def illum(img):
img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
_, thresh = cv2.threshold(img_gray, 180, 255, 0)
cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
"""
# opencv 3.4:
ret:
img, contours, hierarchy
# opencv 4.0
ret:
contours, hierarchy
"""
img_zero = np.zeros(img.shape, dtype=np.uint8)
for cnt in cnts:
x, y, w, h = cv2.boundingRect(cnt)
# x，y是矩阵左上点的坐标，w，h是矩阵的宽和高
img_zero[y:y + h, x:x + w] = 255
mask = img_zero
result = cv2.illuminationChange(img, mask, alpha=1, beta=2)
for i in [img, mask, result]:
cv2.imshow("", i)
cv2.waitKey()
return result
def force_poisson_blending(source, target, coords):
xmin = int(coords[0])
ymin = int(coords[1])
xmax = int(coords[2])
ymax = int(coords[3])
img2 = target[ymin:ymax, xmin:xmax]
img1 = cv2.resize(source, (img2.shape[1], img2.shape[0]))
flatten_mask = np.zeros(target.shape, dtype=target.dtype)
flatten_mask[ymin:ymax, xmin:xmax] = 255
mask = 255 * np.ones(img1.shape, img1.dtype)
center = (int((xmin + xmax) / 2), int((ymin + ymax) / 2))
textureflatten = cv2.illuminationChange(target,
flatten_mask,
alpha=2,
beta=2)
# cv2.imshow("textureflatten", textureflatten)
# cv2.waitKey(0)
# cv2.destroyWindow("textureflatten")
normal_clone = cv2.seamlessClone(img1, textureflatten, mask, center,
cv2.NORMAL_CLONE)
# cv2.imshow("normal_clone", normal_clone)
# cv2.waitKey(0)
# cv2.destroyWindow("normal_clone")
mixed_clone = cv2.seamlessClone(img1, textureflatten, mask, center,
cv2.MIXED_CLONE)
# cv2.imshow("mixed_clone", mixed_clone)
# cv2.waitKey(0)
# cv2.destroyWindow("mixed_clone")
return normal_clone, mixed_clone
def sift_posson_blending(source, target, coords):
xmin = int(coords[0])
ymin = int(coords[1])
xmax = int(coords[2])
ymax = int(coords[3])
img2 = target[ymin:ymax, xmin:xmax]
img1 = cv2.resize(source, (img2.shape[1], img2.shape[0]))
source_kp_image, source_kp, source_des = sift_kp(img1)
target_kp_image, target_kp, target_des = sift_kp(img2)
matches = get_match(source_des, target_des)
print("find %d matches\n" % len(matches))
if len(matches) >= 0:
ptsS = np.float32([source_kp[j.queryIdx].pt
for j in matches]).reshape(-1, 1, 2)
ptsT = np.float32([target_kp[j.trainIdx].pt
for j in matches]).reshape(-1, 1, 2)
H, status = cv2.findHomography(ptsT, ptsS, cv2.RANSAC,
ransacReprojThreshold)
imgOut = cv2.warpPerspective(img1,
H, (img2.shape[1], img2.shape[0]),
flags=cv2.INTER_LINEAR +
cv2.WARP_INVERSE_MAP)
cv2.imshow("result", imgOut)
cv2.waitKey(0)
cv2.destroyWindow("result")
flatten_mask = np.zeros(target.shape, dtype=target.dtype)
flatten_mask[ymin:ymax, xmin:xmax] = 255
mask = 255 * np.ones(imgOut.shape, imgOut.dtype)
center = (int((xmin + xmax) / 2), int((ymin + ymax) / 2))
textureflatten = cv2.illuminationChange(target,
flatten_mask,
alpha=2,
beta=2)
cv2.imshow("textureflatten", textureflatten)
cv2.waitKey(0)
cv2.destroyWindow("textureflatten")
normal_clone = cv2.seamlessClone(imgOut, textureflatten, mask, center,
cv2.NORMAL_CLONE)
cv2.imshow("normal_clone", normal_clone)
cv2.waitKey(0)
cv2.destroyWindow("normal_clone")
mixed_clone = cv2.seamlessClone(imgOut, target, mask, center,
cv2.MIXED_CLONE)
cv2.imshow("mixed_clone", mixed_clone)
cv2.waitKey(0)
# cv2.destroyWindow("mixed_clone")
return normal_clone, mixed_clone
def illum(img):
# img = cv2.imread("test2.jpg")
# img = img[532:768, 0:512]
img_bw = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(img_bw, 180, 255, 0)[1]
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[1]
img_zero = np.zeros(img.shape, dtype=np.uint8)
# img[thresh == 255] = 150
for cnt in cnts:
x, y, w, h = cv2.boundingRect(cnt)
img_zero[y:y + h, x:x + w] = 255
# cv2.imshow("mask", mask)
mask = img_zero
# cv2.imshow("mask", mask)
result = cv2.illuminationChange(img, mask, alpha=1, beta=2)
# cv2.imshow("result", result)
# cv2.waitKey(0)
return result
img_reverse = img_reverse[padding[1]:img_reverse.shape[0] - padding[3],
padding[0]:img_reverse.shape[1] -
padding[2], ::-1]
print('reverse shape:', img_reverse.shape, img_reverse.min(),
img_reverse.max())
img_trans = np.zeros_like(img, img.dtype)
img_trans[y0:y1, x0:x1, :] = img_reverse
img_mix = img * ~mask[..., np.newaxis] + img_trans * mask[...,
np.newaxis]
mask_neigh = dilation(forehead_line(mask, kpt), square(
(x1 - x0) // 15))
print('mask neigh shape:', mask_neigh.shape)
#cv2.imwrite('tmp_forehead.jpg', mask_neigh.astype(np.uint8)*255)
img_mix_smooth = (gaussian(img_mix, sigma=0.6, multichannel=False) *
255).astype(img_mix.dtype)
#cv2.imwrite('tmp_smooth.jpg', img_mix_smooth)
img_mix = img_mix_smooth * mask_neigh[..., np.newaxis] + img_mix * (
~mask_neigh)[..., np.newaxis]
#cv2.imwrite('tmp_forehead.jpg', mask_neigh)
cv2.imwrite(
os.path.join(opt.results_dir,
file.rsplit('/', 1)[-1].replace('_ori', '')),
cv2.illuminationChange(img_mix,
mask_neigh.astype(img_mix.dtype) * 255))
shutil.copy(
file,
os.path.join(opt.results_dir,
file.rsplit('/', 1)[-1].replace('.jpg', '_ori.jpg')))
if (colmax > gray.shape[1]):
colmax = gray.shape[1]
imageROI = gray[rowmin:rowmax, colmin:colmax]
temaver = np.mean(imageROI)
blockImage[r, c] = temaver
blockImage = blockImage - average
blockImage2 = cv2.resize(blockImage, (gray.shape[1], gray.shape[0]),
interpolation=cv2.INTER_CUBIC)
gray2 = gray.astype(np.float32)
dst = gray2 - blockImage2
dst = dst.astype(np.uint8)
dst = cv2.GaussianBlur(dst, (3, 3), 0)
dst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
return dst
if __name__ == '__main__':
file = 'test6.jpg'
blockSize = 16
img = cv2.imread(file)
dst = unevenLightCompensate(img, blockSize)
# result = np.concatenate([img, dst], axis=1)
cv2.imshow('result', dst)
cv2.waitKey(0)
cv2.illuminationChange()
def poissonEdit(self, btnNor, btnMix, cheFFla, sliL, sliH, cheIllu, slia,
slib, cheFCo, cheGr):
if self.sourceMode:
if self.dst_img is None or self.src_img is None:
return
src, mask, _x, _y = self.getEditSrc()
if btnNor.isChecked():
cloneMode = cv2.NORMAL_CLONE
elif btnMix.isChecked():
cloneMode = cv2.MIXED_CLONE
else:
cloneMode = cv2.MONOCHROME_TRANSFER
try:
self.result_img = cv2.seamlessClone(src, self.dst_img, mask,
(_x, _y), cloneMode)
except Exception as e:
print(e)
print(roi_u, roi_d, roi_l, roi_r)
print(src_u, src_d, src_l, src_r)
return
self.display_res()
return
if self.src_img is None:
return
res = self.src_img.copy()
if cheFCo.isChecked():
r = self.setColor.red()
g = self.setColor.green()
b = self.setColor.blue()
if r + g + b != 765:
_b, _g, _r = cv2.split(
cv2.bitwise_and(
res, cv2.merge((self.mask, self.mask, self.mask))))
num = np.sum(self.mask / 255)
mulr, mulg, mulb = r * num / np.sum(_r), g * num / np.sum(
_g), b * num / np.sum(_b)
mulr, mulg, mulb = mulr**0.5, mulg**0.5, mulb**0.5
if mulr < 0.5:
mulr = 0.5
if mulr > 2.5:
mulr = 2.5
if mulg < 0.5:
mulg = 0.5
if mulg > 2.5:
mulg = 2.5
if mulb < 0.5:
mulb = 0.5
if mulb > 2.5:
mulb = 2.5
print(mulr, mulg, mulb)
res = cv2.colorChange(res, self.mask, mulr, mulg, mulb)
if cheGr.isChecked():
dst = cv2.cvtColor(
cv2.cvtColor(self.src_img, cv2.COLOR_BGR2GRAY),
cv2.COLOR_GRAY2BGR)
src, mask, _x, _y = self.getEditSrc(res, False)
res = cv2.seamlessClone(src, dst, mask, (_x, _y),
cv2.NORMAL_CLONE)
if cheFFla.isChecked():
res = cv2.textureFlattening(res, self.mask, res, sliL.value(),
sliH.value())
if cheIllu.isChecked():
res = cv2.illuminationChange(res, self.mask, res,
(slia.value() + 1) / 50,
(slib.value() + 1) / 100)
self.result_img = res
self.display_res()