Re-Identification application (#299)
Boris Sekachev
7 years ago
committed by
Nikita Manovich
parent
b4e6f22f58
commit
e225c38092
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exports.settings = {bullet: '*', paddedTable: false}
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exports.plugins = [
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require('remark-preset-lint-recommended'),
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require('remark-preset-lint-consistent'),
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require('remark-validate-links'),
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[require("remark-lint-no-dead-urls"), { skipOffline: true }],
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[require("remark-lint-maximum-line-length"), 120],
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[require("remark-lint-maximum-heading-length"), 120],
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[require("remark-lint-list-item-indent"), "tab-size"],
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[require("remark-lint-list-item-spacing"), false],
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[require("remark-lint-strong-marker"), "*"],
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[require("remark-lint-emphasis-marker"), "_"],
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[require("remark-lint-unordered-list-marker-style"), "-"],
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[require("remark-lint-ordered-list-marker-style"), "."],
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]
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# Re-Identification Application
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## About the application
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The ReID application uses deep learning model to perform an automatic bbox merging between neighbor frames.
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You can use "Merge" and "Split" functionality to edit automatically generated annotation.
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## Installation
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This application will be installed automatically with the [OpenVINO](https://github.com/opencv/cvat/blob/develop/components/openvino/README.md) component.
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## Running
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For starting the ReID merge process:
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- Open an annotation job
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- Open the menu
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- Click the "Run ReID Merge" button
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- Click the "Submit" button. Also here you can experiment with values of model threshold or maximum distance.
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- Model threshold is maximum cosine distance between objects embeddings.
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- Maximum distance defines a maximum radius that an object can diverge between neightbor frames.
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- The process will be run. You can cancel it in the menu.
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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
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default_app_config = 'cvat.apps.reid.apps.ReidConfig'
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JS_3RDPARTY['engine'] = JS_3RDPARTY.get('engine', []) + ['reid/js/enginePlugin.js']
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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 ReidConfig(AppConfig):
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name = 'cvat.apps.reid'
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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 os
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import rq
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import cv2
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import math
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import numpy
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import fnmatch
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from openvino.inference_engine import IENetwork, IEPlugin
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from scipy.optimize import linear_sum_assignment
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from scipy.spatial.distance import euclidean, cosine
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from cvat.apps.engine.models import Job
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class ReID:
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__threshold = None
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__max_distance = None
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__frame_urls = None
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__frame_boxes = None
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__stop_frame = None
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__plugin = None
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__executable_network = None
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__input_blob_name = None
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__output_blob_name = None
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__input_height = None
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__input_width = None
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def __init__(self, jid, data):
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self.__threshold = data["threshold"]
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self.__max_distance = data["maxDistance"]
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self.__frame_urls = {}
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self.__frame_boxes = {}
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db_job = Job.objects.select_related('segment__task').get(pk = jid)
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db_segment = db_job.segment
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db_task = db_segment.task
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self.__stop_frame = db_segment.stop_frame
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for root, _, filenames in os.walk(db_task.get_data_dirname()):
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for filename in fnmatch.filter(filenames, '*.jpg'):
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frame = int(os.path.splitext(filename)[0])
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if frame >= db_segment.start_frame and frame <= db_segment.stop_frame:
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self.__frame_urls[frame] = os.path.join(root, filename)
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for frame in self.__frame_urls:
