Merge branch 'dygraph' of github.com:wuyefeilin/PaddleSeg into dygraph

dygraph/datasets/__init__.py

@@ -12,5 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from .dataset import Dataset
 from .optic_disc_seg import OpticDiscSeg
 from .cityscapes import Cityscapes

dygraph/datasets/cityscapes.py

@@ -14,8 +14,7 @@
 
 import os
 
-from paddle.fluid.io import Dataset
-
+from .dataset import Dataset
 from utils.download import download_file_and_uncompress
 
 DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset')
@@ -70,16 +69,3 @@ class Cityscapes(Dataset):
                     image_path = os.path.join(self.data_dir, items[0])
                     grt_path = os.path.join(self.data_dir, items[1])
                 self.file_list.append([image_path, grt_path])
-
-    def __getitem__(self, idx):
-        image_path, grt_path = self.file_list[idx]
-        im, im_info, label = self.transforms(im=image_path, label=grt_path)
-        if self.mode == 'train':
-            return im, label
-        elif self.mode == 'eval':
-            return im, label
-        if self.mode == 'test':
-            return im, im_info, image_path
-
-    def __len__(self):
-        return len(self.file_list)

dygraph/datasets/dataset.py

+#   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from paddle.fluid.io import Dataset
+
+
+class Dataset(Dataset):
+    def __init__(self,
+                 data_dir,
+                 num_classes,
+                 train_list=None,
+                 val_list=None,
+                 test_list=None,
+                 separator=' ',
+                 transforms=None,
+                 mode='train'):
+        self.data_dir = data_dir
+        self.transforms = transforms
+        self.file_list = list()
+        self.mode = mode
+        self.num_classes = num_classes
+
+        if mode.lower() not in ['train', 'eval', 'test']:
+            raise Exception(
+                "mode should be 'train', 'eval' or 'test', but got {}.".format(
+                    mode))
+
+        if self.transforms is None:
+            raise Exception("transform is necessary, but it is None.")
+
+        self.data_dir = data_dir
+        if mode == 'train':
+            if train_list is None:
+                raise Exception(
+                    'When mode is "train", train_list is need, but it is None.')
+            elif not os.path.exists(train_list):
+                raise Exception(
+                    'train_list is not found: {}'.format(train_list))
+            else:
+                file_list = train_list
+        elif mode == 'eval':
+            if val_list is None:
+                raise Exception(
+                    'When mode is "eval", val_list is need, but it is None.')
+            elif not os.path.exists(val_list):
+                raise Exception('val_list is not found: {}'.format(val_list))
+            else:
+                file_list = val_list
+        else:
+            if test_list is None:
+                raise Exception(
+                    'When mode is "test", test_list is need, but it is None.')
+            elif not os.path.exists(test_list):
+                raise Exception('test_list is not found: {}'.format(test_list))
+            else:
+                file_list = test_list
+
+        with open(file_list, 'r') as f:
+            for line in f:
+                items = line.strip().split(separator)
+                if len(items) != 2:
+                    if mode == 'train' or mode == 'eval':
+                        raise Exception(
+                            "File list format incorrect! It should be"
+                            " image_name{}label_name\\n".format(separator))
+                    image_path = os.path.join(self.data_dir, items[0])
+                    grt_path = None
+                else:
+                    image_path = os.path.join(self.data_dir, items[0])
+                    grt_path = os.path.join(self.data_dir, items[1])
+                self.file_list.append([image_path, grt_path])
+
+    def __getitem__(self, idx):
+        image_path, grt_path = self.file_list[idx]
+        im, im_info, label = self.transforms(im=image_path, label=grt_path)
+        if self.mode == 'train':
+            return im, label
+        elif self.mode == 'eval':
+            return im, label
+        if self.mode == 'test':
+            return im, im_info, image_path
+
+    def __len__(self):
+        return len(self.file_list)

dygraph/datasets/optic_disc_seg.py

@@ -14,8 +14,7 @@
 
 import os
 
-from paddle.fluid.io import Dataset
-
+from .dataset import Dataset
 from utils.download import download_file_and_uncompress
 
 DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset')
@@ -70,16 +69,3 @@ class OpticDiscSeg(Dataset):
                     image_path = os.path.join(self.data_dir, items[0])
                     grt_path = os.path.join(self.data_dir, items[1])
                 self.file_list.append([image_path, grt_path])
-
-    def __getitem__(self, idx):
-        image_path, grt_path = self.file_list[idx]
-        im, im_info, label = self.transforms(im=image_path, label=grt_path)
-        if self.mode == 'train':
-            return im, label
-        elif self.mode == 'eval':
-            return im, label
-        if self.mode == 'test':
-            return im, im_info, image_path
-
-    def __len__(self):
-        return len(self.file_list)

dygraph/infer.py

@@ -37,12 +37,8 @@ def parse_args():
     parser.add_argument(
         '--model_name',
         dest='model_name',
-        help=
-        'Model type for testing, which is one of ("UNet", "HRNet_W18_Small_V1", "HRNet_W18_Small_V2", '
-        '"HRNet_W18", "HRNet_W30", "HRNet_W32", "HRNet_W40", "HRNet_W44", "HRNet_W48", '
-        '"HRNet_W60", "HRNet_W64", "SE_HRNet_W18_Small_V1", "SE_HRNet_W18_Small_V2", "SE_HRNet_W18", '
-        '"SE_HRNet_W30", "SE_HRNet_W32", "SE_HRNet_W40","SE_HRNet_W44", "SE_HRNet_W48", '
-        '"SE_HRNet_W60", "SE_HRNet_W64")',
+        help='Model type for testing, which is one of {}'.format(
+            str(list(MODELS.keys()))),
         type=str,
         default='UNet')
 

