Issue Summary: File downloaded from cloud storage is not flushed. In case of lot of files, for some files, changes don't reflect in the actual physical file. Actual file is later accessed by filename, which leads to read error. Issue Error logs: ``` 2022-01-05 09:54:14,992 DEBG 'runserver' stderr output: [Wed Jan 05 09:54:14.992125 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] [2022-01-05 09:54:14,991] ERROR cvat.server.task_12: cannot get requested data type: chunk, number: 0, quality: Quality.COMPRESSED [Wed Jan 05 09:54:14.992147 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] Traceback (most recent call last): [Wed Jan 05 09:54:14.992152 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/cache.py", line 96, in prepare_chunk_buff [Wed Jan 05 09:54:14.992156 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] if checksum and not md5_hash(source_path) == checksum: [Wed Jan 05 09:54:14.992159 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/utils.py", line 100, in md5_hash [Wed Jan 05 09:54:14.992163 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] frame = Image.open(frame, 'r') [Wed Jan 05 09:54:14.992166 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/opt/venv/lib/python3.8/site-packages/PIL/Image.py", line 3023, in open [Wed Jan 05 09:54:14.992186 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] raise UnidentifiedImageError( [Wed Jan 05 09:54:14.992189 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] PIL.UnidentifiedImageError: cannot identify image file '/tmp/cvat_041w7vsimages#0089c635-ae5f-49d7-baa5-a4d75f0412ca.png' [Wed Jan 05 09:54:14.992192 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] [Wed Jan 05 09:54:14.992196 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] During handling of the above exception, another exception occurred: [Wed Jan 05 09:54:14.992199 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] 2022-01-05 09:54:14,992 DEBG 'runserver' stderr output: [Wed Jan 05 09:54:14.992202 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] Traceback (most recent call last): [Wed Jan 05 09:54:14.992205 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/views.py", line 689, in data [Wed Jan 05 09:54:14.992208 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] buff, mime_type = frame_provider.get_chunk(data_id, data_quality) [Wed Jan 05 09:54:14.992211 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/frame_provider.py", line 167, in get_chunk [Wed Jan 05 09:54:14.992215 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] return self._loaders[quality].get_chunk_path(chunk_number, quality, self._db_data) [Wed Jan 05 09:54:14.992218 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/cache.py", line 32, in get_buff_mime [Wed Jan 05 09:54:14.992221 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] chunk, tag = self.prepare_chunk_buff(db_data, quality, chunk_number) [Wed Jan 05 09:54:14.992224 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] File "/home/django/cvat/apps/engine/cache.py", line 113, in prepare_chunk_buff [Wed Jan 05 09:54:14.992227 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] raise Exception(msg) [Wed Jan 05 09:54:14.992231 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] Exception: cannot identify image file '/tmp/cvat_041w7vsimages#0089c635-ae5f-49d7-baa5-a4d75f0412ca.png' [Wed Jan 05 09:54:14.992414 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] ERROR - 2022-01-05 09:54:14,991 - views - cannot get requested data type: chunk, number: 0, quality: Quality.COMPRESSED [Wed Jan 05 09:54:14.992425 2022] [wsgi:error] [pid 330:tid 139683931096832] [remote 172.20.0.2:56868] Traceback (most recent call last): ``` |
4 years ago | |
|---|---|---|
| .github | 4 years ago | |
| .vscode | 4 years ago | |
| components | 4 years ago | |
| cvat | 4 years ago | |
| cvat-canvas | 4 years ago | |
| cvat-canvas3d | 4 years ago | |
| cvat-core | 4 years ago | |
| cvat-data | 4 years ago | |
| cvat-ui | 4 years ago | |
| helm-chart | 4 years ago | |
| serverless | 4 years ago | |
| site | 4 years ago | |
| ssh | 5 years ago | |
| tests | 4 years ago | |
| utils | 4 years ago | |
| .bandit | 7 years ago | |
| .codacy.yml | 5 years ago | |
| .coveragerc | 5 years ago | |
| .dockerignore | 6 years ago | |
| .editorconfig | 6 years ago | |
| .eslintignore | 5 years ago | |
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| .remarkrc.js | 5 years ago | |
| .stylelintrc.json | 5 years ago | |
| CHANGELOG.md | 4 years ago | |
| Dockerfile | 4 years ago | |
| Dockerfile.ci | 4 years ago | |
| Dockerfile.ui | 4 years ago | |
| LICENSE | 5 years ago | |
| README.md | 4 years ago | |
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README.md
Computer Vision Annotation Tool (CVAT)
CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team. Try it online cvat.org.