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self.__frame_boxes[frame] = [box for box in data["boxes"] if box["frame"] == frame]
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IE_PLUGINS_PATH = os.getenv('IE_PLUGINS_PATH', None)
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REID_MODEL_DIR = os.getenv('REID_MODEL_DIR', None)
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if not IE_PLUGINS_PATH:
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raise Exception("Environment variable 'IE_PLUGINS_PATH' isn't defined")
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if not REID_MODEL_DIR:
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raise Exception("Environment variable 'REID_MODEL_DIR' isn't defined")
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REID_XML = os.path.join(REID_MODEL_DIR, "reid.xml")
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REID_BIN = os.path.join(REID_MODEL_DIR, "reid.bin")
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self.__plugin = IEPlugin(device="CPU", plugin_dirs=[IE_PLUGINS_PATH])
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network = IENetwork.from_ir(model=REID_XML, weights=REID_BIN)
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self.__input_blob_name = next(iter(network.inputs))
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self.__output_blob_name = next(iter(network.outputs))
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self.__input_height, self.__input_width = network.inputs[self.__input_blob_name].shape[-2:]
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self.__executable_network = self.__plugin.load(network=network)
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del network
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def __del__(self):
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if self.__executable_network:
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del self.__executable_network
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self.__executable_network = None
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if self.__plugin:
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del self.__plugin
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self.__plugin = None
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def __boxes_are_compatible(self, cur_box, next_box):
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cur_c_x = (cur_box["xtl"] + cur_box["xbr"]) / 2
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cur_c_y = (cur_box["ytl"] + cur_box["ybr"]) / 2
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next_c_x = (next_box["xtl"] + next_box["xbr"]) / 2
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next_c_y = (next_box["ytl"] + next_box["ybr"]) / 2
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compatible_distance = euclidean([cur_c_x, cur_c_y], [next_c_x, next_c_y]) <= self.__max_distance
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compatible_label = cur_box["label_id"] == next_box["label_id"]
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return compatible_distance and compatible_label and "path_id" not in next_box
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def __compute_difference(self, image_1, image_2):
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image_1 = cv2.resize(image_1, (self.__input_width, self.__input_height)).transpose((2,0,1))
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image_2 = cv2.resize(image_2, (self.__input_width, self.__input_height)).transpose((2,0,1))
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input_1 = {
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self.__input_blob_name: image_1[numpy.newaxis, ...]
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}
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input_2 = {
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self.__input_blob_name: image_2[numpy.newaxis, ...]
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}
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embedding_1 = self.__executable_network.infer(inputs = input_1)[self.__output_blob_name]
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embedding_2 = self.__executable_network.infer(inputs = input_2)[self.__output_blob_name]
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embedding_1 = embedding_1.reshape(embedding_1.size)
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embedding_2 = embedding_2.reshape(embedding_2.size)
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return cosine(embedding_1, embedding_2)
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def __compute_difference_matrix(self, cur_boxes, next_boxes, cur_image, next_image):
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def _int(number, upper):
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return math.floor(numpy.clip(number, 0, upper - 1))
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default_mat_value = 1000.0
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matrix = numpy.full([len(cur_boxes), len(next_boxes)], default_mat_value, dtype=float)
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for row, cur_box in enumerate(cur_boxes):
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cur_width = cur_image.shape[1]
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cur_height = cur_image.shape[0]
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cur_xtl, cur_xbr, cur_ytl, cur_ybr = (
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_int(cur_box["xtl"], cur_width), _int(cur_box["xbr"], cur_width),
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_int(cur_box["ytl"], cur_height), _int(cur_box["ybr"], cur_height)
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)
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for col, next_box in enumerate(next_boxes):
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next_box = next_boxes[col]
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next_width = next_image.shape[1]
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next_height = next_image.shape[0]
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next_xtl, next_xbr, next_ytl, next_ybr = (
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_int(next_box["xtl"], next_width), _int(next_box["xbr"], next_width),
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_int(next_box["ytl"], next_height), _int(next_box["ybr"], next_height)
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)
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if not self.__boxes_are_compatible(cur_box, next_box):
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continue
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crop_1 = cur_image[cur_ytl:cur_ybr, cur_xtl:cur_xbr]
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crop_2 = next_image[next_ytl:next_ybr, next_xtl:next_xbr]
