def run(self):
from architecture.sub_model import load_sub_models
sub_models = load_sub_models(self._weights_path, self._input_size)
sub_model = sub_models[self._model_id]
# sub_model.summary()
flag = 0
while True:
if len(self._input_conn) == flag and flag != 0:
print("{} conv is over".format(self._model_id))
break
if self._input_conn:
# print("{} conv conn is not empty".format(self._model_id))
# test_img = self._input_conn.get()
test_img = self._input_conn[flag]
# res_img = self.predict(sub_model, test_img)
pre_tile_img_set = []
for h in range(len(test_img)):
pre_tiles = []
for w in range(len(test_img[0])):
curr_tile = test_img[h][w]
pre_img = self.predict(sub_model, curr_tile)
pre_tiles.append(pre_img)
pre_tile_img_set.append(pre_tiles)
self._output_conn.append(pre_tile_img_set)
flag += 1
self._start_flag.value -= 1
self._next_flag.value += 1
else:
time.sleep(self._sleep_time)
def run(self):
from architecture.sub_model import load_sub_models
sub_models = load_sub_models(self._weights_path, self._input_size)
sub_model = sub_models[self._model_id]
# sub_model.summary()
flag = 0
while True:
if len(self._input_conn) == flag:
print("queue is empty")
break
if self._input_conn:
# test_img = self._input_conn.get()
test_img = self._input_conn[flag]
# res_img = self.predict(sub_model, test_img)
pre_tile_img_set = []
for h in range(len(test_img)):
pre_tiles = []
for w in range(len(test_img[0])):
curr_tile = test_img[h][w]
pre_img = self.predict(sub_model, curr_tile)
pre_tiles.append(pre_img)
pre_tile_img_set.append(pre_tiles)
self._output_conn.append(pre_tile_img_set)
flag += 1
self._start_flag.value += 1
def run(self):
from architecture.sub_model import load_sub_models
sub_models = load_sub_models(self._weights_path, self._input_size)
sub_model = sub_models[self._model_id]
sub_model.summary()
flag = 0
while True:
if self._start_flag.value:
print("{} conv conn is not empty".format(self._model_id))
# test_img = self._input_conn.get()
test_img = self._input_conn[flag]
# if ((self._input_conn.qsize()) == 0):
if len(self._input_conn) == flag:
print ("queue is empty")
break
res_img = self.predict(sub_model, test_img)
print ("the shape of res img{}".format(res_img.shape))
self._output_conn.append(res_img)
flag += 1
self._start_flag.value -= 1
self._next_flag.value += 1
else:
if flag != 0:
print ("{} conv is over".format(self._model_id))
break
else:
time.sleep(self._sleep_time)
print("{} conv is wating:{}".format(self._model_id, self._start_flag.value))
def run(self):
from architecture.sub_model import load_sub_models
sub_models = load_sub_models(self._weights_path, self._input_size)
sub_model = sub_models[self._model_id]
# sub_model.summary()
flag = 0
while True:
if len(self._input_conn) == flag and flag != 0:
print("{} conv is over".format(self._model_id))
break
if self._start_flag.value:
# test_img = self._input_conn.get()
test_img = self._input_conn[flag]
crop_part = self._crop_conn[flag]
# res_img = self.predict(sub_model, test_img, crop_part)[0]
pre_tile_img_set = []
for h in range(len(test_img)):
pre_tiles = []
for w in range(len(test_img[0])):
curr_tile = test_img[h][w]
crop_tile = crop_part[h][w]
pre_img = self.predict(sub_model, curr_tile,
crop_tile)[0]
pre_tiles.append(pre_img)
pre_tile_img_set.append(pre_tiles)
res_img = self.tile_set2img(pre_tile_img_set, self._overlap_px)
# print ("the shape of res img{}".format(res_img.shape))
self.output_img(self._name_list[flag], res_img,
self._output_dir)
self._output_conn.append(res_img)
flag += 1
self._start_flag.value -= 1
else:
if flag != 0:
print("{} conv is over".format(self._model_id))
break
else:
time.sleep(self._sleep_time)
def run(self):
from architecture.sub_model import load_sub_models
sub_models = load_sub_models(self._weights_path,self._input_size)
sub_model = sub_models[self._model_id]
sub_model.summary()
flag = 0
while True:
# test_img = self._input_conn.get()
test_img = self._input_conn[flag]
# if ((self._input_conn.qsize()) == 0):
if len(self._input_conn) == flag+1:
print ("queue is empty")
break
res_img = self.predict(sub_model, test_img)
print("the shape of res img{}".format(res_img.shape))
self._output_conn.append(res_img)
flag += 1
self._start_flag.value += 1
print("{} ===== predict done".format(self._model_id))
print ("===========================self._start_flag: {}".format(self._start_flag.value))