README.md

CV-Studio

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.

Watch a demo video

Roadmap

• Datasets: Annotations for videos.
• Platforms: macOS support.

Installation

Note: CV-Studio only have been developed and tested on Windows, and linux. Future platforms are in the roadmap.

1. Install cvstudio

pip install cvstudio

2. Install pytorch

• 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        

3. Download pre-trained models

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

4. Run CVStudio

    cvstudio

Documentation

Check out the wiki.

How to contribute

Send a pull request.

License

Free software: MIT license

Citation: haruiz. CV-Studio. Git code (2019). https://github.com/haruiz/CvStudio

Credits

Images and Icons

• Icons made by Dave Gandy from www.flaticon.com
• Icons made by Pixelmeetup from www.flaticon.com
• Icons made by Smashicons from www.flaticon.com
• Icons made by Eucalyp from www.flaticon.com
• Icons made by Becris from www.flaticon.com
• Icons made by Smashicons from www.flaticon.com
• Icons made by Freepik from www.flaticon.com
• Icons made by Those Icons from www.flaticon.com

Models

Deep Extreme Cut: From Extreme Points to Object Segmentation