This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.
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C3D model conversion - Depth of input (112) is not a multiple of input depth of filter (3) for '{{node tf.nn.conv3d/Conv3D}} #129
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Issue Type
Bug
OS
Ubuntu
OS architecture
x86_64
Programming Language
Python
Framework
TFLite
Download URL for ONNX / OpenVINO IR
https://pastebin.com/t0BqsAfG
Convert Script
openvino2tensorflow --model_path openvino/c3d-sim.xml --model_output_path ./openvino2tensorflow --output_saved_model --output_no_quant_float32_tflite
Description
Model C3D ( https://t.co/PeRc2UZI6x) was converted from Pytorch to ONNX, then to OpenVino, and finally to TFLite, but there is an error regarding dimensions. I followed this guide https://siliconlabs.github.io/mltk/mltk/tutorials/onnx_to_tflite.html with the C3D model, and the error was found in this specific section https://siliconlabs.github.io/mltk/mltk/tutorials/onnx_to_tflite.html#convert-from-openvino-to-tf-lite-float32.
Relevant Log Output
Source code for simple inference testing code
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