diff --git a/README.md b/README.md index f9fbcc55..c62e0414 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,8 @@ ![CVAT logo](site/content/en/images/cvat_poster_with_name.png) # Computer Vision Annotation Tool (CVAT) +CVAT – Computer Vision Annotation Tool - The open data annotation platform for AI | Product Hunt + [![CI][ci-img]][ci-url] [![Gitter chat][gitter-img]][gitter-url] [![Coverage Status][coverage-img]][coverage-url] @@ -33,7 +35,7 @@ Start using CVAT online for free: [cvat.ai](https://cvat.ai). Or set it up as a - [XML annotation format](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/) - [AWS Deployment Guide](https://cvat-ai.github.io/cvat/docs/administration/basics/aws-deployment-guide/) - [Frequently asked questions](https://cvat-ai.github.io/cvat/docs/faq/) -- [Questions](#questions) +- [Where to ask questions](#where-to-ask-questions) ## Partners ❤️ @@ -41,13 +43,13 @@ CVAT is used by teams all over the world. If you use us, please drop us a line a [contact@cvat.ai](mailto:contact+github@cvat.ai) - and we'll add you to this list. - [ATLANTIS](https://github.com/smhassanerfani/atlantis) is an open-source dataset for semantic segmentation - of waterbody images, depevoped by [iWERS](http://ce.sc.edu/iwers/) group in the + of waterbody images, depeloped by [iWERS](http://ce.sc.edu/iwers/) group in the Department of Civil and Environmental Engineering at University of South Carolina, is using CVAT. For developing a semantic segmentation dataset using CVAT, please check [ATLANTIS published article](https://www.sciencedirect.com/science/article/pii/S1364815222000391), [ATLANTIS Development Kit](https://github.com/smhassanerfani/atlantis/tree/master/adk) and [annotation tutorial videos](https://www.youtube.com/playlist?list=PLIfLGY-zZChS5trt7Lc3MfNhab7OWl2BR). -- [Onepanel](https://github.com/onepanelio/core) is an open source +- [Onepanel](https://github.com/onepanelio/core) is an open-source vision AI platform that fully integrates CVAT with scalable data processing and parallelized training pipelines. - [DataIsKey](https://dataiskey.eu/annotation-tool/) uses CVAT as their prime data labeling tool @@ -84,8 +86,8 @@ The images have been downloaded more than 1M times so far. ## REST API -CVAT has a REST API. Its current version is `2.0-alpha`. We focus on its -improvement and therefore REST API may be changed in the next release. +CVAT has a REST API: [documentation](https://cvat-ai.github.io/cvat/docs/administration/basics/rest_api_guide/). +Its current version is `2.0-alpha`. We focus on its improvement, and the API may be changed in the next releases. ## Screencasts 🎦 @@ -115,26 +117,26 @@ For more information about supported formats, look at the | Annotation format | Import | Export | | --------------------------------------------------------------------------------------------------------- | ------ | ------ | -| [CVAT for images](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | X | X | -| [CVAT for a video](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | X | X | -| [Datumaro](https://github.com/cvat-ai/datumaro) | | X | -| [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | X | X | -| Segmentation masks from [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | X | X | -| [YOLO](https://pjreddie.com/darknet/yolo/) | X | X | -| [MS COCO Object Detection](http://cocodataset.org/#format-data) | X | X | -| [TFrecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) | X | X | -| [MOT](https://motchallenge.net/) | X | X | -| [LabelMe 3.0](http://labelme.csail.mit.edu/Release3.0) | X | X | -| [ImageNet](http://www.image-net.org) | X | X | -| [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) | X | X | -| [WIDER Face](http://shuoyang1213.me/WIDERFACE/) | X | X | -| [VGGFace2](https://github.com/ox-vgg/vgg_face2) | X | X | -| [Market-1501](https://www.aitribune.com/dataset/2018051063) | X | X | -| [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) | X | X | -| [Open Images V6](https://storage.googleapis.com/openimages/web/index.html) | X | X | -| [Cityscapes](https://www.cityscapes-dataset.com/login/) | X | X | -| [KITTI](http://www.cvlibs.net/datasets/kitti/) | X | X | -| [LFW](http://vis-www.cs.umass.edu/lfw/) | X | X | +| [CVAT for images](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | ✔️ | ✔️ | +| [CVAT for a video](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | ✔️ | ✔️ | +| [Datumaro](https://github.com/cvat-ai/datumaro) | | ✔️ | +| [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ | +| Segmentation masks from [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ | +| [YOLO](https://pjreddie.com/darknet/yolo/) | ✔️ | ✔️ | +| [MS COCO Object Detection](http://cocodataset.org/#format-data) | ✔️ | ✔️ | +| [TFrecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) | ✔️ | ✔️ | +| [MOT](https://motchallenge.net/) | ✔️ | ✔️ | +| [LabelMe 3.0](http://labelme.csail.mit.edu/Release3.0) | ✔️ | ✔️ | +| [ImageNet](http://www.image-net.org) | ✔️ | ✔️ | +| [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) | ✔️ | ✔️ | +| [WIDER Face](http://shuoyang1213.me/WIDERFACE/) | ✔️ | ✔️ | +| [VGGFace2](https://github.com/ox-vgg/vgg_face2) | ✔️ | ✔️ | +| [Market-1501](https://www.aitribune.com/dataset/2018051063) | ✔️ | ✔️ | +| [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) | ✔️ | ✔️ | +| [Open Images V6](https://storage.googleapis.com/openimages/web/index.html) | ✔️ | ✔️ | +| [Cityscapes](https://www.cityscapes-dataset.com/login/) | ✔️ | ✔️ | +| [KITTI](http://www.cvlibs.net/datasets/kitti/) | ✔️ | ✔️ | +| [LFW](http://vis-www.cs.umass.edu/lfw/) | ✔️ | ✔️ | @@ -148,22 +150,22 @@ can be ran on: | Name | Type | Framework | CPU | GPU | | ------------------------------------------------------------------------------------------------------- | ---------- | ---------- | --- | --- | -| [Deep Extreme Cut](/serverless/openvino/dextr/nuclio) | interactor | OpenVINO | X | | -| [Faster RCNN](/serverless/openvino/omz/public/faster_rcnn_inception_v2_coco/nuclio) | detector | OpenVINO | X | | -| [Mask RCNN](/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio) | detector | OpenVINO | X | | -| [YOLO v3](/serverless/openvino/omz/public/yolo-v3-tf/nuclio) | detector | OpenVINO | X | | -| [Object reidentification](/serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio) | reid | OpenVINO | X | | -| [Semantic segmentation for ADAS](/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | detector | OpenVINO | X | | -| [Text detection v4](/serverless/openvino/omz/intel/text-detection-0004/nuclio) | detector | OpenVINO | X | | -| [YOLO v5](/serverless/pytorch/ultralytics/yolov5/nuclio) | detector | PyTorch | X | | -| [SiamMask](/serverless/pytorch/foolwood/siammask/nuclio) | tracker | PyTorch | X | X | -| [f-BRS](/serverless/pytorch/saic-vul/fbrs/nuclio) | interactor | PyTorch | X | | -| [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio) | interactor | PyTorch | | X | -| [Inside-Outside Guidance](/serverless/pytorch/shiyinzhang/iog/nuclio) | interactor | PyTorch | X | | -| [Faster RCNN](/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | detector | TensorFlow | X | X | -| [Mask RCNN](/serverless/tensorflow/matterport/mask_rcnn/nuclio) | detector | TensorFlow | X | X | -| [RetinaNet](serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio) | detector | PyTorch | X | X | -| [Face Detection](/serverless/openvino/omz/intel/face-detection-0205/nuclio) | detector | OpenVINO | X | | +| [Deep Extreme Cut](/serverless/openvino/dextr/nuclio) | interactor | OpenVINO | ✔️ | | +| [Faster RCNN](/serverless/openvino/omz/public/faster_rcnn_inception_v2_coco/nuclio) | detector | OpenVINO | ✔️ | | +| [Mask RCNN](/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio) | detector | OpenVINO | ✔️ | | +| [YOLO v3](/serverless/openvino/omz/public/yolo-v3-tf/nuclio) | detector | OpenVINO | ✔️ | | +| [Object reidentification](/serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio) | reid | OpenVINO | ✔️ | | +| [Semantic segmentation for ADAS](/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | detector | OpenVINO | ✔️ | | +| [Text detection v4](/serverless/openvino/omz/intel/text-detection-0004/nuclio) | detector | OpenVINO | ✔️ | | +| [YOLO v5](/serverless/pytorch/ultralytics/yolov5/nuclio) | detector | PyTorch | ✔️ | | +| [SiamMask](/serverless/pytorch/foolwood/siammask/nuclio) | tracker | PyTorch | ✔️ | ✔️ | +| [f-BRS](/serverless/pytorch/saic-vul/fbrs/nuclio) | interactor | PyTorch | ✔️ | | +| [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio) | interactor | PyTorch | | ✔️ | +| [Inside-Outside Guidance](/serverless/pytorch/shiyinzhang/iog/nuclio) | interactor | PyTorch | ✔️ | | +| [Faster RCNN](/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | detector | TensorFlow | ✔️ | ✔️ | +| [Mask RCNN](/serverless/tensorflow/matterport/mask_rcnn/nuclio) | detector | TensorFlow | ✔️ | ✔️ | +| [RetinaNet](serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio) | detector | PyTorch | ✔️ | ✔️ | +| [Face Detection](/serverless/openvino/omz/intel/face-detection-0205/nuclio) | detector | OpenVINO | ✔️ | | @@ -177,26 +179,23 @@ The exact steps on how FFmpeg was configured and compiled can be found in the [D FFmpeg is an open source framework licensed under LGPL and GPL. See [https://www.ffmpeg.org/legal.html](https://www.ffmpeg.org/legal.html). You are solely responsible for determining if your use of FFmpeg requires any -additional licenses. CVAT.ai is not responsible for obtaining any +additional licenses. CVAT.ai Corporation is not responsible for obtaining any such licenses, nor liable for any licensing fees due in connection with your use of FFmpeg. -## Questions - -CVAT usage related questions or unclear concepts can be posted in our -[Gitter chat](https://gitter.im/opencv-cvat) for **quick replies** from -contributors and other users. +## Where to ask questions -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](https://github.com/cvat-ai/cvat/issues). +[Gitter chat](https://gitter.im/opencv-cvat): you can post CVAT usage related there. +Typically they get answered fast by the core team or community. You can also browse other users +common questions on our gitter. -If you are not sure or just want to browse other users common questions, -[Gitter chat](https://gitter.im/opencv-cvat) is the way to go. +[GitHub issues](https://github.com/cvat-ai/cvat/issues): please post your have feature requests or bug reports there. +If it's a bug, please add the steps to reproduce it. -Other ways to ask questions and get our support: +[\#cvat](https://stackoverflow.com/search?q=%23cvat) tag on StackOverflow is one more way to ask +questions and get our support. -- [\#cvat](https://stackoverflow.com/search?q=%23cvat) tag on StackOverflow\* +[contact@cvat.ai](mailto:contact+github@cvat.ai): reach out to us with feedback, comments, or inquiries. ## Links