def setUp(self):
p = "./images/2009_000237.jpg"
img = PIL.Image.open(p).convert("RGB")
img = np.array(img)
##mock data
save_list = [img] * 13
mq_dataset.intermediate_job_finish(out_queue, save_list)
def setUp(self):
global out_queue, in_queue, scan_dir, save_dir
out_queue = "unittest_transfer"
in_queue = "unittest_transfer_result"
scan_dir = "./unittest_listen/data_listen"
save_dir = "./unittest_listen/result_listen"
self.tearDown()
if not os.path.isdir(os.path.dirname(scan_dir)):
os.mkdir(os.path.dirname(scan_dir))
if not os.path.isdir(scan_dir):
os.mkdir(scan_dir)
if not os.path.isdir(save_dir):
os.mkdir(save_dir)
data_list = []
for i in range(batch_size):
mock_data = [create()] * 4
data_list.append(np.array(mock_data))
self.msg_list = []
self.msg_list = mq_dataset.intermediate_job_finish(
out_queue, data_list)
for i, (x, y) in enumerate(self.msg_list):
x = x.replace("type:image,job:unittest_transfer,source_id:",
"")
fn = os.path.join(save_dir, x + "_final_res.jpg")
da = create()
cv2.imwrite(fn, da)
def _post_process(msg_ids, result_list, each_image_list):
def format_img(result, each_image):
origin_image = Image.fromarray(each_image).convert('RGB')
origin_width, origin_height = origin_image.size
result = result * 255
result = np.array(result, dtype=np.uint8)
matte_image = Image.fromarray(result, mode='L') \
.resize([origin_width, origin_height], resample=Image.BILINEAR)
# matte_image_np=np.array(matte_image,dtype=np.uint8)
p = Image.new('RGBA', [origin_width, origin_height], (0, 0, 0))
p.paste(origin_image, (0, 0, origin_width, origin_height), matte_image)
p = p.convert("RGB")
return np.array(p), np.array(matte_image)
save_list = []
for msg_id, result, each_image in zip(msg_ids, result_list,
each_image_list):
rgb, matting = format_img(result, each_image)
save_list.append((msg_id, matting))
mq_dataset.intermediate_job_finish(in_queue, save_list)
def test_mmq(self):
import sys ,os
p=sys.argv[1]
if not os.path.isfile(p) :
raise Exception("not exist")
print ("will read",p)
# image=cv2.imread("./images/295b37832c0db6470a855640d6510c04.jpg")
image=cv2.imread(p)
# target_image=cv2.imread("./images/19064748793_bb942deea1_k.jpg")
print ("send...")
msg_id_list = mq_dataset.intermediate_job_finish("detectron", [image])
msg_id = msg_id_list[0]
furture_id , _= mq_dataset.build_key(msg_id,"detectron_result")
print (furture_id,"222")
while True :
if mq_dataset.is_exist(furture_id):
get_data=mq_dataset.get_msg_info(furture_id)
_,matting_list = get_data
bl=[np.zeros(matting_list.shape[1:],dtype=np.uint8)]
for i,m in enumerate(matting_list):
m=(m//255)*(i+1)
bl.append(m)
mm=m.copy()
mm[m!=0]=255
print (len(bl),len(matting_list))
print (np.unique(np.array(bl)))
###cover mask
source_img = image.copy()
new_img = util_cover_mask(image,bl)
img,mask = choice_mask_floors(new_img,np.array(bl) )
cv2.imwrite("t1_img.jpg",image)
cv2.imwrite("t1_img_mask.png",mask)
print ("save success")
break
def _response(self, cl_list):
save_list = []
for msg_id, rgb, matting in cl_list:
save_list.append((msg_id, matting))
mq_dataset.intermediate_job_finish(in_queue, save_list)
def _post_process(msg_id, info_path):
if os.path.isfile(info_path):
data = cv2.imread(info_path)
info_x = (msg_id, data)
msg_save_list = mq_dataset.intermediate_job_finish(
in_queue, [info_x])