faster hsv augmentation (#1110)
As per https://github.com/ultralytics/yolov3/issues/1096
This commit is contained in:
parent
15f1343dfc
commit
992d8af242
|
@ -514,9 +514,16 @@ def load_image(self, index):
|
||||||
|
|
||||||
|
|
||||||
def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5):
|
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
|
r = 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)
|
hue, sat, val = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV))
|
||||||
np.clip(img_hsv[:, :, 0], None, 179, out=img_hsv[:, :, 0]) # inplace hue clip (0 - 179 deg)
|
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
|
cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) # no return needed
|
||||||
|
|
||||||
# Histogram equalization
|
# Histogram equalization
|
||||||
|
|
Loading…
Reference in New Issue