Documentation
- Contributing
- Installation guide
- Manual
- Django REST API documentation
- Datumaro dataset framework
- Command line interface
- XML annotation format
- AWS Deployment Guide
- Frequently asked questions
- Questions
Screencasts
- Introduction
- Annotation mode
- Interpolation of bounding boxes
- Interpolation of polygons
- Tag annotation video
- Attribute mode
- Segmentation mode
- Tutorial for polygons
- Semi-automatic segmentation
Supported annotation formats
Format selection is possible after clicking on the Upload annotation and Dump annotation buttons. Datumaro dataset framework allows additional dataset transformations via its command line tool and Python library.
For more information about supported formats look at the documentation.
| Annotation format | Import | Export |
|---|---|---|
| CVAT for images | X | X |
| CVAT for a video | X | X |
| Datumaro | X | |
| PASCAL VOC | X | X |
| Segmentation masks from PASCAL VOC | X | X |
| YOLO | X | X |
| MS COCO Object Detection | X | X |
| TFrecord | X | X |
| MOT | X | X |
| LabelMe 3.0 | X | X |
| ImageNet | X | X |
| CamVid | X | X |
| WIDER Face | X | X |
| VGGFace2 | X | X |
| Market-1501 | X | X |
| ICDAR13/15 | X | X |
| Open Images V6 | X | X |
| Cityscapes | X | X |
| KITTI | X | X |
| LFW | X | X |
Deep learning serverless functions for automatic labeling
| Name | Type | Framework | CPU | GPU |
|---|---|---|---|---|
| Deep Extreme Cut | interactor | OpenVINO | X | |
| Faster RCNN | detector | OpenVINO | X | |
| Mask RCNN | detector | OpenVINO | X | |
| YOLO v3 | detector | OpenVINO | X | |
| Object reidentification | reid | OpenVINO | X | |
| Semantic segmentation for ADAS | detector | OpenVINO | X | |
| Text detection v4 | detector | OpenVINO | X | |
| SiamMask | tracker | PyTorch | X | X |
| f-BRS | interactor | PyTorch | X | |
| HRNet | interactor | PyTorch | X | |
| Inside-Outside Guidance | interactor | PyTorch | X | |
| Faster RCNN | detector | TensorFlow | X | X |
| Mask RCNN | detector | TensorFlow | X | X |
| RetinaNet | detector | PyTorch | X | X |
Online demo: cvat.org
This is an online demo with the latest version of the annotation tool. Try it online without local installation. Only own or assigned tasks are visible to users.
Disabled features:
Limitations:
- No more than 10 tasks per user
- Uploaded data is limited to 500Mb
Prebuilt Docker images
Prebuilt docker images for CVAT releases are available on Docker Hub:
LICENSE
Code released under the MIT License.
This software uses LGPL licensed libraries from the FFmpeg project. The exact steps on how FFmpeg was configured and compiled can be found in the Dockerfile.
FFmpeg is an open source framework licensed under LGPL and GPL. See https://www.ffmpeg.org/legal.html. You are solely responsible for determining if your use of FFmpeg requires any additional licenses. Intel is not responsible for obtaining any such licenses, nor liable for any licensing fees due in connection with your use of FFmpeg.
Partners
- Onepanel is an open source vision AI platform that fully integrates CVAT with scalable data processing and parallelized training pipelines.
- DataIsKey uses CVAT as their prime data labeling tool to offer annotation services for projects of any size.
- Human Protocol uses CVAT as a way of adding annotation service to the human protocol.
- Cogito Tech LLC, a Human-in-the-Loop Workforce Solutions Provider, used CVAT in annotation of about 5,000 images for a brand operating in the fashion segment.
- FiftyOne is an open-source dataset curation and model analysis tool for visualizing, exploring, and improving computer vision datasets and models that is tightly integrated with CVAT for annotation and label refinement.
Questions
CVAT usage related questions or unclear concepts can be posted in our Gitter chat for quick replies from contributors and other users.
However, if you have a feature request or a bug report that can reproduced, feel free to open an issue (with steps to reproduce the bug if it's a bug report) on GitHub* issues.
If you are not sure or just want to browse other users common questions, Gitter chat is the way to go.
Other ways to ask questions and get our support:
- #cvat tag on StackOverflow*
- Forum on Intel Developer Zone

