Published September 25, 2022
| Version 1.5.44
Software
Open
Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC)
Authors/Creators
Description
Pad- Implement padding process with dynamic tensor
- https://tfhub.dev/tensorflow/lite-model/efficientdet/lite2/detection/default/1?lite-format=tflite
- https://github.com/PINTO0309/onnx2tf/releases/download/1.1.28/efficientdet_lite2_detection_1.onnx
- https://discuss.tensorflow.org/t/convert-efficientdet-lite-2-to-mlmodel/14542
https://tfhub.dev/tensorflow/lite-model/efficientdet/lite2/detection/default/1?lite-format=tflite
python3 -m tf2onnx.convert \
--opset 12 \
--tflite lite-model_efficientdet_lite2_detection_default_1.tflite \
--output efficientdet_lite2_detection_1.onnx \
--dequantize \
--inputs-as-nchw serving_default_images:0
onnxsim efficientdet_lite2_detection_1.onnx efficientdet_lite2_detection_1.onnx
onnxsim efficientdet_lite2_detection_1.onnx efficientdet_lite2_detection_1.onnx
onnxsim efficientdet_lite2_detection_1.onnx efficientdet_lite2_detection_1.onnx
onnx2tf -i efficientdet_lite2_detection_1.onnx -osd
- [EfficientDet-lite2] Implement padding process with dynamic tensor by @PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/171
Full Changelog: https://github.com/PINTO0309/onnx2tf/compare/1.5.43...1.5.44
Notes
If you use onnx2tf in your research, please cite it using these metadata.
Files
PINTO0309/onnx2tf-1.5.44.zip
Files
(454.8 kB)
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Additional details
Related works
- Is supplement to
- https://github.com/PINTO0309/onnx2tf/tree/1.5.44 (URL)