(db_task.get_frame_path(frame))
|
||||||
|
|
||||||
|
queue = django_rq.get_queue(__RQ_QUEUE_NAME)
|
||||||
|
rq_id = "dextr.create/{}/{}".format(jid, username)
|
||||||
|
job = queue.fetch_job(rq_id)
|
||||||
|
|
||||||
|
if job is not None and (job.is_started or job.is_queued):
|
||||||
|
if "cancel" not in job.meta:
|
||||||
|
raise Exception("Segmentation process has been already run for the " +
|
||||||
|
"JOB: {} and the USER: {}".format(jid, username))
|
||||||
|
else:
|
||||||
|
job.delete()
|
||||||
|
|
||||||
|
queue.enqueue_call(func=_dextr_thread,
|
||||||
|
args=(im_path, points),
|
||||||
|
job_id=rq_id,
|
||||||
|
timeout=15,
|
||||||
|
ttl=30)
|
||||||
|
|
||||||
|
return HttpResponse()
|
||||||
|
except Exception as ex:
|
||||||
|
slogger.job[jid].error("can't create a dextr request for the job {}".format(jid), exc_info=True)
|
||||||
|
return HttpResponseBadRequest(str(ex))
|
||||||
|
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["engine.job.change"],
|
||||||
|
fn=objectgetter(Job, "jid"), raise_exception=True)
|
||||||
|
def cancel(request, jid):
|
||||||
|
try:
|
||||||
|
username = request.user.username
|
||||||
|
slogger.job[jid].info("cancel dextr request for the JOB: {} ".format(jid)
|
||||||
|
+ "by the USER: {}".format(username))
|
||||||
|
|
||||||
|
queue = django_rq.get_queue(__RQ_QUEUE_NAME)
|
||||||
|
rq_id = "dextr.create/{}/{}".format(jid, username)
|
||||||
|
job = queue.fetch_job(rq_id)
|
||||||
|
|
||||||
|
if job is None or job.is_finished or job.is_failed:
|
||||||
|
raise Exception("Segmentation isn't running now")
|
||||||
|
elif "cancel" not in job.meta:
|
||||||
|
job.meta["cancel"] = True
|
||||||
|
job.save_meta()
|
||||||
|
|
||||||
|
return HttpResponse()
|
||||||
|
except Exception as ex:
|
||||||
|
slogger.job[jid].error("can't cancel a dextr request for the job {}".format(jid), exc_info=True)
|
||||||
|
return HttpResponseBadRequest(str(ex))
|
||||||
|
|
||||||
|
|
||||||
|
@login_required
|
||||||
|
@permission_required(perm=["engine.job.change"],
|
||||||
|
fn=objectgetter(Job, "jid"), raise_exception=True)
|
||||||
|
def check(request, jid):
|
||||||
|
try:
|
||||||
|
username = request.user.username
|
||||||
|
slogger.job[jid].info("check dextr request for the JOB: {} ".format(jid)
|
||||||
|
+ "by the USER: {}".format(username))
|
||||||
|
|
||||||
|
queue = django_rq.get_queue(__RQ_QUEUE_NAME)
|
||||||
|
rq_id = "dextr.create/{}/{}".format(jid, username)
|
||||||
|
job = queue.fetch_job(rq_id)
|
||||||
|
data = {}
|
||||||
|
|
||||||
|
if job is None:
|
||||||
|
data["status"] = "unknown"
|
||||||
|
else:
|
||||||
|
if "cancel" in job.meta:
|
||||||
|
data["status"] = "finished"
|
||||||
|
elif job.is_queued:
|
||||||
|
data["status"] = "queued"
|
||||||
|
elif job.is_started:
|
||||||
|
data["status"] = "started"
|
||||||
|
elif job.is_finished:
|
||||||
|
data["status"] = "finished"
|
||||||
|
data["result"] = job.meta["result"]
|
||||||
|
job.delete()
|
||||||
|
else:
|
||||||
|
data["status"] = "failed"
|
||||||
|
data["stderr"] = job.exc_info
|
||||||
|
job.delete()
|
||||||
|
|
||||||
|
return JsonResponse(data)
|
||||||
|
except Exception as ex:
|
||||||
|
slogger.job[jid].error("can't check a dextr request for the job {}".format(jid), exc_info=True)
|
||||||
|
return HttpResponseBadRequest(str(ex))
|
||||||
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|
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|
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|
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Before Width: | Height: | Size: 64 KiB After Width: | Height: | Size: 39 KiB |
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Before Width: | Height: | Size: 94 KiB After Width: | Height: | Size: 84 KiB |
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Before Width: | Height: | Size: 7.1 KiB After Width: | Height: | Size: 29 KiB |
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Before Width: | Height: | Size: 28 KiB After Width: | Height: | Size: 27 KiB |
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Before Width: | Height: | Size: 55 KiB After Width: | Height: | Size: 36 KiB |
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Before Width: | Height: | Size: 93 KiB After Width: | Height: | Size: 91 KiB |
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Before Width: | Height: | Size: 122 KiB After Width: | Height: | Size: 77 KiB |
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Before Width: | Height: | Size: 27 KiB After Width: | Height: | Size: 29 KiB |
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Before Width: | Height: | Size: 96 KiB After Width: | Height: | Size: 114 KiB |
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Before Width: | Height: | Size: 95 KiB After Width: | Height: | Size: 112 KiB |
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Before Width: | Height: | Size: 16 KiB After Width: | Height: | Size: 19 KiB |
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Before Width: | Height: | Size: 17 KiB After Width: | Height: | Size: 20 KiB |
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After Width: | Height: | Size: 9.2 KiB |
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After Width: | Height: | Size: 9.3 KiB |
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After Width: | Height: | Size: 9.2 KiB |
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After Width: | Height: | Size: 9.1 KiB |
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After Width: | Height: | Size: 12 KiB |
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After Width: | Height: | Size: 30 KiB |
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Reference in New Issue