def init_det_client(self, det_port, det_client_config):
self.det_preprocess = Sequential([
ResizeByFactor(32, 960), Div(255),
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose(
(2, 0, 1))
])
self.det_client = Client()
self.det_client.load_client_config(det_client_config)
self.det_client.connect(["127.0.0.1:{}".format(det_port)])
self.ocr_reader = OCRReader()
def init_det_debugger(self, det_model_config):
self.det_preprocess = Sequential([
ResizeByFactor(32, 960),
Div(255),
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
Transpose((2, 0, 1))
])
self.det_client = Debugger()
self.det_client.load_model_config(det_model_config,
gpu=True,
profile=False)
self.ocr_reader = OCRReader()
def init_rec(self):
self.ocr_reader = OCRReader()
self.text_recognizer = TextRecognizerHelper(global_args)
def init_rec(self):
self.ocr_reader = OCRReader()
def init_op(self):
self.ocr_reader = OCRReader()
self.get_rotate_crop_image = GetRotateCropImage()
self.sorted_boxes = SortedBoxes()
client.load_client_config(sys.argv[1:])
client.connect(["127.0.0.1:9293"])
import paddle
test_img_dir = "imgs/"
def cv2_to_base64(image):
return base64.b64encode(image) #data.tostring()).decode('utf8')
for img_file in os.listdir(test_img_dir):
with open(os.path.join(test_img_dir, img_file), 'rb') as file:
image_data = file.read()
image = cv2_to_base64(image_data)
fetch_map = client.predict(
feed={"image": image},
fetch=["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"],
batch=True)
result = {}
result["score"] = fetch_map["softmax_0.tmp_0"]
del fetch_map["softmax_0.tmp_0"]
rec_res = OCRReader().postprocess(fetch_map, with_score=False)
res_lst = []
for res in rec_res:
res_lst.append(res[0])
result["res"] = res_lst
print(result)
def init_rec(self):
self.ocr_reader = OCRReader()
self.text_classifier = TextClassifierHelper(global_args)