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synced 2026-07-04 19:07:50 +08:00
Moved more variables out of the loops and modified the docstring
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@@ -91,7 +91,7 @@ def hog_histograms(cnp.float64_t[:, :] gradient_columns,
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number_of_orientations : int
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Number of orientation bins.
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orientation_histogram : ndarray
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The histogram to fill.
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The histogram array which is modified in place.
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"""
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cdef cnp.float64_t[:, :] magnitude = np.hypot(gradient_columns,
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@@ -101,24 +101,25 @@ def hog_histograms(cnp.float64_t[:, :] gradient_columns,
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cdef int i, x, y, o, yi, xi, cy1, cy2, cx1, cx2
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cdef float orientation_start, orientation_end
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# compute orientations integral images
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x0 = cell_columns / 2
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y0 = cell_rows / 2
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cy2 = cell_rows * number_of_cells_rows
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cx2 = cell_columns * number_of_cells_columns
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# compute orientations integral images
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for i in range(number_of_orientations):
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# isolate orientations in this range
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orientation_start = 180. / number_of_orientations * (i + 1)
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orientation_end = 180. / number_of_orientations * i
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y = cell_rows / 2
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cy2 = cell_rows * number_of_cells_rows
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x = cell_columns / 2
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cx2 = cell_columns * number_of_cells_columns
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x = x0
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y = y0
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yi = 0
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xi = 0
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while y < cy2:
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xi = 0
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x = cell_columns / 2
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x = x0
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while x < cx2:
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orientation_histogram[yi, xi, i] = cell_hog(magnitude,
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