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faster hsv augmentation (#1110) 

As per https://github.com/ultralytics/yolov3/issues/1096
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Josh Veitch-Michaelis 2020-04-28 20:59:44 +01:00 committed by GitHub
parent 15f1343dfc
commit 992d8af242
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1 changed files with 10 additions and 3 deletions
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13
utils/datasets.py
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@ -514,9 +514,16 @@ def load_image(self, index):
def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5):
x = np.random.uniform(-1, 1, 3) * [hgain, sgain, vgain] + 1 # random gains
img_hsv = (cv2.cvtColor(img, cv2.COLOR_BGR2HSV) * x).clip(None, 255).astype(np.uint8)
np.clip(img_hsv[:, :, 0], None, 179, out=img_hsv[:, :, 0]) # inplace hue clip (0 - 179 deg)
r = np.random.uniform(-1, 1, 3) * [hgain, sgain, vgain] + 1 # random gains
hue, sat, val = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV))
dtype = img.dtype # uint8
x = np.arange(0, 256, dtype=np.int16)
lut_hue = ((x * r[0]) % 180).astype(dtype)
lut_sat = np.clip(x * r[1], 0, 255).astype(dtype)
lut_val = np.clip(x * r[2], 0, 255).astype(dtype)
img_hsv = cv2.merge((cv2.LUT(hue, lut_hue), cv2.LUT(sat, lut_sat), cv2.LUT(val, lut_val))).astype(dtype)
cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) # no return needed
# Histogram equalization