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matrix[row][col] = self.__compute_difference(crop_1, crop_2)
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return matrix
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def __apply_matching(self):
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frames = sorted(list(self.__frame_boxes.keys()))
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job = rq.get_current_job()
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box_paths = {}
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for idx, (cur_frame, next_frame) in enumerate(list(zip(frames[:-1], frames[1:]))):
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job.refresh()
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if "cancel" in job.meta:
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return None
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job.meta["progress"] = idx * 100.0 / len(frames)
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job.save_meta()
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cur_boxes = self.__frame_boxes[cur_frame]
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next_boxes = self.__frame_boxes[next_frame]
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for box in cur_boxes:
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if "path_id" not in box:
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path_id = len(box_paths)
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box_paths[path_id] = [box]
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box["path_id"] = path_id
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if not (len(cur_boxes) and len(next_boxes)):
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continue
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cur_image = cv2.imread(self.__frame_urls[cur_frame], cv2.IMREAD_COLOR)
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next_image = cv2.imread(self.__frame_urls[next_frame], cv2.IMREAD_COLOR)
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difference_matrix = self.__compute_difference_matrix(cur_boxes, next_boxes, cur_image, next_image)
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cur_idxs, next_idxs = linear_sum_assignment(difference_matrix)
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for idx, cur_idx in enumerate(cur_idxs):
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if (difference_matrix[cur_idx][next_idxs[idx]]) <= self.__threshold:
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cur_box = cur_boxes[cur_idx]
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next_box = next_boxes[next_idxs[idx]]
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next_box["path_id"] = cur_box["path_id"]
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box_paths[cur_box["path_id"]].append(next_box)
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for box in self.__frame_boxes[frames[-1]]:
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if "path_id" not in box:
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path_id = len(box_paths)
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box["path_id"] = path_id
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box_paths[path_id] = [box]
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return box_paths
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def run(self):
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box_paths = self.__apply_matching()
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output = []
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# ReID process has been canceled
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if box_paths is None:
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return
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for path_id in box_paths:
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output.append({
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"label_id": box_paths[path_id][0]["label_id"],
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"group_id": 0,
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"attributes": [],
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"frame": box_paths[path_id][0]["frame"],
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"shapes": box_paths[path_id]
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})
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for box in output[-1]["shapes"]:
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del box["id"]
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del box["path_id"]
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del box["group_id"]
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del box["label_id"]
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box["outside"] = False
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box["attributes"] = []
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for path in output:
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if path["shapes"][-1]["frame"] != self.__stop_frame:
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copy = path["shapes"][-1].copy()
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copy["outside"] = True
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copy["frame"] += 1
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path["shapes"].append(copy)
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return output
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@ -0,0 +1,170 @@
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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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/* global showMessage userConfirm */
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document.addEventListener('DOMContentLoaded', () => {
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function run(overlay, cancelButton, thresholdInput, distanceInput) {
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const collection = window.cvat.data.get();
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const data = {
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threshold: +thresholdInput.prop('value'),
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maxDistance: +distanceInput.prop('value'),
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boxes: collection.boxes,
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};
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overlay.removeClass('hidden');
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cancelButton.prop('disabled', true);
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$.ajax({
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url: `reid/start/job/${window.cvat.job.id}`,
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type: 'POST',
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data: JSON.stringify(data),
