fix bug of image transforms

ppcls/configs/ImageNet/HRNet/HRNet_W18_C.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/HRNet/HRNet_W30_C.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/HRNet/HRNet_W32_C.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/HRNet/HRNet_W40_C.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/HRNet/HRNet_W48_C.yaml

@@ -76,8 +76,6 @@ DataLoader:
         image_root: "./dataset/ILSVRC2012/"
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
-          - ResizeImage:
-              size: 224
           - NormalizeImage:
               scale: 0.00392157
               mean: [0.485, 0.456, 0.406]

ppcls/configs/ImageNet/HRNet/HRNet_W64_C.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/Ineption/InceptionV3.yaml

@@ -77,7 +77,9 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
-              size: 224
+              resize_short: 320
+          - CropImage:
+              size: 299
           - NormalizeImage:
               scale: 0.00392157
               mean: [0.485, 0.456, 0.406]

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_25.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_5.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV1/MobileNetV1_x0_75.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_35.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_5.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x0_75.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_25.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_35.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_5.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x0_75.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x1_0.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_small_x1_25.yaml

@@ -24,6 +24,7 @@ Loss:
   Train:
     - CELoss:
         weight: 1.0
+        epsilon: 0.1
   Eval:
     - CELoss:
         weight: 1.0
@@ -75,6 +76,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet101.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet101_vd.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet152.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet152_vd.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet18.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet18_vd.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet200_vd.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet34.yaml

@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet34_vd.yaml

@@ -17,7 +17,7 @@ Global:
 
 # model architecture
 Arch:
-  name: "ResNet101_vd"
+  name: "ResNet34_vd"
  
 # loss function config for traing/eval process
 Loss:
@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet50.yaml

 # global configs
 Global:
-  checkpoints: null
+  checkpoints: "output/ResNet50/ppcls_epoch_15"
   pretrained_model: null
   output_dir: "./output/"
   device: "gpu"
@@ -77,6 +77,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/VGG/VGG11.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/VGG/VGG13.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/VGG/VGG16.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/configs/ImageNet/VGG/VGG19.yaml

@@ -75,6 +75,8 @@ DataLoader:
         cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
         transform_ops:
           - ResizeImage:
+              resize_short: 256
+          - CropImage:
               size: 224
           - NormalizeImage:
               scale: 0.00392157

ppcls/data/dataset/imagenet_dataset.py

@@ -30,13 +30,18 @@ from .common_dataset import CommonDataset
 
 class ImageNetDataset(CommonDataset):
 
-    def _load_anno(self):
+    def _load_anno(self, seed=None):
         assert os.path.exists(self._cls_path)
         assert os.path.exists(self._img_root)
         self.images = []
         self.labels = []
+
         with open(self._cls_path) as fd:
             lines = fd.readlines()
+            if seed is not None:
+                np.random.RandomState(seed).shuffle(lines)
+            else:
+                np.random.shuffle(lines)
             for l in lines:
                 l = l.strip().split(" ")
                 self.images.append(os.path.join(self._img_root, l[0]))