CV-Studio is a graphical annotation tool to address different Computer Vision tasks.
CV-Studio is developed in Python, Qt, SQLite and uses PyTorch's resources to train deep learning models.
CVStudio supports:
Datasets:
- Create and manage your datasets for images.
- Manually annotate images:
- Using a label system for classification problems.
- Using a bounding box for localization and object detection problems.
- Using a polygon tool or freehand selection for segmentation tasks.
- Auto-annotate images with a pretrained model to continue tagging the images by your own.
- Datasets: Annotations for videos.
- Platforms: macOS support.
Note: CV-Studio only have been developed and tested on Windows, and linux. Future platforms are in the roadmap.
pip install cvstudio
- Using GPU:
pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cu101/torch_nightly.html
- Using CPU:
pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
This command must be executed from the CVStudio folder: Windows (PowerShell)
Invoke-WebRequest -OutFile ./models/MS_DeepLab_resnet_trained_VOC.pth https://data.vision.ee.ethz.ch/csergi/share/DEXTR/MS_DeepLab_resnet_trained_VOC.pth
Invoke-WebRequest -OutFile ./models/dextr_pascal-sbd.pth https://data.vision.ee.ethz.ch/csergi/share/DEXTR/dextr_pascal-sbd.pth
Linux
wget https://data.vision.ee.ethz.ch/csergi/share/DEXTR/MS_DeepLab_resnet_trained_VOC.pth -P ./models
wget https://data.vision.ee.ethz.ch/csergi/share/DEXTR/dextr_pascal-sbd.pth -P ./models
cvstudio
Check out the wiki.
Send a pull request.
Citation: haruiz. CV-Studio. Git code (2019). https://github.com/haruiz/CvStudio
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