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contentType: 'application/json',
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success: () => {
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function checkCallback() {
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$.ajax({
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url: `/reid/check/${window.cvat.job.id}`,
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type: 'GET',
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success: (jobData) => {
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if (jobData.progress) {
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cancelButton.text(`Cancel ReID Merge (${jobData.progress.toString().slice(0, 4)}%)`);
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}
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if (['queued', 'started'].includes(jobData.status)) {
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setTimeout(checkCallback, 1000);
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} else {
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overlay.addClass('hidden');
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if (jobData.status === 'finished') {
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if (jobData.result) {
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collection.boxes = [];
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collection.box_paths = collection.box_paths
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.concat(JSON.parse(jobData.result));
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window.cvat.data.clear();
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window.cvat.data.set(collection);
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showMessage('ReID merge has done.');
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} else {
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showMessage('ReID merge been canceled.');
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}
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} else if (jobData.status === 'failed') {
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const message = `ReID merge has fallen. Error: '${jobData.stderr}'`;
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showMessage(message);
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} else {
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let message = `Check request returned "${jobData.status}" status.`;
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if (jobData.stderr) {
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message += ` Error: ${jobData.stderr}`;
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}
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showMessage(message);
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}
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}
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},
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error: (errorData) => {
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overlay.addClass('hidden');
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const message = `Can not check ReID merge. Code: ${errorData.status}. Message: ${errorData.responseText || errorData.statusText}`;
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showMessage(message);
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},
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});
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}
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setTimeout(checkCallback, 1000);
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},
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error: (errorData) => {
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overlay.addClass('hidden');
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const message = `Can not start ReID merge. Code: ${errorData.status}. Message: ${errorData.responseText || errorData.statusText}`;
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showMessage(message);
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},
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complete: () => {
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cancelButton.prop('disabled', false);
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},
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});
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}
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function cancel(overlay, cancelButton) {
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cancelButton.prop('disabled', true);
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$.ajax({
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url: `/reid/cancel/${window.cvat.job.id}`,
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type: 'GET',
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success: () => {
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overlay.addClass('hidden');
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cancelButton.text('Cancel ReID Merge (0%)');
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},
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error: (errorData) => {
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const message = `Can not cancel ReID process. Code: ${errorData.status}. Message: ${errorData.responseText || errorData.statusText}`;
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showMessage(message);
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},
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complete: () => {
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cancelButton.prop('disabled', false);
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}
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});
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}
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const buttonsUI = $('#engineMenuButtons');
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const reidWindowId = 'reidSubmitWindow';
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const reidThresholdValueId = 'reidThresholdValue';
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const reidDistanceValueId = 'reidDistanceValue';
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const reidCancelMergeId = 'reidCancelMerge';
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const reidSubmitMergeId = 'reidSubmitMerge';
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const reidCancelButtonId = 'reidCancelReID';
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const reidOverlay = 'reidOverlay';
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$('<button> Run ReID Merge </button>').on('click', () => {
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$('#annotationMenu').addClass('hidden');
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$(`#${reidWindowId}`).removeClass('hidden');
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}).addClass('menuButton semiBold h2').prependTo(buttonsUI);
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$(`
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<div class="modal hidden" id="${reidWindowId}">
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<div class="modal-content" style="width: 300px; height: 170px;">
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<table>
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<tr>
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<td> <label class="regular h2"> Threshold: </label> </td>
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<td> <input id="${reidThresholdValueId}" class="regular h1" type="number"` +
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`title="Maximum cosine distance between embeddings of objects" min="0.05" max="0.95" value="0.5" step="0.05"> </td>
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</tr>
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<tr>
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<td> <label class="regular h2"> Max Pixel Distance </label> </td>
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<td> <input id="${reidDistanceValueId}" class="regular h1" type="number"` +
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`title="Maximum radius that an object can diverge between neighbor frames" min="10" max="1000" value="50" step="10"> </td>
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</tr>
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<tr>
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<td colspan="2"> <label class="regular h2" style="color: red;"> All boxes will be translated to box paths. Continue? </label> </td>
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</tr>
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</table>
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<center style="margin-top: 10px;">
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<button id="${reidCancelMergeId}" class="regular h2"> Cancel </button>
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<button id="${reidSubmitMergeId}" class="regular h2"> Merge </button>
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</center>
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</div>
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</div>
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`).appendTo('body');
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$(`
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<div class="modal hidden force-modal" id="${reidOverlay}">
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<div class="modal-content" style="width: 300px; height: 70px;">
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<center> <label class="regular h2"> ReID is processing the data </label></center>
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<center style="margin-top: 5px;">
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<button id="${reidCancelButtonId}" class="regular h2" style="width: 250px;"> Cancel ReID Merge (0%) </button>
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</center>
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</div>
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</div>
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`).appendTo('body');
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$(`#${reidCancelMergeId}`).on('click', () => {
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$(`#${reidWindowId}`).addClass('hidden');
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});
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$(`#${reidCancelButtonId}`).on('click', () => {
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userConfirm('ReID process will be canceld. Are you sure?', () => {
|
||||
cancel($(`#${reidOverlay}`), $(`#${reidCancelButtonId}`));
|
||||
});
|
||||
});
|
||||
|
||||
$(`#${reidSubmitMergeId}`).on('click', () => {
|
||||
$(`#${reidWindowId}`).addClass('hidden');
|
||||
run($(`#${reidOverlay}`), $(`#${reidCancelButtonId}`),
|
||||
$(`#${reidThresholdValueId}`), $(`#${reidDistanceValueId}`));
|
||||
});
|
||||
});
|
||||
@ -0,0 +1,12 @@
|
||||
# Copyright (C) 2018 Intel Corporation
|
||||
#
|
||||
# SPDX-License-Identifier: MIT
|
||||
|
||||
from django.urls import path
|
||||
from . import views
|
||||
|
||||
urlpatterns = [
|
||||
path('start/job/<int:jid>', views.start),
|
||||
path('cancel/<int:jid>', views.cancel),
|
||||
path('check/<int:jid>', views.check),
|
||||
]
|
||||
@ -0,0 +1,96 @@
|
||||
# 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.reid.reid import ReID
|
||||
|
||||
import django_rq
|
||||
import json
|
||||
import rq
|
||||
|
||||
|
||||
def _create_thread(jid, data):
|
||||
job = rq.get_current_job()
|
||||
reid_obj = ReID(jid, data)
|
||||
job.meta["result"] = json.dumps(reid_obj.run())
|
||||
job.save_meta()
|
||||
|
||||
|
||||
@login_required
|
||||
@permission_required(perm=["engine.job.change"],
|
||||
fn=objectgetter(Job, 'jid'), raise_exception=True)
|
||||
def start(request, jid):
|
||||
try:
|
||||
data = json.loads(request.body.decode('utf-8'))
|
||||
queue = django_rq.get_queue("low")
|
||||
job_id = "reid.create.{}".format(jid)
|
||||
job = queue.fetch_job(job_id)
|
||||
if job is not None and (job.is_started or job.is_queued):
|
||||
raise Exception('ReID process has been already started')
|
||||
queue.enqueue_call(func=_create_thread, args=(jid, data), job_id=job_id, timeout=7200)
|
||||
job = queue.fetch_job(job_id)
|
||||
job.meta = {}
|
||||
job.save_meta()
|
||||
except Exception as e:
|
||||
return HttpResponseBadRequest(str(e))
|
||||
|
||||
return HttpResponse()
|
||||
|
||||
|
||||
@login_required
|
||||
@permission_required(perm=["engine.job.change"],
|
||||
fn=objectgetter(Job, 'jid'), raise_exception=True)
|
||||
def check(request, jid):
|
||||
try:
|
||||
queue = django_rq.get_queue("low")
|
||||
rq_id = "reid.create.{}".format(jid)
|
||||
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"
|
||||
if "progress" in job.meta:
|
||||
data["progress"] = job.meta["progress"]
|
||||
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()
|
||||
|
||||
except Exception as ex:
|
||||
data["stderr"] = str(ex)
|
||||
data["status"] = "unknown"
|
||||
|
||||
return JsonResponse(data)
|
||||
|
||||
|
||||
@login_required
|
||||
@permission_required(perm=["engine.job.change"],
|
||||
fn=objectgetter(Job, 'jid'), raise_exception=True)
|
||||
def cancel(request, jid):
|
||||
try:
|
||||
queue = django_rq.get_queue("low")
|
||||
rq_id = "reid.create.{}".format(jid)
|
||||
job = queue.fetch_job(rq_id)
|
||||
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_meta()
|
||||
except Exception as e:
|
||||
return HttpResponseBadRequest(str(e))
|
||||
|
||||
return HttpResponse()
|
||||
Loading…
Reference in New Issue