modified demo.py

.idea/workspace.xml

@@ -2,7 +2,9 @@
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-      <change beforePath="$PROJECT_DIR$/README.md" beforeDir="false" afterPath="$PROJECT_DIR$/README.md" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/demo.py" beforeDir="false" afterPath="$PROJECT_DIR$/demo.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/train.py" beforeDir="false" afterPath="$PROJECT_DIR$/train.py" afterDir="false" />
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@@ -38,16 +40,16 @@
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@@ -117,6 +101,11 @@
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+      <file pinned="false" current-in-tab="true">
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@@ -160,6 +149,18 @@
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@@ -168,17 +169,17 @@
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         <option value="$PROJECT_DIR$/lib/utils/preprocessing.py" />
         <option value="$PROJECT_DIR$/lib/dataset/_360cc.py" />
-        <option value="$PROJECT_DIR$/train.py" />
         <option value="$PROJECT_DIR$/lib/config/360CC_config.yaml" />
         <option value="$PROJECT_DIR$/lib/core/function.py" />
         <option value="$PROJECT_DIR$/lib/config/OWN_config.yaml" />
         <option value="$PROJECT_DIR$/lib/dataset/_own.py" />
         <option value="$PROJECT_DIR$/lib/dataset/__init__.py" />
         <option value="$PROJECT_DIR$/README.md" />
+        <option value="$PROJECT_DIR$/demo.py" />
+        <option value="$PROJECT_DIR$/train.py" />
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@@ -189,7 +190,8 @@
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@@ -199,6 +201,17 @@
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     <layout>
-      <window_info active="true" content_ui="combo" id="Project" order="0" visible="true" weight="0.2196162" />
+      <window_info active="true" content_ui="combo" id="Project" order="0" visible="true" weight="0.2217484" />
       <window_info id="Structure" order="1" side_tool="true" weight="0.25" />
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@@ -366,22 +368,26 @@
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+    <entry file="file://$PROJECT_DIR$/lib/config/OWN_config.yaml">
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@@ -404,61 +410,60 @@
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+      <provider selected="true" editor-type-id="text-editor" />
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+      <provider selected="true" editor-type-id="split-provider[text-editor;markdown-preview-editor]">
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+    <entry file="file://$PROJECT_DIR$/train.py">
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-          <second_editor />
+    <entry file="file://$PROJECT_DIR$/demo.py">
+      <provider selected="true" editor-type-id="text-editor">
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demo.py

@@ -31,10 +31,15 @@ def parse_arg():
 
 def recognition(config, img, model, converter, device):
 
-    # ratio resize
-    w_cur = int(img.shape[1] / (config.MODEL.IMAGE_SIZE.OW / config.MODEL.IMAGE_SIZE.W))
+    # github issues: https://github.com/Sierkinhane/CRNN_Chinese_Characters_Rec/issues/211
+    h, w = img.shape
+    # fisrt step: resize the height and width of image to (32, x)
+    img = cv2.resize(img, (0, 0), fx=config.MODEL.IMAGE_SIZE.H / h, fy=config.MODEL.IMAGE_SIZE.H / h, interpolation=cv2.INTER_CUBIC)
+
+    # second step: keep the ratio of image's text same with training
     h, w = img.shape
-    img = cv2.resize(img, (0, 0), fx=w_cur / w, fy=config.MODEL.IMAGE_SIZE.H / h, interpolation=cv2.INTER_CUBIC)
+    w_cur = int(img.shape[1] / (config.MODEL.IMAGE_SIZE.OW / config.MODEL.IMAGE_SIZE.W))
+    img = cv2.resize(img, (0, 0), fx=w_cur / w, fy=1.0, interpolation=cv2.INTER_CUBIC)
     img = np.reshape(img, (config.MODEL.IMAGE_SIZE.H, w_cur, 1))
 
     # normalize

train.py

@@ -64,17 +64,8 @@ def main():
     # define loss function
     criterion = torch.nn.CTCLoss()
 
-    optimizer = utils.get_optimizer(config, model)
-
     last_epoch = config.TRAIN.BEGIN_EPOCH
-    if config.TRAIN.RESUME.IS_RESUME:
-        model_state_file = config.TRAIN.RESUME.FILE
-        if model_state_file == '':
-            print(" => no checkpoint found")
-        checkpoint = torch.load(model_state_file, map_location='cpu')
-        model.load_state_dict(checkpoint['state_dict'])
-        last_epoch = checkpoint['epoch']
-
+    optimizer = utils.get_optimizer(config, model)
     if isinstance(config.TRAIN.LR_STEP, list):
         lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(
             optimizer, config.TRAIN.LR_STEP,
@@ -86,6 +77,16 @@ def main():
             config.TRAIN.LR_FACTOR, last_epoch - 1
         )
 
+    if config.TRAIN.RESUME.IS_RESUME:
+        model_state_file = config.TRAIN.RESUME.FILE
+        if model_state_file == '':
+            print(" => no checkpoint found")
+        checkpoint = torch.load(model_state_file, map_location='cpu')
+        model.load_state_dict(checkpoint['state_dict'])
+        # optimizer.load_state_dict(checkpoint['optimizer'])
+        # lr_scheduler.load_state_dict(checkpoint['lr_scheduler'])
+        last_epoch = checkpoint['epoch']
+
     train_dataset = get_dataset(config)(config, is_train=True)
     train_loader = DataLoader(
         dataset=train_dataset,
@@ -123,6 +124,8 @@ def main():
             {
                 "state_dict": model.state_dict(),
                 "epoch": epoch + 1,
+                # "optimizer": optimizer.state_dict(),
+                # "lr_scheduler": lr_scheduler.state_dict(),
                 "best_acc": best_acc,
             },  os.path.join(output_dict['chs_dir'], "checkpoint_{}_acc_{:.4f}.pth".format(epoch, acc))
         )