Add KITTI format (#3757)
Kirill Sizov
4 years ago
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GitHub
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# Copyright (C) 2021 Intel Corporation
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#
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# SPDX-License-Identifier: MIT
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import os.path as osp
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from tempfile import TemporaryDirectory
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from datumaro.components.dataset import Dataset
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from datumaro.plugins.kitti_format.format import KittiPath, write_label_map
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from pyunpack import Archive
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from cvat.apps.dataset_manager.bindings import (GetCVATDataExtractor,
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ProjectData, import_dm_annotations)
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from cvat.apps.dataset_manager.util import make_zip_archive
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from .registry import dm_env, exporter, importer
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from .utils import make_colormap
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@exporter(name='KITTI', ext='ZIP', version='1.0')
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def _export(dst_file, instance_data, save_images=False):
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dataset = Dataset.from_extractors(GetCVATDataExtractor(instance_data,
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include_images=save_images), env=dm_env)
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with TemporaryDirectory() as tmp_dir:
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dataset.transform('polygons_to_masks')
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dataset.transform('merge_instance_segments')
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dataset.export(tmp_dir, format='kitti',
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label_map={k: v[0] for k, v in make_colormap(instance_data).items()},
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apply_colormap=True, save_images=save_images
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)
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make_zip_archive(tmp_dir, dst_file)
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@importer(name='KITTI', ext='ZIP', version='1.0')
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def _import(src_file, instance_data):
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with TemporaryDirectory() as tmp_dir:
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Archive(src_file.name).extractall(tmp_dir)
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color_map = {k: v[0] for k, v in make_colormap(instance_data).items()}
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color_map_path = osp.join(tmp_dir, KittiPath.LABELMAP_FILE)
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if not osp.isfile(color_map_path):
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write_label_map(color_map_path, color_map)
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dataset = Dataset.import_from(tmp_dir, format='kitti', env=dm_env)
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labels_meta = instance_data.meta['project']['labels'] \
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if isinstance(instance_data, ProjectData) else instance_data.meta['task']['labels']
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if 'background' not in [label['name'] for _, label in labels_meta]:
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dataset.filter('/item/annotation[label != "background"]',
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filter_annotations=True)
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dataset.transform('masks_to_polygons')
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import_dm_annotations(dataset, instance_data)
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---
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linkTitle: 'KITTI'
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weight: 17
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---
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# [KITTI](http://www.cvlibs.net/datasets/kitti/)
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- [Format specification for KITTI detection](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_object.zip)
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- [Format specification for KITTI segmentation](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_semantics.zip)
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- supported annotations:
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- Rectangles (detection task)
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- Polygon (segmentation task)
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- supported attributes:
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- `occluded` (both UI option and a separate attribute).
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Indicates that a significant portion of the object within
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the bounding box is occluded by another object
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- `truncated` supported only for rectangles
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(should be defined for labels as `checkbox` -es).
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Indicates that the bounding box specified for the object
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does not correspond to the full extent of the object
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- 'is_crowd' supported only for polygons
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(should be defined for labels as `checkbox` -es).
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Indicates that the annotation covers multiple instances of the same class
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## KITTI annotations export
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Downloaded file: a zip archive of the following structure:
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```
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└─ annotations.zip/
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├── label_colors.txt # list of pairs r g b label_name
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├── labels.txt # list of labels
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└── default/
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├── label_2/ # left color camera label files
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│ ├── <image_name_1>.txt
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│ ├── <image_name_2>.txt
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│ └── ...
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├── instance/ # instance segmentation masks
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│ ├── <image_name_1>.png
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│ ├── <image_name_2>.png
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│ └── ...
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├── semantic/ # semantic segmentation masks (labels are encoded by its id)
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│ ├── <image_name_1>.png
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│ ├── <image_name_2>.png
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│ └── ...
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└── semantic_rgb/ # semantic segmentation masks (labels are encoded by its color)
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├── <image_name_1>.png
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├── <image_name_2>.png
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└── ...
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```
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## KITTI annotations import
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You can upload KITTI annotations in two ways:
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rectangles for the detection task and
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masks for the segmentation task.
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For detection tasks the uploading archive should have the following structure:
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```
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└─ annotations.zip/
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├── labels.txt # optional, labels list for non-original detection labels
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└── <subset_name>/
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├── label_2/ # left color camera label files
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│ ├── <image_name_1>.txt
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│ ├── <image_name_2>.txt
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│ └── ...
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```
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For segmentation tasks the uploading archive should have the following structure:
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```
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└─ annotations.zip/
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├── label_colors.txt # optional, color map for non-original segmentation labels
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└── <subset_name>/
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├── instance/ # instance segmentation masks
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│ ├── <image_name_1>.png
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│ ├── <image_name_2>.png
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│ └── ...
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├── semantic/ # optional, semantic segmentation masks (labels are encoded by its id)
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│ ├── <image_name_1>.png
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│ ├── <image_name_2>.png
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│ └── ...
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└── semantic_rgb/ # optional, semantic segmentation masks (labels are encoded by its color)
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├── <image_name_1>.png
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├── <image_name_2>.png
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└── ...
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```
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All annotation files and masks should have structures
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that are described in the original format specification.
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