def predict_mask(module, input_img, id, batch_size, extra=None, r_img=True):
output_folder = "detection_result"
global use_gpu
method_name = module.desc.attr.map.data['default_signature'].s
predict_method = getattr(module, method_name)
try:
data = {}
if input_img is not None:
input_img = {"image": input_img}
data.update(input_img)
if extra is not None:
data.update(extra)
r_img = False if "visual_result" in extra.keys() else True
results = predict_method(data=data,
visualization=r_img,
use_gpu=use_gpu,
batch_size=batch_size)
results = utils.handle_mask_results(results)
except Exception as err:
curr = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time()))
print(curr, " - ", err)
return {"result": "Please check data format!"}
finally:
base64_list = []
results_pack = []
if input_img is not None:
if r_img is False:
for index in range(len(results)):
results[index]["path"] = ""
results_pack = results
else:
input_img = input_img.get("image", [])
for index in range(len(input_img)):
item = input_img[index]
with open(os.path.join(output_folder, item), "rb") as fp:
b_head = "data:image/" + item.split(
".")[-1] + ";base64"
b_body = base64.b64encode(fp.read())
b_body = str(b_body).replace("b'", "").replace("'", "")
b_img = b_head + "," + b_body
base64_list.append(b_img)
results[index]["path"] = results[index]["path"].replace(
id + "_", "") if results[index]["path"] != "" \
else ""
results[index].update({"base64": b_img})
results_pack.append(results[index])
os.remove(item)
os.remove(os.path.join(output_folder, item))
else:
results_pack = results
return results_pack
def predict_mask(module_info, input_img, id, extra=None, r_img=False):
output_folder = "detection_result"
method_name = module_info["method_name"]
module = module_info["module"]
predict_method = getattr(module, method_name)
data_len = len(input_img) if input_img is not None else 0
data = {}
if input_img is not None:
input_img = {"image": input_img}
data.update(input_img)
if extra is not None:
data.update(extra)
r_img = True if "visual_result" in extra.keys() else False
predict_args = module_info["predict_args"].copy()
predict_args.update({"data": data})
if isinstance(predict_method, functools.partial):
predict_method = predict_method.func
predict_args.update({"sign_name": method_name})
for item in predict_method.__code__.co_varnames:
if item in module_info.keys():
predict_args.update({item: module_info[item]})
try:
results = predict_method(**predict_args)
results = utils.handle_mask_results(results, data_len)
except Exception as err:
curr = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time()))
print(curr, " - ", err)
return gen_result("-1", "Please check data format!", "")
finally:
base64_list = []
results_pack = []
if input_img is not None:
if r_img is False:
for index in range(len(results)):
results[index]["path"] = ""
results_pack = results
str_id = id + "*"
files_deleted = glob.glob(str_id)
for path in files_deleted:
if os.path.exists(path):
os.remove(path)
else:
input_img = input_img.get("image", [])
for index in range(len(input_img)):
item = input_img[index]
file_path = os.path.join(output_folder, item)
if not os.path.exists(file_path):
results_pack.append(results[index])
os.remove(item)
else:
with open(file_path, "rb") as fp:
b_head = "data:image/" + item.split(
".")[-1] + ";base64"
b_body = base64.b64encode(fp.read())
b_body = str(b_body).replace("b'", "").replace(
"'", "")
b_img = b_head + "," + b_body
base64_list.append(b_img)
results[index]["path"] = results[index]["path"].replace(
id + "_", "") if results[index]["path"] != "" \
else ""
results[index].update({"base64": b_img})
results_pack.append(results[index])
os.remove(item)
os.remove(os.path.join(output_folder, item))
else:
results_pack = results
return gen_result("0", "", str(results_pack))