ONNX-HITNET-Stereo-Depth-estimation
Python scripts form performing stereo depth estimation using the HITNET model in ONNX.
Stereo depth estimation on the cones images from the Middlebury dataset (https://vision.middlebury.edu/stereo/data/scenes2003/)
Requirements
- OpenCV, imread-from-url, onnx and onnxruntime. Also, pafy and youtube-dl are required for youtube video inference.
Installation
pip install -r requirements.txt
pip install pafy youtube-dl
ONNX model
The original models were converted to different formats (including .onnx) by PINTO0309, download the models from his repository and save them into the models folder.
Original Tensorflow model
The Tensorflow pretrained model was taken from the original repository.
Examples
- Image inference:
python imageDepthEstimation.py
- Video inference:
python videoDepthEstimation.py
- DrivingStereo dataset inference:
python drivingStereoTest.py
Pytorch inference
For performing the inference in Tensorflow, check my other repository HITNET Stereo Depth estimation.
TFLite inference
For performing the inference in TFLite, check my other repository TFLite HITNET Stereo Depth estimation.
Inference video Example
References:
- Hitnet model: https://github.com/google-research/google-research/tree/master/hitnet
- PINTO0309's model zoo: https://github.com/PINTO0309/PINTO_model_zoo
- PINTO0309's model conversion tool: https://github.com/PINTO0309/openvino2tensorflow
- DrivingStereo dataset: https://drivingstereo-dataset.github.io/
- Original paper: https://arxiv.org/abs/2007.12140
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