Tapir Pytorch Inference

https://github.com/user-attachments/assets/457eeb57-9961-4022-9b15-55f1d9dc2260

Important

This is a strip down version of the original Tapir repository focused on inference.

• Removed the JAX dependencies and the training code.
• Make it easy to run in real-time even with a camera feed.
• Converted tensors from 5D to 4D (only use one frame)
• ⚠️⚠️⚠️ONNX Inference is very slow⚠️⚠️⚠️

Installation

git clone https://github.com/ibaiGorordo/Tapir-Pytorch-Inference.git
cd Tapir-Pytorch-Inference
pip install -r requirements.txt

• Download model from: https://storage.googleapis.com/dm-tapnet/causal_bootstapir_checkpoint.pt

License

The License of the original model is Apache 2.0: License

ONNX Export

⚠️⚠️⚠️ONNX Inference is very slow⚠️⚠️⚠️

python onnx_export.py

Arguments:

• --model: Path to the model weights
• --resolution: Input resolution (default: 640)
• --num_points: Number of points (default: 1000)
• --dynamic: Export with dynamic number of points (default: False)
• --num_iters: Number of iterations, use 0 for faster inference, 4 for better results (default: 4)
• --output_dir: Output directory (default: ./)

Examples

Video inference:

 python example_video_tracking.py

Webcam inference:

 python example_webcam_tracking.py

References:

• TAPIR Repository: https://github.com/google-deepmind/tapnet/tree/main