dygraph/models/hrnet.py

@@ -18,7 +18,11 @@ import paddle
 import paddle.fluid as fluid
 from paddle.fluid.param_attr import ParamAttr
 from paddle.fluid.layer_helper import LayerHelper
-from paddle.fluid.dygraph.nn import Conv2D, Pool2D, BatchNorm, Linear
+from paddle.fluid.dygraph.nn import Conv2D, Pool2D, Linear
+try:
+    from paddle.fluid.dygraph import SyncBatchNorm as BatchNorm
+except:
+    from paddle.fluid.dygraph import BatchNorm
 
 __all__ = [
     "HRNet_W18_Small_V1", "HRNet_W18_Small_V2", "HRNet_W18", "HRNet_W30",

dygraph/models/unet.py

@@ -13,7 +13,11 @@
 # limitations under the License.
 
 import paddle.fluid as fluid
-from paddle.fluid.dygraph import Conv2D, BatchNorm, Pool2D
+from paddle.fluid.dygraph import Conv2D, Pool2D
+try:
+    from paddle.fluid.dygraph import SyncBatchNorm as BatchNorm
+except:
+    from paddle.fluid.dygraph import BatchNorm
 
 
 class UNet(fluid.dygraph.Layer):

dygraph/train.py

@@ -38,12 +38,8 @@ def parse_args():
     parser.add_argument(
         '--model_name',
         dest='model_name',
-        help=
-        'Model type for training, which is one of ("UNet", "HRNet_W18_Small_V1", "HRNet_W18_Small_V2", '
-        '"HRNet_W18", "HRNet_W30", "HRNet_W32", "HRNet_W40", "HRNet_W44", "HRNet_W48", '
-        '"HRNet_W60", "HRNet_W64", "SE_HRNet_W18_Small_V1", "SE_HRNet_W18_Small_V2", "SE_HRNet_W18", '
-        '"SE_HRNet_W30", "SE_HRNet_W32", "SE_HRNet_W40","SE_HRNet_W44", "SE_HRNet_W48", '
-        '"SE_HRNet_W60", "SE_HRNet_W64")',
+        help='Model type for training, which is one of {}'.format(
+            str(list(MODELS.keys()))),
         type=str,
         default='UNet')
 
@@ -186,6 +182,7 @@ def train(model,
     total_steps = steps_per_epoch * (num_epochs - start_epoch)
     num_steps = 0
     best_mean_iou = -1.0
+    best_model_epoch = -1
     for epoch in range(start_epoch, num_epochs):
         for step, data in enumerate(loader):
             images = data[0]
@@ -245,9 +242,9 @@ def train(model,
                     best_model_dir = os.path.join(save_dir, "best_model")
                     fluid.save_dygraph(model.state_dict(),
                                        os.path.join(best_model_dir, 'model'))
-                    logging.info(
-                        'Current evaluated best model in eval_dataset is epoch_{}, miou={:4f}'
-                        .format(best_model_epoch, best_mean_iou))
+                logging.info(
+                    'Current evaluated best model in eval_dataset is epoch_{}, miou={:4f}'
+                    .format(best_model_epoch, best_mean_iou))
 
                 if use_vdl:
                     log_writer.add_scalar('Evaluate/mean_iou', mean_iou,

dygraph/transforms/transforms.py

+# coding: utf8
 # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");

dygraph/utils/utils.py

@@ -52,7 +52,11 @@ def load_pretrained_model(model, pretrained_model):
         logging.info('Load pretrained model from {}'.format(pretrained_model))
         if os.path.exists(pretrained_model):
             ckpt_path = os.path.join(pretrained_model, 'model')
-            para_state_dict, _ = fluid.load_dygraph(ckpt_path)
+            try:
+                para_state_dict, _ = fluid.load_dygraph(ckpt_path)
+            except:
+                para_state_dict = fluid.load_program_state(pretrained_model)
+
             model_state_dict = model.state_dict()
             keys = model_state_dict.keys()
             num_params_loaded = 0

dygraph/val.py

@@ -39,12 +39,8 @@ def parse_args():
     parser.add_argument(
         '--model_name',
         dest='model_name',
-        help=
-        'Model type for evaluation, which is one of ("UNet", "HRNet_W18_Small_V1", "HRNet_W18_Small_V2", '
-        '"HRNet_W18", "HRNet_W30", "HRNet_W32", "HRNet_W40", "HRNet_W44", "HRNet_W48", '
-        '"HRNet_W60", "HRNet_W64", "SE_HRNet_W18_Small_V1", "SE_HRNet_W18_Small_V2", "SE_HRNet_W18", '
-        '"SE_HRNet_W30", "SE_HRNet_W32", "SE_HRNet_W40","SE_HRNet_W44", "SE_HRNet_W48", '
-        '"SE_HRNet_W60", "SE_HRNet_W64")',
+        help='Model type for evaluation, which is one of {}'.format(
+            str(list(MODELS.keys()))),
         type=str,
         default='UNet')