def format_image(image):
if len(image.shape) > 2 and image.shape[2] == 3:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
else:
image = cv2.imdecode(image, cv2.CV_LOAD_IMAGE_GRAYSCALE)
faces = cascade_classifier.detectMultiScale(
image,
scaleFactor = 1.3,
minNeighbors = 5
)
# None is we don't found an image
if not len(faces) > 0:
return None
max_area_face = faces[0]
for face in faces:
if face[2] * face[3] > max_area_face[2] * max_area_face[3]:
max_area_face = face
# Chop image to face
face = max_area_face
image = image[face[1]:(face[1] + face[2]), face[0]:(face[0] + face[3])]
# Resize image to network size
try:
image = cv2.resize(image, (SIZE_FACE, SIZE_FACE), interpolation = cv2.INTER_CUBIC) / 255.
except Exception:
print("[+] Problem during resize")
return None
# cv2.imshow("Lol", image)
# cv2.waitKey(0)
return image
# Load Model
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