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27cdf70086
This patch implements the DNNAsyncExecModule for the LibTorch backend, enabling non-blocking inference using the common infrastructure instead of custom threading (th_async_module_submit) to align with the TensorFlow and OpenVINO backends. The implementation uses ff_dnn_start_inference_async which provides unified async logic across all DNN backends, eliminating the need for backend-specific threading code. Verified with: ffmpeg -f lavfi -i testsrc=duration=5:size=320x240:rate=30 -vf dnn_processing=dnn_backend=torch:model=model.pt -y output.mp4 Signed-off-by: Raja Rathour <imraja729@gmail.com> |
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| .. | ||
| dnn_backend_common.c | ||
| dnn_backend_common.h | ||
| dnn_backend_openvino.c | ||
| dnn_backend_tf.c | ||
| dnn_backend_torch.cpp | ||
| dnn_interface.c | ||
| dnn_io_proc.c | ||
| dnn_io_proc.h | ||
| Makefile | ||
| queue.c | ||
| queue.h | ||
| safe_queue.c | ||
| safe_queue.h | ||