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Python project that constructs a surface normal colormap of a subject in a scene (both with and without knowing lighting direction a priori) through photometric stereo techniques.

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curesh/photometric-stereo

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photometric-stereo

Two important parameters for the circle detecting algorithm are:

dp parameter in cv2.HoughCircles: This adjusts the granuality of the circle finding algorithm. It should be somewhere between 1 and 4 (usually closer to one is better).

threshold parameter in cv2.threshold: This adjusts the threshold for bright patches. Values range from 0 to 255 but a good value is around 240.

For vani's data set, the best dp is 1.4 and the best threshold is 240.

To run with the harvard dataset switch branch from master to dataset.

For my data set, ideal dp value is 1.4

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Python project that constructs a surface normal colormap of a subject in a scene (both with and without knowing lighting direction a priori) through photometric stereo techniques.

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