def api(P1, P2, P3):
errmsg = ""
detected_person = [] #{}
opt_person = []
start_ts = time.time()
try:
#face_names,face_vectors,face_id_lists=get_face_db_from_redis(P1,P2)
face_names, face_vectors, face_id_lists = get_face_db_from_json(P1)
#print(face_names)
#print(face_vectors)
if os.path.isfile(P2):
test_face_imgs, test_locations, test_encodings = get_face_vector(
P2)
if len(test_encodings) > 0:
detected_person, _ = get_face_profile(face_names, face_vectors,
face_id_lists,
test_face_imgs,
test_locations,
test_encodings)
img = mark_face(P2, test_locations, detected_person)
pu.SaveImg(img, P3)
pu.ShowImgIfWinOS(img)
else:
errmsg = "image not exist"
except Exception as e:
errmsg = str(e)
for s in detected_person:
if s != '?': opt_person.append(s)
log.Json_log(l, "error_msg", errmsg)
log.Json_log(l, "detected", opt_person)
log.Json_log(l, "process_time", round(time.time() - start_ts, 3))
log.Json_print(l)
def api(P1, P2, P3):
imgs = []
totalimgs = []
errmsg = ""
start_ts = time.time()
have_face = False
best_score = 0
det_time = 0
fpsOpencvDnn = 0
try:
cap = cv2.VideoCapture(P1)
hasFrame, frame = cap.read()
#vid_writer = cv2.VideoWriter('output-dnn-{}.avi'.format(str(source).split(".")[0]),cv2.VideoWriter_fourcc('M','J','P','G'), 15, (frame.shape[1],frame.shape[0]))
frame_count = 0
tt_opencvDnn = 0
while (frame_count < int(P3)):
hasFrame, frame = cap.read()
if not hasFrame: break
frame_count += 1
if frame_count % frame_step != 0: continue
t = time.time()
# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
#sframe = cv2.resize(frame,(pw,ph),interpolation=cv2.INTER_AREA)
#sframe=frame
#sframe = sframe[:, :, ::-1]
#sframe = cv2.cvtColor(sframe,cv2.COLOR_BGR2GRAY)
sframe, imgs, bboxes = DetBodyFaces(frame, frame) #dnn 作法
#imgs,bboxes=pd.CvDetBodyFaces(sframe,frame) #haar 作法 face+body
#imgs,bboxes=pd.DeepDetBodyFaces(sframe,frame) #haar 作法 face+body
#bboxes=pd.CvDetFace(sframe,frame) #haar 作法 face
tt_opencvDnn += time.time() - t
fpsOpencvDnn = frame_count / tt_opencvDnn
label = "FPS : {:.2f}".format(fpsOpencvDnn)
#print(label)
pu.ShowCVVideoIfWinOS(sframe)
for img in imgs:
#pu.ShowImgIfWinOS(img)
totalimgs.append(img)
#pu.ShowImgIfWinOS(best_img)
#cv2.putText(outOpencvDnn, label, (10,50), cv2.FONT_HERSHEY_SIMPLEX, 1.1, (0, 0, 255), 3, cv2.LINE_AA)
#cv2.imshow("Face Detection Comparison", frame)
#vid_writer.write(frame)
if frame_count == 1: tt_opencvDnn = 0
det_time = time.time()
have_face, best_img, best_score = pd.DlibGetBestFace(totalimgs,
score=face_score,
debug=False)
if have_face:
pu.ShowImgIfWinOS(best_img)
nimg = ClipBestFace(best_img)
pu.ShowImgIfWinOS(nimg)
pu.SaveImg(nimg, P2)
except Exception as e:
errmsg = str(e)
log.Json_log(l, "p1", P1)
log.Json_log(l, "p2", P2)
log.Json_log(l, "p3", P3)
log.Json_log(l, "fps", fpsOpencvDnn)
log.Json_log(l, "processed_frames", frame_count)
log.Json_log(l, "face_detected", have_face)
log.Json_log(l, "face_score", best_score)
log.Json_log(l, "error_msg", errmsg)
log.Json_log(l, "process_time_detface", round(det_time - start_ts, 3))
log.Json_log(l, "process_time_bestface", round(time.time() - det_time, 3))
log.Json_print(l)
cv2.destroyAllWindows()
def api(P1, P2, P3):
imgs = []
totalimgs = []
errmsg = ""
have_face = False
best_score = 0
det_time = 0
