def run(self, camera_index=0):
cap = cv2.VideoCapture(camera_index)
cap.set(3, 1280)
cap.set(4, 720)
print('type q for exit')
while cap.isOpened():
ret, frame = cap.read()
if ret == False:
raise Exception(
'the camera not recognized: change camera_index param to '
+ str(0 if camera_index == 1 else 1))
faces, boxes, scores, landmarks = self.face_detector.detect_align(
frame)
if len(faces.shape) > 1:
emotions, emo_probs = self.emotion_detector.detect_emotion(
faces)
for i, b in enumerate(boxes):
special_draw(frame,
b,
landmarks[i],
name=emotions[i],
score=emo_probs[i])
cv2.imshow('frame', frame)
if cv2.waitKey(1) == ord('q'):
break
cv2.destroyAllWindows()
def run(self, camera_index=0):
if len(self.targets) < 1:
raise Exception(
"you don't have any person in facebank: add new person with 'add_from_webcam' or 'add_from_folder' function"
)
cap = cv2.VideoCapture(camera_index)
cap.set(3, 1280)
cap.set(4, 720)
# frame rate 6 due to my laptop is quite slow...
print('type q for exit')
while cap.isOpened():
ret, frame = cap.read()
if ret == False:
raise Exception(
'the camera not recognized: change camera_index param to '
+ str(0 if camera_index == 1 else 1))
faces, boxes, scores, landmarks = self.detector.detect_align(frame)
if len(faces.shape) > 1:
results, score = self.recognizer.infer(self.conf,
faces,
self.targets,
tta=self.tta)
for idx, bbox in enumerate(boxes):
special_draw(frame, bbox, landmarks[idx],
self.names[results[idx] + 1], score[idx])
cv2.imshow('face Capture', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
face_rec = FaceRecognizer(conf, inference=True)
face_rec.threshold = args.threshold
face_rec.model.eval()
if args.update:
targets, names = update_facebank(conf,
face_rec.model,
detector,
tta=args.tta)
else:
targets, names = load_facebank(conf)
# init camera
cap = cv2.VideoCapture(1)
cap.set(3, 1280)
cap.set(4, 720)
# frame rate 6 due to my laptop is quite slow...
while cap.isOpened():
_, frame = cap.read()
faces, boxes, scores, landmarks = detector.detect_align(frame)
if len(faces.shape) > 1:
results, score = face_rec.infer(conf, faces, targets, args.tta)
for idx, bbox in enumerate(boxes):
special_draw(frame, bbox, landmarks[idx],
names[results[idx] + 1], score[idx])
cv2.imshow('face Capture', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
from facelib import special_draw
import cv2
face_detector = FaceDetector(name='mobilenet',
weight_path='../Retinaface/weights/mobilenet.pth',
device='cuda',
face_size=(224, 224))
emotion_detector = EmotionDetector(name='densnet121',
weight_path='weights/densnet121.pth',
device='cuda')
vid = cv2.VideoCapture(1)
vid.set(3, 1280)
vid.set(4, 720)
while True:
ret, frame = vid.read()
faces, boxes, scores, landmarks = face_detector.detect_align(frame)
if len(faces.shape) > 1:
emotions, emo_probs = emotion_detector.detect_emotion(faces)
for i, b in enumerate(boxes):
special_draw(frame,
b,
landmarks[i],
name=emotions[i],
score=emo_probs[i])
cv2.imshow('frame', frame)
if cv2.waitKey(1) == ord('q'):
break
cv2.destroyAllWindows()
from facelib import special_draw
import cv2
from time import time
face_detector = FaceDetector(name='mobilenet',
weight_path='../Retinaface/weights/mobilenet.pth',
device='cuda')
age_gender_detector = AgeGenderEstimator(
name='full', weight_path='weigths/ShufflenetFull.pth', device='cuda')
vid = cv2.VideoCapture(1)
vid.set(3, 1280)
vid.set(4, 720)
while True:
ret, frame = vid.read()
faces, boxes, scores, landmarks = face_detector.detect_align(frame)
if len(faces.shape) > 1:
tic = time()
genders, ages = age_gender_detector.detect(faces)
print(time() - tic)
for i, b in enumerate(boxes):
special_draw(frame,
b,
landmarks[i],
name=genders[i] + ' ' + str(ages[i]))
cv2.imshow('frame', frame)
if cv2.waitKey(1) == ord('q'):
break
cv2.destroyAllWindows()
from facelib import FaceDetector
detector = FaceDetector(name='mobilenet',
weight_path='weights/mobilenet.pth',
device='cuda',
face_size=(224, 224))
cap = cv2.VideoCapture(1)
cap.set(3, 1280)
cap.set(4, 720)
while True:
_, frame = cap.read()
tic = time()
# boxes, scores, landmarks = detector.detect_faces(frame)
faces, boxes, scores, landmarks = detector.detect_align(frame)
print('forward time: ', time() - tic)
if len(faces.shape) > 1:
for idx, bbox in enumerate(boxes):
special_draw(frame,
bbox,
landmarks[idx],
name='face',
score=scores[idx])
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()