Python scripts form performing stereo depth estimation using the HITNET model in Tensorflow Lite.

Overview

TFLite-HITNET-Stereo-depth-estimation

Python scripts form performing stereo depth estimation using the HITNET model in Tensorflow Lite.

Hitnet stereo depth estimation TFLite Stereo depth estimation on the cones images from the Middlebury dataset (https://vision.middlebury.edu/stereo/data/scenes2003/)

Requirements

  • OpenCV, imread-from-url and tensorflow==2.6.0 or tflite_runtime. Also, pafy and youtube-dl are required for youtube video inference.

Installation

pip install -r requirements.txt
pip install pafy youtube-dl

For the tflite runtime, you can either use tensorflow(make sure it is version 2.6.0 or above) pip install tensorflow==2.6.0 or the TensorFlow Runtime binary

Known issues

In computers with a GPU, the program would silently creash without any error during the inference, os.environ["CUDA_VISIBLE_DEVICES"]="-1" is added at the beginning of the script to force the program to run on the CPU. You can comment this line for other types of devices.

tflite model

The original models were converted to different formats (including .tflite) 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.

ONNX inference

For performing the inference in ONNX, check my other repository ONNX HITNET Stereo Depth estimation.

Inference video Example Raspberry Pi 4

Hitnet stereo depth estimation on video Raspberry Pi 4

References:

Owner
Ibai Gorordo
Passionate about sensors, technology and their potential to help people.
Ibai Gorordo
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