fix all minor bugs

deploy/pdserving/clas_local_server.py

@@ -117,7 +117,7 @@ class OCRService(WebService):
 
 if __name__ == "__main__":
     ocr_service = OCRService(name="ocr")
-    ocr_service.load_model_config("cls_server")
+    ocr_service.load_model_config(global_args.cls_model_dir)
     ocr_service.init_rec()
     if global_args.use_gpu:
         ocr_service.prepare_server(

deploy/pdserving/clas_web_client.py

@@ -37,4 +37,3 @@ for img_file in os.listdir(test_img_dir):
     data = {"feed": [{"image": image}], "fetch": ["res"]}
     r = requests.post(url=url, headers=headers, data=json.dumps(data))
     print(r.json())
-    break

deploy/pdserving/det_local_server.py

@@ -96,7 +96,7 @@ class DetService(WebService):
 
 if __name__ == "__main__":
     ocr_service = DetService(name="ocr")
-    ocr_service.load_model_config("serving_server_dir")
+    ocr_service.load_model_config(global_args.det_model_dir)
     ocr_service.init_det()
     if global_args.use_gpu:
         ocr_service.prepare_server(

deploy/pdserving/det_rpc_server.py

@@ -79,7 +79,6 @@ class TextDetectorHelper(TextDetector):
 class DetService(WebService):
     def init_det(self):
         self.text_detector = TextDetectorHelper(global_args)
-        print("init finish")
 
     def preprocess(self, feed=[], fetch=[]):
         data = base64.b64decode(feed[0]["image"].encode('utf8'))
@@ -96,7 +95,7 @@ class DetService(WebService):
 
 if __name__ == "__main__":
     ocr_service = DetService(name="ocr")
-    ocr_service.load_model_config("serving_server_dir")
+    ocr_service.load_model_config(global_args.det_model_dir)
     ocr_service.init_det()
     if global_args.use_gpu:
         ocr_service.prepare_server(

deploy/pdserving/ocr_local_server.py

@@ -44,17 +44,16 @@ class TextSystemHelper(TextSystem):
         if self.use_angle_cls:
             self.clas_client = Debugger()
             self.clas_client.load_model_config(
-                "ocr_clas_server", gpu=True, profile=False)
+                global_args.cls_model_dir, gpu=True, profile=False)
             self.text_classifier = TextClassifierHelper(args)
         self.det_client = Debugger()
         self.det_client.load_model_config(
-            "serving_server_dir", gpu=True, profile=False)
+            global_args.det_model_dir, gpu=True, profile=False)
         self.fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]
 
     def preprocess(self, img):
         feed, fetch, self.tmp_args = self.text_detector.preprocess(img)
         fetch_map = self.det_client.predict(feed, fetch)
-        print("det fetch_map", fetch_map)
         outputs = [fetch_map[x] for x in fetch]
         dt_boxes = self.text_detector.postprocess(outputs, self.tmp_args)
         if dt_boxes is None:
@@ -90,12 +89,10 @@ class OCRService(WebService):
 
     def preprocess(self, feed=[], fetch=[]):
         # TODO: to handle batch rec images
-        print("start preprocess")
         data = base64.b64decode(feed[0]["image"].encode('utf8'))
         data = np.fromstring(data, np.uint8)
         im = cv2.imdecode(data, cv2.IMREAD_COLOR)
         feed, fetch, self.tmp_args = self.text_system.preprocess(im)
-        print("ocr preprocess done")
         return feed, fetch
 
     def postprocess(self, feed={}, fetch=[], fetch_map=None):

deploy/pdserving/ocr_rpc_server.py

@@ -25,7 +25,7 @@ from clas_rpc_server import TextClassifierHelper
 from det_rpc_server import TextDetectorHelper
 from rec_rpc_server import TextRecognizerHelper
 import tools.infer.utility as utility
-from tools.infer.predict_system import TextSystem
+from tools.infer.predict_system import TextSystem, sorted_boxes
 import copy
 
 global_args = utility.parse_args()
@@ -48,7 +48,7 @@ class TextSystemHelper(TextSystem):
             self.text_classifier = TextClassifierHelper(args)
         self.det_client = Client()
         self.det_client.load_client_config(
-            "ocr_det_server/serving_client_conf.prototxt")
+            "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"]
 
@@ -57,10 +57,10 @@ class TextSystemHelper(TextSystem):
         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)
+        print(dt_boxes)
         if dt_boxes is None:
             return None, None
         img_crop_list = []
-        sorted_boxes = SortedBoxes()
         dt_boxes = sorted_boxes(dt_boxes)
         for bno in range(len(dt_boxes)):
             tmp_box = copy.deepcopy(dt_boxes[bno])
@@ -70,6 +70,7 @@ class TextSystemHelper(TextSystem):
             feed, fetch, self.tmp_args = self.text_classifier.preprocess(
                 img_crop_list)
             fetch_map = self.clas_client.predict(feed, fetch)
+            print(fetch_map)
             outputs = [fetch_map[x] for x in self.text_classifier.fetch]
             for x in fetch_map.keys():
                 if ".lod" in x:

deploy/pdserving/ocr_web_client.py

@@ -36,8 +36,5 @@ for img_file in os.listdir(test_img_dir):
     image = cv2_to_base64(image_data1)
     data = {"feed": [{"image": image}], "fetch": ["res"]}
     r = requests.post(url=url, headers=headers, data=json.dumps(data))
-    print(r)
     rjson = r.json()
     print(rjson)
-    #for x in rjson["result"]["pred_text"]:
-    #    print(x)

deploy/pdserving/rec_local_server.py

@@ -85,7 +85,6 @@ class TextRecognizerHelper(TextRecognizer):
             rec_idx_lod = args["ctc_greedy_decoder_0.tmp_0.lod"]
             predict_lod = args["softmax_0.tmp_0.lod"]
             indices = args["indices"]
-            print("indices", indices, rec_idx_lod)
             rec_res = [['', 0.0]] * (len(rec_idx_lod) - 1)
             for rno in range(len(rec_idx_lod) - 1):
                 beg = rec_idx_lod[rno]
@@ -155,7 +154,6 @@ class OCRService(WebService):
             if ".lod" in x:
                 self.tmp_args[x] = fetch_map[x]
         rec_res = self.text_recognizer.postprocess(outputs, self.tmp_args)
-        print("rec_res", rec_res)
         res = {
             "pred_text": [x[0] for x in rec_res],
             "score": [str(x[1]) for x in rec_res]

deploy/pdserving/rec_rpc_server.py

@@ -91,7 +91,6 @@ class TextRecognizerHelper(TextRecognizer):
             rec_idx_lod = args["ctc_greedy_decoder_0.tmp_0.lod"]
             predict_lod = args["softmax_0.tmp_0.lod"]
             indices = args["indices"]
-            print("indices", indices, rec_idx_lod)
             rec_res = [['', 0.0]] * (len(rec_idx_lod) - 1)
             for rno in range(len(rec_idx_lod) - 1):
                 beg = rec_idx_lod[rno]
@@ -161,7 +160,6 @@ class OCRService(WebService):
             if ".lod" in x:
                 self.tmp_args[x] = fetch_map[x]
         rec_res = self.text_recognizer.postprocess(outputs, self.tmp_args)
-        print("rec_res", rec_res)
         res = {
             "pred_text": [x[0] for x in rec_res],
             "score": [str(x[1]) for x in rec_res]

deploy/pdserving/rec_web_client.py

@@ -37,4 +37,3 @@ for img_file in os.listdir(test_img_dir):
     data = {"feed": [{"image": image}], "fetch": ["res"]}
     r = requests.post(url=url, headers=headers, data=json.dumps(data))
     print(r.json())
-    break

tools/infer/predict_cls.py

@@ -33,7 +33,7 @@ from paddle import fluid
 
 class TextClassifier(object):
     def __init__(self, args):
-        if args.use_serving is False:
+        if args.use_pdserving is False:
             self.predictor, self.input_tensor, self.output_tensors = \
                 utility.create_predictor(args, mode="cls")
         self.cls_image_shape = [int(v) for v in args.cls_image_shape.split(",")]

tools/infer/predict_det.py

@@ -75,7 +75,7 @@ class TextDetector(object):
         else:
             logger.info("unknown det_algorithm:{}".format(self.det_algorithm))
             sys.exit(0)
-        if args.use_gpu is False:
+        if args.use_pdserving is False:
             self.predictor, self.input_tensor, self.output_tensors =\
                 utility.create_predictor(args, mode="det")
 

tools/infer/predict_rec.py

@@ -34,7 +34,7 @@ from ppocr.utils.character import CharacterOps
 
 class TextRecognizer(object):
     def __init__(self, args):
-        if args.use_serving is False:
+        if args.use_pdserving is False:
             self.predictor, self.input_tensor, self.output_tensors =\
                 utility.create_predictor(args, mode="rec")
         self.rec_image_shape = [int(v) for v in args.rec_image_shape.split(",")]

tools/infer/predict_system.py

@@ -161,7 +161,12 @@ def main(args):
             scores = [rec_res[i][1] for i in range(len(rec_res))]
 
             draw_img = draw_ocr(
-                image, boxes, txts, scores, drop_score=drop_score, font_path=font_path)
+                image,
+                boxes,
+                txts,
+                scores,
+                drop_score=drop_score,
+                font_path=font_path)
             draw_img_save = "./inference_results/"
             if not os.path.exists(draw_img_save):
                 os.makedirs(draw_img_save)

tools/infer/utility.py

@@ -37,7 +37,7 @@ def parse_args():
     parser.add_argument("--ir_optim", type=str2bool, default=True)
     parser.add_argument("--use_tensorrt", type=str2bool, default=False)
     parser.add_argument("--gpu_mem", type=int, default=8000)
-    parser.add_argument("--use_serving", type=str2bool, default=False)
+    parser.add_argument("--use_pdserving", type=str2bool, default=False)
 
     # params for text detector
     parser.add_argument("--image_dir", type=str)
@@ -73,9 +73,7 @@ def parse_args():
         default="./ppocr/utils/ppocr_keys_v1.txt")
     parser.add_argument("--use_space_char", type=str2bool, default=True)
     parser.add_argument(
-        "--vis_font_path",
+        "--vis_font_path", type=str, default="./doc/simfang.ttf")
-        type=str,
-        default="./doc/simfang.ttf")
 
     # params for text classifier
     parser.add_argument("--use_angle_cls", type=str2bool, default=False)
@@ -230,8 +228,7 @@ def draw_ocr_box_txt(image, boxes, txts, font_path="./doc/simfang.ttf"):
             1])**2)
         if box_height > 2 * box_width:
             font_size = max(int(box_width * 0.9), 10)
-            font = ImageFont.truetype(
+            font = ImageFont.truetype(font_path, font_size, encoding="utf-8")
-                font_path, font_size, encoding="utf-8")
             cur_y = box[0][1]
             for c in txt:
                 char_size = font.getsize(c)
@@ -240,8 +237,7 @@ def draw_ocr_box_txt(image, boxes, txts, font_path="./doc/simfang.ttf"):
                 cur_y += char_size[1]
         else:
             font_size = max(int(box_height * 0.8), 10)
-            font = ImageFont.truetype(
+            font = ImageFont.truetype(font_path, font_size, encoding="utf-8")
-                font_path, font_size, encoding="utf-8")
             draw_right.text(
                 [box[0][0], box[0][1]], txt, fill=(0, 0, 0), font=font)
     img_left = Image.blend(image, img_left, 0.5)