def img_load(path, w, h, resize=True):
img = cv2_imread(path)
if len(img.shape) == 2:
img = np.dstack((img, img, img))
if resize:
img = cv2_resize(img, (w, h)).astype(np.uint8)
img = cvtColor(img, COLOR_BGR2RGB)
return img
def predict_eye_state(self, image):
"""Treatment of crop for model prediction"""
image = cv2_resize(image, (20, 10))
image = image.astype(dtype=np.float32)
image_batch = np.reshape(image, (1, 10, 20, 1))
image_batch = keras_preprocess_input(image_batch)
pred = np.argmax(self.model.predict(image_batch)[0])
return pred
def face_detection_with_face_recognition(self, rgb_frame):
"""I dont understand you can see the github in ciration in (blink models)"""
original_height, original_width = rgb_frame.shape[:2]
resized_image = cv2_resize(rgb_frame, (0, 0),
fx=self.scale,
fy=self.scale)
lab = cv2_cvtColor(resized_image, cv2_COLOR_BGR2LAB)
l, _, _ = cv2_split(lab)
resized_height, resized_width = l.shape[:2]
height_ratio, width_ratio = original_height / resized_height, original_width / resized_width
face_loc = face_locations(l, model='hog')
return face_loc, height_ratio, width_ratio
def crop(image, params):
height, width = image.shape[:2]
dst_height = int(height * params['central_fraction'])
dst_width = int(width * params['central_fraction'])
if height < dst_height or width < dst_width:
resized = np.array([width, height])
if width < dst_width:
resized *= dst_width / width
if height < dst_height:
resized *= dst_height / height
image = cv2_resize(image, tuple(np.ceil(resized).astype(int)))
top_left_y = (height - dst_height) // 2
top_left_x = (width - dst_width) // 2
return image[top_left_y:top_left_y + dst_height, top_left_x:top_left_x + dst_width]
def resize(image, params):
shape = params['height'], params['width']
return cv2_resize(image, shape)
def get_im_cv2_1024(path):
img = cv2_imread(path)
resized = cv2_resize(img, (1024, 1024), cv2_INTER_AREA)
return [path, resized]
def get_im_cv2_512(path):
img = cv2_imread(path)
resized = cv2_resize(img, (512, 512), cv2_INTER_AREA)
return [path, resized]
def get_im_cv2_256(path):
img = cv2_imread(path)
resized = cv2_resize(img, (256, 256), cv2_INTER_AREA)
return [path, resized]
def get_im_cv2_64(path):
img = cv2_imread(path)
resized = cv2_resize(img, (64, 64), cv2_INTER_AREA)
return [path, resized]
def get_im_cv2_32(path):
img = cv2_imread(path)
resized = cv2_resize(
img, (32, 32),
cv2_INTER_AREA) #use cv2_resize(img, (64, 64), cv2_INTER_AREA)
return [path, resized]