Closed wadhwasahil closed 2 years ago
Please refer to the official sample by NVIDIA: https://github.com/NVIDIA/TensorRT/tree/main/samples/python/tensorflow_object_detection_api
So the thing is I have used tf.train.write_graph(dynamic_graph.as_graph_def(), ".","test.pb", as_text=False)
to get a .pb file. However I am unable to load the .pb file. Is this a correct way?
I recommend to use export_inference_graph.py to export your custom trained model to pb. The resulting pb file would be named as "frozen_inference_graph.pb".
Actually I am using the frozen graph before running your code here - https://github.com/jkjung-avt/tensorrt_demos/blob/a061e44a82e1ca097f57e5a32f20daf5bebe7ade/ssd/build_engine.py I am having some issues with using UFF method because I want Explicit batch and UFF doesn't support that. Hence I am trying to see if I can generate an ONNX representation intermediately
I am using your code to convert my trained SSD MobileNet V2 model to Tensor RT format. You have used UFF format - https://github.com/jkjung-avt/tensorrt_demos/blob/a061e44a82e1ca097f57e5a32f20daf5bebe7ade/ssd/build_engine.py#L282
However I want to use Onnx instead of UFF. Once the graph is generated how can I convert it to ONNX instead of UFF?
Thanks