fpsOpencvDnn = 0
first_frame = []
background_frame = []
try:
cap = cv2.VideoCapture(P1)
hasFrame, frame = cap.read()
#vid_writer = cv2.VideoWriter('output-dnn-{}.avi'.format(str(source).split(".")[0]),cv2.VideoWriter_fourcc('M','J','P','G'), 15, (frame.shape[1],frame.shape[0]))
frame_count = 0
tt_opencvDnn = 0
start_ts = time.time()
while (frame_count < int(P3)):
tt = time.time()
hasFrame, frame = cap.read()
pc.TIME_WAIT_FRAME += (time.time() - tt)
if not hasFrame: break
if len(first_frame) == 0: first_frame = frame
# if frame_count%30==0:
# background_frame=first_frame #background 每 30 frames refresh一次
# first_frame=frame
frame_count += 1
if frame_count % frame_step != 0: continue
t = time.time()
# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
#sframe = cv2.resize(frame,(pw,ph),interpolation=cv2.INTER_AREA)
#sframe=frame
#sframe = sframe[:, :, ::-1]
#sframe = cv2.cvtColor(sframe,cv2.COLOR_BGR2GRAY)
#------- 去除背景
cut_frame = cv2.resize(frame, (sw, sh),
interpolation=cv2.INTER_AREA)
gframe, cframe = pd.FilterFrame(frame, first_frame, pw, ph)
cframe, motion_rect = pd.FindMotionRect(cut_frame, cframe,
motion_size)
#motion_rect=[cut_frame]
#-------
motion_bboxes = []
motion_imgs = []
#if len(motion_rect)==0: continue
for m in motion_rect:
#pu.ShowImgIfWinOS(m)
#sframe,imgs, bboxes = pd.CVDnnDetBodyFaces(m,m) #dnn 作法
imgs, bboxes = pd.CvDetBodyFaces(
m, m, CVminNeighbors=1, minsize=25,
maxsize=200) #haar 作法 face+body
#imgs,bboxes=pd.DeepDetBodyFaces(m,m) #haar 作法 face+body
#bboxes=pd.CvDetFace(sframe,frame) #haar 作法 face
motion_bboxes = motion_bboxes + bboxes
motion_imgs = motion_imgs + imgs
#if len(motion_bboxes)>0: print(motion_bboxes)
tt_opencvDnn += time.time() - t
fpsOpencvDnn = frame_count / tt_opencvDnn
label = "FPS : {:.2f}".format(fpsOpencvDnn)
cv2.putText(cframe, label, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.0,
(0, 0, 255), 2, cv2.LINE_AA)
pu.ShowCVVideoIfWinOS(cframe)
for img in motion_imgs:
#pu.ShowImgIfWinOS(img)
totalimgs.append(img)
#cv2.imshow("Face Detection Comparison", frame)
#vid_writer.write(frame)
if frame_count == 1: tt_opencvDnn = 0
det_time = time.time()
have_face, best_img, best_score = pd.DlibGetBestFace(totalimgs,
score=face_score,
debug=False)
if have_face:
pu.ShowImgIfWinOS(best_img)
nimg = ClipBestFace(best_img)
pu.ShowImgIfWinOS(nimg)
pu.SaveImg(nimg, P2)
except Exception as e:
errmsg = str(e)
log.Json_log(l, "p1", P1)
log.Json_log(l, "p2", P2)
log.Json_log(l, "p3", P3)
log.Json_log(l, "fps", fpsOpencvDnn)
log.Json_log(l, "processed_frames", frame_count)
log.Json_log(l, "face_detected", have_face)
log.Json_log(l, "face_score", best_score)
log.Json_log(l, "error_msg", errmsg)
log.Json_log(l, "0.process_time_wait_frame", round(pc.TIME_WAIT_FRAME, 3))
log.Json_log(l, "1.process_time_filter_frame",
round(pc.TIME_FILTER_FRAME, 3))
log.Json_log(l, "2.process_time_motion_block",
round(pc.TIME_MOTION_DET, 3))
log.Json_log(l, "3.process_time_detface", round(pc.TIME_FACE_DET, 3))
log.Json_log(l, "4.process_time_bestface", round(time.time() - det_time,
3))
log.Json_log(l, "5.process_time_ui_shown", round(pc.TIME_UI_SHOWN, 3))
log.Json_log(l, "9.process_time_total", round(time.time() - start_ts, 3))
log.Json_print(l)
cv2.destroyAllWindows()