recursive dataset stuff

3 files changed, 95 insertions, 2 deletions

diff --git a/data/custom_dataset_data_loader.py b/data/custom_dataset_data_loader.py
index 0b98254..89ae554 100755
--- a/data/custom_dataset_data_loader.py
+++ b/data/custom_dataset_data_loader.py
@@ -4,8 +4,15 @@ from data.base_data_loader import BaseDataLoader
 
 def CreateDataset(opt):
     dataset = None
-    from data.aligned_dataset import AlignedDataset
-    dataset = AlignedDataset()
+    if opt.phase == 'recursive':
+        from data.recursive_dataset import RecursiveDataset
+        dataset = RecursiveDataset()
+    elif opt.phase == 'sequence':
+        from data.sequence_dataset import SequenceDataset
+        dataset = SequenceDataset()
+    else:
+        from data.aligned_dataset import AlignedDataset
+        dataset = AlignedDataset()
 
     print("dataset [%s] was created" % (dataset.name()))
     dataset.initialize(opt)
diff --git a/data/recursive_dataset.py b/data/recursive_dataset.py
new file mode 100644
index 0000000..14ce906
--- /dev/null
+++ b/data/recursive_dataset.py
@@ -0,0 +1,44 @@
+### Copyright (C) 2017 NVIDIA Corporation. All rights reserved. 
+### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
+import os.path
+from data.base_dataset import BaseDataset, get_params, get_transform, normalize
+from data.image_folder import make_dataset
+from PIL import Image
+
+class RecursiveDataset(BaseDataset):
+    def initialize(self, opt):
+        self.opt = opt
+        self.root = opt.dataroot    
+
+        ### input A (label maps)
+        self.dir_A = opt.dataroot
+        self.A_paths = sorted(make_dataset(self.dir_A))
+
+        self.dataset_size = len(self.A_paths) 
+      
+    def __getitem__(self, index):
+        ### input A (label maps)
+        A_path = os.path.join(self.opt.dataroot, "frame_{:05d}.png".format(index))
+        if not os.path.exists(A_path):
+            # print()
+            while not os.path.exists(A_path):
+                # print('sleeping for {}'.format(self.opt.poll_delay))
+                time.sleep(self.opt.poll_delay)
+        # print("got {}".format(A_path))
+        A = Image.open(A_path)
+        params = get_params(self.opt, A.size)
+        transform_A = get_transform(self.opt, params)
+        A_tensor = transform_A(A.convert('RGB'))
+
+        B_tensor = inst_tensor = feat_tensor = 0
+
+        input_dict = {'label': A_tensor, 'inst': inst_tensor, 'image': B_tensor, 
+                      'feat': feat_tensor, 'path': A_path}
+
+        return input_dict
+
+    def __len__(self):
+        return len(self.A_paths)
+
+    def name(self):
+        return 'RecursiveDataset'
\ No newline at end of file
diff --git a/data/sequence_dataset.py b/data/sequence_dataset.py
new file mode 100644
index 0000000..3eaa12b
--- /dev/null
+++ b/data/sequence_dataset.py
@@ -0,0 +1,42 @@
+### Copyright (C) 2017 NVIDIA Corporation. All rights reserved. 
+### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
+import os.path
+from data.base_dataset import BaseDataset, get_params, get_transform, normalize
+from data.image_folder import make_dataset
+from PIL import Image
+
+class SequenceDataset(BaseDataset):
+    def initialize(self, opt):
+        self.opt = opt
+        self.root = opt.dataroot    
+
+        ### input A (label maps)
+        self.dir_A = opt.dataroot
+        self.A_paths = sorted(make_dataset(self.dir_A))
+
+        self.dataset_size = len(self.A_paths) 
+      
+    def __getitem__(self, index):        
+        ### input A (label maps)
+        A_path = self.A_paths[index]              
+        A = Image.open(A_path)        
+        params = get_params(self.opt, A.size)
+        if self.opt.label_nc == 0:
+            transform_A = get_transform(self.opt, params)
+            A_tensor = transform_A(A.convert('RGB'))
+        else:
+            transform_A = get_transform(self.opt, params, method=Image.NEAREST, normalize=False)
+            A_tensor = transform_A(A) * 255.0
+
+        B_tensor = inst_tensor = feat_tensor = 0
+
+        input_dict = {'label': A_tensor, 'inst': inst_tensor, 'image': B_tensor, 
+                      'feat': feat_tensor, 'path': A_path}
+
+        return input_dict
+
+    def __len__(self):
+        return len(self.A_paths)
+
+    def name(self):
+        return 'SequenceDataset'
\ No newline at end of file