def load_feature(img_path):
img = util.cv_imread(img_path)
crop = img / 255.
crop = crop - 0.5
crop = crop * 2.
crop = cv2.resize(crop, (config.INPUT_SIZE, config.INPUT_SIZE))
return crop
def load_feature(img_path):
img = util.cv_imread(img_path)
crop = img / 255.
crop = crop - 0.5
crop = crop * 2.
crop = cv2.resize(crop, (250, 250))
return crop
def load_feature(img_path):
img = util.cv_imread(img_path)
img= relight(img,random.uniform(0.9, 1.1), random.randint(-10, 10))
crop= img / 255.
crop = crop - 0.5
crop = crop * 2.
crop = cv2.resize(crop, (229, 229))
return crop
def load_feature(img_path):
img = util.cv_imread(img_path)
crop = random_crop(img, 224)
flip = np.random.randint(0, 3)
if flip == 1:
flipimg = cv2.flip(crop, 1)
if flip == 0:
flipimg = cv2.flip(crop, 0)
if flip == 2:
flipimg = crop
return flipimg
def load_feature(img_path):
img = util.cv_imread(img_path)
img = relight(img, random.uniform(0.9, 1.1), random.randint(-10, 10))
crop = img / 255.
r1 = random.uniform(0.9, 1.1)
r2 = random.randint(0, 45)
crop = rotate(crop, angle=r2, scale=r1)
flip = np.random.randint(0, 3)
if flip == 1:
flipimg = cv2.flip(crop, 1)
if flip == 0:
flipimg = cv2.flip(crop, 0)
if flip == 2:
flipimg = crop
crop = cv2.resize(flipimg, (224, 224))
return crop
def load_feature(img_path):
img = util.cv_imread(img_path)
norm_img = img / 255.
resized_img = util.resize_img(norm_img, size)
crop = cv2.resize(resized_img, (size, size))
return crop
def load_feature(img_path):
img = util.cv_imread(img_path)
norm_img = img / 255.
resized_img = util.resize_img(norm_img, config.INPUT_SIZE)
crop = cv2.resize(resized_img, (config.INPUT_SIZE, config.INPUT_SIZE))
return crop