def session(cli, add):
"""
sl , sr : synchronized set speed
al, ar : asynchronous set speed
gs: get speed
gi: get information
sp: synchronized get picture :response 'ok'
ap: asynchronized get picrture
vd: stream video
sv: stop stream video
"""
while True:
command_raw = cli.recv(unpacker.size)
name, speed = unpacker.unpack(command_raw)
name = name.decode()
if name[0] == 's':
if name[1] == 'p':
cli.sendall(get_frame())
print('wait for response')
res = cli.recv(unpacker.size)
n, s = unpacker.unpack(res)
if not n.decode() == 'ok':
print('send image failed')
if name[1] == 'l':
left_motor.change_speed(speed)
cli.sendall(single_packer.pack(left_motor.get_speed()))
elif name[1] == 'r':
right_motor.change_speed(speed)
cli.sendall(single_packer.pack(right_motor.get_speed()))
elif name[0] == 'a':
if name[1] == 'p':
fb = get_frame()
cli.sendall(fb)
if name[1] == 'l':
left_motor.change_speed(speed)
elif name[1] == 'r':
right_motor.change_speed(speed)
elif name[0] == 'g':
if name[1] == 's':
cli.sendall(double_packer.pack(left_motor.get_speed(), right_motor.get_speed()))
elif name[1] == 'i':
fbs, speeds = get_packed_info()
cli.sendall(fbs)
cli.sendall(speeds)
elif name == 'in':
size = get_frame_size()
picked = single_packer.pack(size)
cli.sendall(picked)
def cam_process():
global encodings, current_faces, zach_encoding, zach_image
while True:
frame = camera.get_frame()
if frame is None:
break
# find faces
face_locations = face_recognition.face_locations(frame)
face_encodings = face_recognition.face_encodings(frame, face_locations)
# identify faces
for enc in encodings:
if not enc[0] in current_faces.keys():
current_faces[enc[0]] = 0
current_faces[
enc[0]] = 1 if True in face_recognition.compare_faces(
face_encodings, enc[1]) else current_faces[enc[0]] * .75
# tell the keylogger what faces are visible
faces = []
for key in current_faces.keys():
if current_faces[key] >= .25:
faces.append(key)
keylogger.set_faces(faces)
print(current_faces)
time.sleep(.3)
def gen():
camera = VideoCamera(server_conf.camera_source)
detector = object_detector.ObjectDetector(
'ssd_mobilenet_v1_coco_2017_11_17')
face_recog_m = FaceRecog()
self.logger.debug("start detector")
#detector = ObjectDetector('mask_rcnn_inception_v2_coco_2018_01_28')
#detector = ObjectDetector('pet', label_file='data/pet_label_map.pbtxt')
retry_cnt = 0
while True:
try:
frame = camera.get_frame()
frame, face_result_list = face_recog_m.get_frame_live(
frame)
#frame = cam.get_frame()
frame, obj_detect_dict = detector.detect_objects_live(
frame)
self.buffer_handle(face_result_list, obj_detect_dict)
ret, jpg = cv2.imencode('.jpg', frame)
jpg_bytes = jpg.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpg_bytes +
b'\r\n\r\n')
except Exception as err:
self.logger.error(str(err))
try:
camera = VideoCamera(server_conf.camera_source)
except:
retry_cnt += 1
if retry_cnt > self.retry_cnt_max:
break
def gen(camera,callback):
global frame,play;
while True:
if play:
frame = camera.get_frame(callback)
else:
time.sleep(1)
yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
def get_snapshot(cam_no):
if not session.get('logged_in'):
return "Login to view feed"
# For now, save it locally then send it.
# TODO Fix this in the future.
result = cv2.imwrite("snapshot.jpg", camera.get_frame(cam_no))
dir = app.root_path
return send_from_directory(directory=dir, filename="snapshot.jpg")
def gen(camera):
while (int(time.time() - start_time) < capture_duration):
settings.init()
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
if len(settings.myList) != 0:
emotions.append(settings.myList[0][0])
print(settings.myList[0][0])
def gen2(camera):
while True:
#get camera frame
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
def gen(camera):
#start_time = time.time() #New---Code--Added
#timestamp_record.append(start_time) #New---Code--Added
while True:
#get camera frame
frame = camera.get_frame() #start_time,timestamp_record)
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
def gen(camera):
"""Video streaming generator function."""
