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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There was insufficient consideration of the case where the MatMul is immediately after the 4D input layer #121
ValueError: Dimensions must be equal, but are 3 and 28 for '{{node tf.linalg.matmul/MatMul}} = BatchMatMulV2[T=DT_FLOAT, adj_x=false, adj_y=true](Placeholder, tf.linalg.matmul/MatMul/b)' with input shapes: [1,28,28,3], [10,28].
ERROR: Please refer to 6-7 in the README first. https://github.com/PINTO0309/openvino2tensorflow
Issue Type
Bug
OS
Ubuntu
OS architecture
x86_64
Programming Language
Python
Framework
OpenVINO, PyTorch, ONNX, TensorFlow, TensorFlowLite
Download URL for ONNX / OpenVINO IR
https://github.com/PINTO0309/openvino2tensorflow/files/9409671/model.zip
Convert Script
Description
Error occurs when
MatMul
is immediately after the 4D input layer. https://github.com/PINTO0309/openvino2tensorflow/pull/120#issuecomment-1224570231Relevant Log Output
Source code for simple inference testing code