detector = RetinaFace(0)
cap = cv2.VideoCapture(0)
faces = None
results = None
while True:
start = time.time()
ret, img = cap.read()
if not ret:
break
if faces is None: # 只在第一帧检测
faces = detector(img, cv=True, threshold=0.5)
else:
ldm_new = results[0]
(x1, y1), (x2, y2) = ldm_new.min(0), ldm_new.max(0)
box_new = np.array([x1, y1, x2, y2])
box_new[:2] -= 10
box_new[2:] += 10
faces = [[box_new, None, None]]
if len(faces) == 0:
print("NO face is detected!")
continue
else:
results = predictor(faces, img, from_fd=True)
for face, landmarks in zip(faces, results):
img = drawLandmark_multiple(img, face[0], landmarks)
cv2.imshow("", img)
cv2.waitKey(1)
print("FPS=", 1 / (time.time() - start))
faces = None
results = None
recon_landmarks = []
while True:
ret, img = cap.read()
start = time.time()
if not ret:
break
if faces is None:
faces = detector(img, cv=True, threshold=0.5)
img_for_show = img.copy()
if len(faces) == 0:
print("NO face is detected!")
continue
else:
if results is None:
results = predictor(faces, img, from_fd=True)
faces = faces_from_results(results)
boxes = [face[0] for face in faces]
recon_results = regressor(boxes, img)
results = []
for recon_res, box in zip(recon_results, boxes):
pts = recon_res["pts68"]
results.append(pts)
img_for_show = drawLandmark_multiple(img_for_show, box, pts)
cv2.imshow("", img_for_show)
print("FPS=", 1 / (time.time() - start))
cv2.waitKey(1)