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GazeML

Input

Input

Ailia input shape: (2, 36, 60, 1)
Range: [-1.0, 1.0]

Output

Output

Shape: (2, 36, 60, 18)
Range: [0, 1.0]

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 gazeml.py 

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 gazeml.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 gazeml.py --video VIDEO_PATH

Reference

A deep learning framework based on Tensorflow for the training of high performance gaze estimation

Framework

TensorFlow 1.13.1

Model Format

ONNX opset = 10

Netron

gazeml_elg_i60x36_n32.onnx.prototxt

gazeml_elg_i180x108_n64.onnx.prototxt