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1from libreyolo import LibreYOLO
2
3model = LibreYOLO("LibreCenterNetdla34.pt")
4results = model.predict("image.jpg")4c50fd3a46bdf63dbf2082c5cbb3458d39579e6c.
Copyright (c) 2019 Xingyi Zhou. The source implementation is MIT licensed.43bf4cc2efe00e02c1ae8484035b062a35543872d276c7dcfeb4db3e64203e4fmodule. prefix was removed and LibreYOLO v1 checkpoint
metadata was added. Learned tensors are unchanged. The native graph strictly
loads the official state dict and its hm, wh, and reg outputs are
bit-exact against the pinned implementation. LibreYOLO replaces the legacy
DCNv2 extension with torchvision deformable convolution.weights/convert_centernet_weights.py and
docs/provenance/centernet.md in the
LibreYOLO source repository.