PyTorchCV provides a collection of computer vision models (classification, segmentation, detection, etc.) for PyTorch, with pretrained weights. Current version 0.0.74, release cadence is irregular. Requires Python >=3.10.
pip install pytorchcvVerified import paths — ran on the pinned version, not inferred.
Quickstart: load a pretrained ResNet-18 model and run inference on a random tensor.
Use lowercase names; check available models via pytorchcv.model_provider.get_model_list().
Replace direct class imports with get_model('model_name').Set environment variable PYTORCHCV_CACHE_DIR to customize cache location; consider pre-downloading weights.
Run: pip install pytorchcv
Check list of models: from pytorchcv.model_provider import get_model_list; print(get_model_list())
Ensure internet connection or set pretrained=False to load architecture without weights.
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