def to_pb_image(input_image, encode_format='.jpeg', compression_level=0.8):
"""Converts a numpy array image to ProtoBuf Object.
Args:
input_image (Numpy Array): image
encode_format (str): standard .jpeg
compression_level (float): standard 0.8
Returns:
Image (Image): Protobuf object from is_msgs.
"""
if isinstance(input_image, np.ndarray):
if encode_format == '.jpeg':
params = [
cv2.IMWRITE_JPEG_QUALITY,
int(compression_level * (100 - 0) + 0)
]
elif encode_format == '.png':
params = [
cv2.IMWRITE_PNG_COMPRESSION,
int(compression_level * (9 - 0) + 0)
]
else:
return Image()
cimage = cv2.imencode(ext=encode_format,
img=input_image,
params=params)
return Image(data=cimage[1].tobytes())
elif isinstance(input_image, Image):
return input_image
else:
return Image()
def get_pb_image(input_image, encode_format='.jpeg', compression_level=0.8):
if isinstance(input_image, np.ndarray):
if encode_format == '.jpeg':
params = [cv2.IMWRITE_JPEG_QUALITY, int(compression_level * (100 - 0) + 0)]
elif encode_format == '.png':
params = [cv2.IMWRITE_PNG_COMPRESSION, int(compression_level * (9 - 0) + 0)]
else:
return Image()
cimage = cv2.imencode(ext=encode_format, img=input_image, params=params)
return Image(data=cimage[1].tobytes())
elif isinstance(input_image, Image):
return input_image
else:
return Image()
def grab_image(self):
with self.lock:
diff = self.deadline - time.time()
if diff > 0:
time.sleep(diff)
with self.lock:
if diff < 0:
self.deadline = time.time()
before_get = time.time()
frame = self.video.getImageRemote(self.camera)
proc_begin = time.time()
width, height, buffer = frame[0], frame[1], frame[6]
mat = np.frombuffer(buffer,
dtype=np.uint8).reshape(height, width, -1)
if self.color_space == ColorSpaces.Value("GRAY"):
mat = cv2.cvtColor(mat, cv2.COLOR_BGR2GRAY)
image = cv2.imencode(ext=self.encode_format,
img=mat,
params=self.encode_parameters)
proc_end = time.time()
self.logger.debug(
"[GrabImage] New Frame (get={:.1f}ms, proc={:.1f}ms, next_in={:.1f}ms)",
(proc_begin - before_get) * 1000,
(proc_end - proc_begin) * 1000, diff * 1000)
self.deadline += 1.0 / self.fps
return Image(data=image[1].tobytes())
if len(sys.argv) > 1:
broker_uri = sys.argv[1]
channel = Channel(broker_uri)
subscription = Subscription(channel)
exporter = ZipkinExporter(
service_name='SkeletonsDetectorRequester',
host_name='localhost',
port=9411,
transport=BackgroundThreadTransport(max_batch_size=100),
)
image = cv2.imread('../image.png')
tracer = Tracer(exporter)
with tracer.span(name='image') as span:
cimage = cv2.imencode(ext='.jpeg', img=image, params=[cv2.IMWRITE_JPEG_QUALITY, 80])
data = cimage[1].tobytes()
im = Image(data=data)
msg = Message(content=im, reply_to=subscription)
msg.inject_tracing(span)
channel.publish(message=msg, topic='SkeletonsDetector.Detect')
cid = msg.correlation_id
while True:
msg = channel.consume()
if msg.correlation_id == cid:
skeletons = msg.unpack(ObjectAnnotations)
print(skeletons)
sys.exit(0)