for i,img_name in enumerate(img_names,1):
try:
img = Image.open(os.path.join(img_path,img_name))
img = transform_img(img)
img = np.array(img)
img = img[...,::-1]
if BOUNDING:
mosaic_area = 0
while mosaic_area < 16384:
mask = Image.open(os.path.join(ir_mask_path,random.choices(mask_names)[0]))
mask = transform_mask(mask)
mask = np.array(mask)
mosaic_area = impro.mask_area(mask)
mosaic_img = mosaic.addmosaic_random(img, mask,'bounding')
BOUNDING_flag = '_bound'
else:
mask = Image.open(os.path.join(ir_mask_path,random.choices(mask_names)[0]))
mask = transform_mask(mask)
mask = np.array(mask)
mosaic_img = mosaic.addmosaic_random(img, mask)
BOUNDING_flag = ''
if HD:#[128:384,128:384,:] --->256
cv2.imwrite(os.path.join(train_A_path,'%05d' % i+BOUNDING_flag+'.jpg'), mosaic_img)
cv2.imwrite(os.path.join(train_B_path,'%05d' % i+BOUNDING_flag+'.jpg'), img)
else:
merge_img = impro.makedataset(mosaic_img, img)
cv2.imwrite(os.path.join(train_path,'%05d' % i+BOUNDING_flag+'.jpg'), merge_img)
if MASK:
cnt = 0
for fold in range(FOLD_NUM):
for img_name, mask_name in zip(img_names, mask_names):
try:
img = impro.imread(os.path.join(img_dir, img_name))
mask = impro.imread(os.path.join(mask_dir, mask_name), 'gray')
mask = impro.resize_like(mask, img)
x, y, size, area = impro.boundingSquare(mask, 1.5)
if area > 100:
if Bounding:
img = impro.resize(
img[y - size:y + size, x - size:x + size], OUT_SIZE)
mask = impro.resize(
mask[y - size:y + size, x - size:x + size], OUT_SIZE)
img_mosaic = mosaic.addmosaic_random(img, mask)
if HD:
cv2.imwrite(
os.path.join(train_A_path, '%05d' % cnt + '.jpg'),
img_mosaic)
cv2.imwrite(
os.path.join(train_B_path, '%05d' % cnt + '.jpg'), img)
else:
merge_img = impro.makedataset(img_mosaic, img)
cv2.imwrite(
os.path.join(train_path, '%05d' % cnt + '.jpg'),
merge_img)
if MASK:
cv2.imwrite(os.path.join(mask_path, '%05d' % cnt + '.png'),
mask)
img_names = os.listdir(img_path)
print('Find images:', len(img_names))
for i, img_name in enumerate(img_names, 1):
try:
img = Image.open(os.path.join(img_path, img_name))
img = transform_img(img)
img = np.array(img)
img = img[..., ::-1]
mask = Image.open(
os.path.join(ir_mask_path,
random.choices(mask_names)[0]))
mask = transform_mask(mask)
mask = np.array(mask)
mosaic_img = mosaic.addmosaic_random(img, mask)
if HD:
cv2.imwrite(os.path.join(train_A_path, '%05d' % i + '.jpg'),
mosaic_img)
cv2.imwrite(os.path.join(train_B_path, '%05d' % i + '.jpg'), img)
else:
merge_img = impro.makedataset(mosaic_img, img)
cv2.imwrite(os.path.join(train_path, '%05d' % i + '.jpg'),
merge_img)
if MASK:
cv2.imwrite(os.path.join(mask_path, '%05d' % i + '.png'), mask)
print("Processing:", img_name, " ", "Remain:", len(img_names) - i)
except Exception as e:
print(img_name, e)