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validate projected coordinates are in the boundaries
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@ -175,22 +175,30 @@ def rotate_facial_area(
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# Angle in radians
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# Angle in radians
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angle = angle * np.pi / 180
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angle = angle * np.pi / 180
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height, weight = size
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# Translate the facial area to the center of the image
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# Translate the facial area to the center of the image
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x = (facial_area[0] + facial_area[2]) / 2 - size[1] / 2
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x = (facial_area[0] + facial_area[2]) / 2 - weight / 2
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y = (facial_area[1] + facial_area[3]) / 2 - size[0] / 2
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y = (facial_area[1] + facial_area[3]) / 2 - height / 2
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# Rotate the facial area
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# Rotate the facial area
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x_new = x * np.cos(angle) + y * direction * np.sin(angle)
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x_new = x * np.cos(angle) + y * direction * np.sin(angle)
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y_new = -x * direction * np.sin(angle) + y * np.cos(angle)
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y_new = -x * direction * np.sin(angle) + y * np.cos(angle)
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# Translate the facial area back to the original position
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# Translate the facial area back to the original position
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x_new = x_new + size[1] / 2
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x_new = x_new + weight / 2
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y_new = y_new + size[0] / 2
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y_new = y_new + height / 2
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# Calculate the new facial area
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# Calculate projected coordinates after alignment
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x1 = x_new - (facial_area[2] - facial_area[0]) / 2
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x1 = x_new - (facial_area[2] - facial_area[0]) / 2
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y1 = y_new - (facial_area[3] - facial_area[1]) / 2
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y1 = y_new - (facial_area[3] - facial_area[1]) / 2
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x2 = x_new + (facial_area[2] - facial_area[0]) / 2
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x2 = x_new + (facial_area[2] - facial_area[0]) / 2
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y2 = y_new + (facial_area[3] - facial_area[1]) / 2
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y2 = y_new + (facial_area[3] - facial_area[1]) / 2
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return (int(x1), int(y1), int(x2), int(y2))
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# validate projected coordinates are in image's boundaries
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x1 = max(int(x1), 0)
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y1 = max(int(y1), 0)
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x2 = min(int(x2), weight)
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y2 = min(int(y2), height)
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return (x1, y1, x2, y2)
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