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PINTO0309 / openvino2tensorflow

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.
MIT License
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There was insufficient consideration of the case where the MatMul is immediately after the 4D input layer #121

Closed PINTO0309 closed 1 year ago

PINTO0309 commented 2 years ago

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

mo \
--framework onnx \
--input_model model.onnx \
--data_type FP32 \
--output_dir openvino/FP32 \
--model_name model

openvino2tensorflow \
--model_path openvino/FP32/model.xml \
--output_saved_model \
--output_pb \
--non_verbose \
--output_no_quant_float32_tflite

Description

Error occurs when MatMul is immediately after the 4D input layer. https://github.com/PINTO0309/openvino2tensorflow/pull/120#issuecomment-1224570231

Relevant Log Output

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

Source code for simple inference testing code

mo \
--framework onnx \
--input_model model.onnx \
--data_type FP32 \
--output_dir openvino/FP32 \
--model_name model

openvino2tensorflow \
--model_path openvino/FP32/model.xml \
--output_saved_model \
--output_pb \
--non_verbose \
--output_no_quant_float32_tflite