class TextSystemHelper(TextSystem):
def __init__(self, args):
self.text_detector = TextDetectorHelper(args)
self.text_recognizer = TextRecognizerHelper(args)
self.use_angle_cls = args.use_angle_cls
if self.use_angle_cls:
self.clas_client = Client()
self.clas_client.load_client_config(
os.path.join(args.cls_client_dir,
"serving_client_conf.prototxt"))
self.clas_client.connect(["127.0.0.1:9294"])
self.text_classifier = TextClassifierHelper(args)
self.det_client = Client()
self.det_client.load_client_config(
os.path.join(args.det_client_dir, "serving_client_conf.prototxt"))
self.det_client.connect(["127.0.0.1:9293"])
self.fetch = [
"save_infer_model/scale_0.tmp_0", "save_infer_model/scale_1.tmp_0"
]
def preprocess(self, img):
feed, fetch, self.tmp_args = self.text_detector.preprocess(img)
fetch_map = self.det_client.predict(feed, fetch)
outputs = [fetch_map[x] for x in fetch]
dt_boxes = self.text_detector.postprocess(outputs, self.tmp_args)
if dt_boxes is None:
return None, None
img_crop_list = []
dt_boxes = sorted_boxes(dt_boxes)
self.dt_boxes = dt_boxes
for bno in range(len(dt_boxes)):
tmp_box = copy.deepcopy(dt_boxes[bno])
img_crop = self.get_rotate_crop_image(img, tmp_box)
img_crop_list.append(img_crop)
if self.use_angle_cls:
feed, fetch, self.tmp_args = self.text_classifier.preprocess(
img_crop_list)
fetch_map = self.clas_client.predict(feed, fetch)
outputs = [fetch_map[x] for x in self.text_classifier.fetch]
for x in fetch_map.keys():
if ".lod" in x:
self.tmp_args[x] = fetch_map[x]
img_crop_list, _ = self.text_classifier.postprocess(
outputs, self.tmp_args)
feed, fetch, self.tmp_args = self.text_recognizer.preprocess(
img_crop_list)
return feed, self.fetch, self.tmp_args
def postprocess(self, outputs, args):
return self.text_recognizer.postprocess(outputs, args)
def __init__(self, args):
self.text_detector = TextDetectorHelper(args)
self.text_recognizer = TextRecognizerHelper(args)
self.use_angle_cls = args.use_angle_cls
if self.use_angle_cls:
self.clas_client = Client()
self.clas_client.load_client_config(
"cls_infer_client/serving_client_conf.prototxt")
self.clas_client.connect(["127.0.0.1:9294"])
self.text_classifier = TextClassifierHelper(args)
self.det_client = Client()
self.det_client.load_client_config(
"det_infer_client/serving_client_conf.prototxt")
self.det_client.connect(["127.0.0.1:9293"])
self.fetch = ["save_infer_model/scale_0.tmp_0", "save_infer_model/scale_1.tmp_0"]
def __init__(self, args):
self.text_detector = TextDetectorHelper(args)
self.text_recognizer = TextRecognizerHelper(args)
self.use_angle_cls = args.use_angle_cls
if self.use_angle_cls:
self.clas_client = Client()
self.clas_client.load_client_config(
"ocr_clas_client/serving_client_conf.prototxt")
self.clas_client.connect(["127.0.0.1:9294"])
self.text_classifier = TextClassifierHelper(args)
self.det_client = Client()
self.det_client.load_client_config(
"det_db_client/serving_client_conf.prototxt")
self.det_client.connect(["127.0.0.1:9293"])
self.fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]