Notes

@app.route('/api/liveness_detector', methods = ['POST'])
def liveness_detector():
global image_path
global temp_path

fd_model_path = "/home/plnt_admin/app/intel/face-detection-0200/FP32/face-detection-0200.xml"
fd_threshold = 0.6
device = 'CPU'
face_detector = FaceDetector(fd_model_path,fd_threshold, device, None)

spf_model_path = "/home/plnt_admin/app/spf_models/MN3_antispoof.xml"
spoof_model = VectorCNN(spf_model_path)

# vidcap = cv2.VideoCapture('/home/sharjeel/Documents/light-weight-face-anti-spoofing/test.mp4')
brightness_threshold = 100
spoof_threshold = 0.95
real_threshold = 0.2
spoof_flag = False
# real_flag = False

since_last_spoof_counter = 0
spoof_flag_counter = 0
off_center_counter = 0
spoof_counter = 0
real_counter = 0

spoof_counter_threshold = 10
real_counter_threshold = 0.7
last_spoof_threshold = 1
spoof_flag_threshold = 50
off_center_threshold = 10

if request.method == "POST":
response = {'message' : 'Inconclusive, Try Again',
'real_flag' : False,
'spoof_flag': spoof_flag,
'liveness_score': 0,
'off_center_counter': off_center_counter,
'spoof_flag_counter': spoof_flag_counter,
'since_last_spoof_counter': since_last_spoof_counter,
'spoof_counter': spoof_counter}

frame_count = request.form['frame_count']
running_flag = True

for i in range(0,int(frame_count)):
if running_flag:
frame_key="frame"+str(i)
base64_s = request.form[str(frame_key)]
base64_s=base64_s.split(',')
base64_s=base64_s[1]
now = datetime.now()
now.strftime("%d%m%Y%H%M%S%.3f")
cur_date=now.strftime("%d%m%Y%H%M%S%.3f")
filename=image_path+'live_'+cur_date+'_'+str(i)+'.png'
# filename1=image_path+cur_date+'.jpg'

img = Image.open(io.BytesIO(base64.decodebytes(bytes(base64_s, "utf-8"))))
img.save(filename)

img = cv2.imread(filename)
img_rotate_90_clockwise = cv2.rotate(img, cv2.ROTATE_90_COUNTERCLOCKWISE)
cv2.imwrite(filename, img_rotate_90_clockwise)

img = Image.open(filename)

# print('Rotating into correct orientation...')

if hasattr(ImageOps, 'exif_transpose'):
# Very recent versions of PIL can do exit transpose internally
img = ImageOps.exif_transpose(img)
else:
# Otherwise, do the exif transpose ourselves
img = exif_transpose(img)
img.save(filename)
frame = cv2.imread(filename)

# has_frame, frame = vidcap.read()
# if not has_frame:
# break

frame = increase_brightness(frame, value=-10)
frame = contrast(frame, value=-10)

frame = sat(frame)
frame = white_balance(frame)

detections = face_detector.get_detections(frame)
if not detections:
response['message'] = "Face not Found in image."
response['code'] = 2
return response
left, top, right, bottom = detections[0][0]

b = check_brightness(frame)
if b <= brightness_threshold:
running_flag = False
response['message'] = "Kindly ensure adequate light conditions are followed."
response['code'] = 2
return response

# sat_frame = spoof_frame(frame)
# sat_detections = face_detector.get_detections(sat_frame)
# if sat_detections:
# spoof_flag = True
# since_last_spoof_counter = 0
# else:
# spoof_flag = False
# since_last_spoof_counter += 1

# frame_width = vidcap.get(3)
# width_limits = [frame_width * 0.2, frame_width * 0.8]
h, w, _ = frame.shape
size = [h, w]

pixels=size[0]*size[1]
sat_frame=spoof_frame(frame)
red_pix=np.sum(sat_frame==255)/(pixels)

if red_pix<0.2:
face_pixels = abs((right-left) * (top-bottom))
face_sat_frame = spoof_frame(frame[top:bottom, left:right])
face_red_pix = np.sum(face_sat_frame == 255)/(face_pixels)

if face_red_pix<0.2:
running_flag=False
response['message']='Kindly ensure there is no light source behind you.'
response['code'] = 2
return response

faces =[]
confidence = None, None
for rect, _ in detections:
left, top, right, bottom = rect
faces.append(frame[top:bottom, left:right])
if faces:
confidence = spoof_model.forward(faces)
confidence = list(map(lambda x: x.reshape(-1), confidence))

for i, rect in enumerate(detections):
left, top, right, bottom = rect[0]
area = calc_area(rect[0], size)
if area < 0.15:
off_center_counter += 1
if spoof_flag:
spoof_flag_counter += 1
elif confidence[i][0] > real_threshold:
# real_flag = True
real_counter += 1
elif confidence[i][1] > spoof_threshold:
spoof_counter += 1


if off_center_counter == off_center_threshold:
running_flag = False
response['message'] = 'Face too far, kindly move closer to camera and retry.'
response['code'] = 2

elif spoof_flag_counter == spoof_flag_threshold:
running_flag = False
response['message'] = 'Possible fraud Detected'
response['code'] = 1

elif spoof_counter >= spoof_counter_threshold:
running_flag = False
response['message'] = 'Possible fraud Detected'
response['code'] = 1

print('Spoof Counter:', spoof_counter,' ','Percentage:',confidence[i][1])
print('Real Counter:', real_counter,' ','Percentage:',confidence[i][0])
print('Area: ', area )
continue
break
response['spoof_flag'] = spoof_flag
response['off_center_counter'] = off_center_counter
response['spoof_flag_counter'] = spoof_flag_counter
response['since_last_spoof_counter'] = since_last_spoof_counter
response['spoof_counter'] = spoof_counter

if spoof_counter/(real_counter + spoof_counter + 0.0001)>= spoof_counter_threshold:
response['real_flag'] = False
response['message'] = 'Possible Fraud Detected.'
response['code'] = 1

if real_counter/(real_counter+spoof_counter + 0.0001) >= real_counter_threshold and running_flag == True:
response['real_flag'] = True
response['message'] = 'Live Face Detected'
response['code'] = 0
response['liveness_score'] = real_counter/int(frame_count)
print(response)
return response