return
self.__in_pipe.pull_wait()
ret, inference = self.__in_pipe.pull(self.__flush_pipe_on_read)
if ret:
self.__session_runner.get_in_pipe().push(
SessionRunnable(self.__job, inference, run_on_thread=self.__run_session_on_thread))
def __job(self, inference):
self.__out_pipe.push(
(self.__tf_sess.run(self.__z,
feed_dict={self.__x: inference.get_data()[0], self.__y: inference.get_data()[1]}),
inference))
if __name__ == '__main__':
session_runner = SessionRunner()
session_runner.start()
addOnGPU = SessionTest()
ip = addOnGPU.get_in_pipe()
op = addOnGPU.get_out_pipe()
addOnGPU.use_session_runner(session_runner)
addOnGPU.run()
def send():
while True:
ip.push_wait()
inference = Inference([random.randint(0, 100), random.randint(0, 100)])
from threading import Thread
from time import sleep
import cv2
import imutils
from py_tensorflow_runner.session_utils import SessionRunner
from py_face_detection.comparator_api.embedding_generator import EmbeddingGenerator
import glob
from proj_data.py_face_detection.infy_images import path as images_path
from proj_data.py_face_detection.embeddings import path as emb_path
import pickle
stop_flag = True
session_runner = SessionRunner()
generator = EmbeddingGenerator()
generator_ip = generator.get_in_pipe()
generator_op = generator.get_out_pipe()
generator.use_session_runner(session_runner)
generator.run()
#
# cap = cv2.VideoCapture('/home/developer/Downloads/video.mp4')
emb_dict = dict()
images_list = glob.glob(images_path.get() + "/**/*.JPG")
print(images_list)
image_dict = dict()
for images in images_list:
person_name = images.split("/")[-2]
if person_name not in image_dict.keys():
image_dict[person_name] = list()
ret, inference = detector.getOutPipe().pull(True)
if ret:
i_dets = inference.get_result()
pipe.push(i_dets.get_annotated())
if __name__ == '__main__':
fs = FlaskMovie()
fs.start("0.0.0.0", 5000)
session_runner = {}
detector = {}
cap = {}
pipe = {}
video_inputs = {0: 0, 1: 1}
for i in video_inputs.keys():
session_runner[i] = SessionRunner()
session_runner[i].start()
detector[i] = TFObjectDetector(PRETRAINED_ssd_mobilenet_v1_coco_2017_11_17, LABELMAP_mscoco, None,
'tf_api_' + str(i), True)
detector[i].use_session_runner(session_runner[i])
detector[i].run()
cap[i] = cv2.VideoCapture(video_inputs[i])
pipe[i] = Pipe()
fs.create('feed_' + str(i), pipe[i])
Thread(target=detect_objects, args=(cap[i], pipe[i], detector[i], False)).start()