Comments (2)
Which evaluation are you referring to? Are you also aware that we use MPIIGaze+ (using ground-truth eye corner annotations for segmentation)? How do you yield your gaze directions?
Please gain a better understanding of the task before jumping to conclusions. This repository is not for reproducing the paper's results, but for providing a reference implementation of the neural network model.
I'm afraid I cannot provide the relevant code - no matter which. Please review the paper in detail for information on how the evaluation was done. Do take care in understanding how each different evaluation is done and what it demonstrates.
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thanks a lot
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Related Issues (20)
- Theta and Phi
- Train-data parameter in elg-demo file
- Video_out is not defined when using record_video for testing elg demo
- Running demo elg using CPU gives overlapping frame of original image and segmented eye image instead of segmented eye image in top-left corner
- Could you share code to test on different data sets?
- can_use_eye, can_use_eyelid and can_use_iris in elg_demo.py are False HOT 1
- Stuck with --from_video option HOT 3
- Could you please tell me where the pre-training weight should be placed in the Windows system?
- The project only has elg demo. how to run dpg demo
- RuntimeError: Error deserializing object of type int64 while deserializing a floating point number.
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- About train/test data in MPIIGaze.h5
- Collaboration offer to help progress
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- elgo_demo.py stucks after video is closed HOT 1
- python and tensorflow version
- [TUTORIAL] How to save ELG model to .onnx and further to TensorRT .engine HOT 1
- Long proc time when running elg_demo.py on CPU HOT 1
- Can not get pre-trained weights
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