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feat: properly tune tracking algo AHSF
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@ -1008,16 +1008,16 @@ def External_Run_AHSF(frame_gray):
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wmax = (frame_gray.shape[1] * 0.5) # likes to crash, might need more tuning still
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wmax = (frame_gray.shape[1] * 0.5) # likes to crash, might need more tuning still
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wmin = (frame_gray.shape[1] * 0.1)
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wmin = (frame_gray.shape[1] * 0.1)
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params = {
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params = {
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"ratio_downsample": 0.3,
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"ratio_downsample": 0.5,
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"use_init_rect": False,
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"use_init_rect": False,
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"mu_outer": 220, # aprroximatly how much pupil should be in the outer rect
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"mu_outer": 200, # aprroximatly how much pupil should be in the outer rect
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"mu_inner": 40, # aprroximatly how much pupil should be in the inner rect
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"mu_inner": 50, # aprroximatly how much pupil should be in the inner rect
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"ratio_outer": 1.0, # rectangular ratio. 1 means square (LIKE REGULAR HSF)
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"ratio_outer": 1.0, # rectangular ratio. 1 means square (LIKE REGULAR HSF)
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"kf": 2, # noise filter. May lose tracking if too high (or even never start)
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"kf": 2, # noise filter. May lose tracking if too high (or even never start)
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"width_min": wmin, # Minimum width of the pupil
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"width_min": wmin, # Minimum width of the pupil
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"width_max": wmax, # Maximum width of the pupil
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"width_max": wmax, # Maximum width of the pupil
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"wh_step": 5, # Pupil width and height step search size
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"wh_step": 5, # Pupil width and height step search size
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"xy_step": 5, # Kernel movement step search size
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"xy_step": 10, # Kernel movement step search size
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"roi": (0, 0, frame_gray.shape[1], frame_gray.shape[0]),
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"roi": (0, 0, frame_gray.shape[1], frame_gray.shape[0]),
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"init_rect_flag": False,
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"init_rect_flag": False,
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"init_rect": (0, 0, frame_gray.shape[1], frame_gray.shape[0]),
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"init_rect": (0, 0, frame_gray.shape[1], frame_gray.shape[0]),
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