reference = 100
counter = 0
init_time = time.time()
while True:
# Getting frame from camera object
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
def gen(camera):
global words
print("working")
while True:
frame = camera.get_frame()
# yield (b'--frame\r\n'
# b'Content-Type: image/jpeg\r\n\r\n' + frame[0] + b'\r\n\r\n')
if frame[1] == False:
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame[0] + b'\r\n\r\n')
else:
print("Text: ", frame[2])
finalAnswer="right"
words = frame[2]
def gen(camera, save=False, vstart=False):
while True:
frame = camera.get_frame(False,save,vstart)
yield (b'--frame\r\nContent-Type: image/jpeg\r\n\r\n{0}\r\n\r\n'.format(frame))
def getFrameFromCamera(self):
frame = camera.get_frame()
while len(frame) <= 0:
frame = camera.get_frame()
frame = np.fromstring(frame, np.uint8).reshape(self.h, self.w, 3)
return frame
def gen(camera):
while True:
frame = camera.get_frame(face_cascade)
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
def gen(camera, save=False, vstart=False):
while True:
frame = camera.get_frame(False,save,vstart)
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
targetValues['lowerLimits'] = np.array([target[0], target[1], target[2]])
targetValues['upperLimits'] = np.array([target[3], target[4], target[5]])
targetValues['targetKerne'] = np.ones((target[6], target[6]), np.uint8)
targetValues = {'lowerLimits': None, 'upperLimits': None, 'kernelDilate': None}
set_target_basket(opponent)
values = []
cv2.namedWindow('rgb_img', cv2.WINDOW_NORMAL)
while True:
if cv2.waitKey(1) & 0xFF == ord('q'):
break
depth_frame, frame = camera.get_frame()
hsv_frame = camera.to_hsv(frame)
basket = camera.basket_bottom(hsv_frame, targetValues)
if basket:
print("Bottom coordinate:", basket[1])
cv2.putText(frame, str(basket), tuple(basket),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
else:
print("No Basket")
cv2.imshow("Show", frame)
camera.stop()
cv2.destroyAllWindows()
def gen(camera, save=False, vstart=False):
while True:
frame = camera.get_frame(False, save, vstart)
yield (b'--frame\r\nContent-Type: image/jpeg\r\n\r\n{0}\r\n\r\n'.
format(frame))
def gen():
while True:
f = camera.get_frame(_cam)
r = camera.fmt_frame(_cam)
yield (r)
def calc2():
return Response(get_frame(1),
mimetype='multipart/x-mixed-replace; boundary=frame')
def get_packed_info():
frame_bytes = get_frame()
ls = left_motor.get_speed()
rs = right_motor.get_speed()
speeds = double_packer.pack(ls, rs)
return frame_bytes, speeds
cv2.createTrackbar('hB', "Controls", bars[3], 255, partial(updateValue, 3))
cv2.createTrackbar('hG', "Controls", bars[4], 255, partial(updateValue, 4))
cv2.createTrackbar('hR', "Controls", bars[5], 255, partial(updateValue, 5))
cv2.createTrackbar('Dilate', "Controls", bars[6], 20, partial(updateValue, 6))
# cv2.createTrackbar('Erode', "Controls", bars[7], 20, partial(updateValue, 7))
try:
while True:
# kernel
values['kernelDilate'] = np.ones((bars[6], bars[6]), np.uint8)
# kernelErode = np.ones((bars[7],bars[7]),np.uint8)
values['lowerLimits'] = np.array([bars[0], bars[1], bars[2]])
values['upperLimits'] = np.array([bars[3], bars[4], bars[5]])
d, frame = camera.get_frame()
#frame = frame[600:680, 530:650]
hsv = camera.to_hsv(frame)
# for balls
processed_frame = camera.process_frame(hsv, values)
# for baskets
# processed_frame = Camera.process_basket(hsv, lowerLimits, upperLimits, kernelDilate)
contours, _hierarchy = cv2.findContours(processed_frame, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
circles = map(cv2.minEnclosingCircle, contours)
# tagging all blobs
for i in circles:
devices = [args.device, args.device_age_gender]
models = [args.model_face, args.model_age_gender]
if "CPU" in devices and args.cpu_extension is None:
print("\nPlease try to specify cpu extensions library path in demo's command line parameters using -l ""or --cpu_extension command line argument")
sys.exit(1)
detections = interactive_detection.Detections(
devices, models, args.cpu_extension, args.plugin_dir,args.prob_threshold, args.prob_threshold_face)
ct = CentroidTracker()
camera = VideoCamera(args.input, detections, args.no_v4l, ct)
# このframeにはすでに描画処理されているものだな
while True:
frame = camera.get_frame(flip_code, is_age_gender_detection)
# show the output frame
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
dump_json(object_list)
break
# if we are using a webcam, release the pointer
if video is None:
vs.stop()
dump_json(object_list)
# otherwise, release the file pointer
else:
