Merge pull request #277 from tink2123/fix_resize_shape

fix resize shape

ppocr/data/rec/img_tools.py

@@ -97,10 +97,11 @@ def process_image(img,
                   max_text_length=None,
                   tps=None,
                   infer_mode=False):
-    if not infer_mode or char_ops.character_type == "en" or tps != None:
-        norm_img = resize_norm_img(img, image_shape)
-    else:
+    if infer_mode and char_ops.character_type == "ch" and not tps:
         norm_img = resize_norm_img_chinese(img, image_shape)
+    else:
+        norm_img = resize_norm_img(img, image_shape)
+
     norm_img = norm_img[np.newaxis, :]
     if label is not None:
         # char_num = char_ops.get_char_num()
@@ -109,7 +110,8 @@ def process_image(img,
             logger.info(
                 "Warning in ppocr/data/rec/img_tools.py:line106: Wrong data type."
                 "Excepted string with length between 1 and {}, but "
-                "got '{}'. Label is '{}'".format(max_text_length, len(text),label))
+                "got '{}'. Label is '{}'".format(max_text_length,
+                                                 len(text), label))
             return None
         else:
             if loss_type == "ctc":

tools/infer/predict_rec.py

@@ -53,7 +53,7 @@ class TextRecognizer(object):
         imgC, imgH, imgW = self.rec_image_shape
         assert imgC == img.shape[2]
         if self.character_type == "ch":
-            imgW = int(math.ceil(32 * max_wh_ratio))
+            imgW = int((32 * max_wh_ratio))
         h, w = img.shape[:2]
         ratio = w / float(h)
         if math.ceil(imgH * ratio) > imgW: