Allow using class_map functionality w/ IterableDataset (TFDS/WDS) to remap class labels

timm/data/dataset.py

@@ -88,6 +88,7 @@ class IterableImageDataset(data.IterableDataset):
             root,
             reader=None,
             split='train',
+            class_map=None,
             is_training=False,
             batch_size=None,
             seed=42,
@@ -102,6 +103,7 @@ class IterableImageDataset(data.IterableDataset):
                 reader,
                 root=root,
                 split=split,
+                class_map=class_map,
                 is_training=is_training,
                 batch_size=batch_size,
                 seed=seed,

timm/data/dataset_factory.py

@@ -157,6 +157,7 @@ def create_dataset(
             root,
             reader=name,
             split=split,
+            class_map=class_map,
             is_training=is_training,
             download=download,
             batch_size=batch_size,
@@ -169,6 +170,7 @@ def create_dataset(
             root,
             reader=name,
             split=split,
+            class_map=class_map,
             is_training=is_training,
             batch_size=batch_size,
             repeats=repeats,

timm/data/readers/reader_tfds.py

@@ -34,6 +34,7 @@ except ImportError as e:
     print("Please install tensorflow_datasets package `pip install tensorflow-datasets`.")
     exit(1)
 
+from .class_map import load_class_map
 from .reader import Reader
 from .shared_count import SharedCount
 
@@ -94,6 +95,7 @@ class ReaderTfds(Reader):
             root,
             name,
             split='train',
+            class_map=None,
             is_training=False,
             batch_size=None,
             download=False,
@@ -151,7 +153,12 @@ class ReaderTfds(Reader):
         # NOTE: the tfds command line app can be used download & prepare datasets if you don't enable download flag
         if download:
             self.builder.download_and_prepare()
-        self.class_to_idx = get_class_labels(self.builder.info) if self.target_name == 'label' else {}
+        self.remap_class = False
+        if class_map:
+            self.class_to_idx = load_class_map(class_map)
+            self.remap_class = True
+        else:
+            self.class_to_idx = get_class_labels(self.builder.info) if self.target_name == 'label' else {}
         self.split_info = self.builder.info.splits[split]
         self.num_samples = self.split_info.num_examples
 
@@ -299,6 +306,8 @@ class ReaderTfds(Reader):
             target_data = sample[self.target_name]
             if self.target_img_mode:
                 target_data = Image.fromarray(target_data, mode=self.target_img_mode)
+            elif self.remap_class:
+                target_data = self.class_to_idx[target_data]
             yield input_data, target_data
             sample_count += 1
             if self.is_training and sample_count >= target_sample_count:

timm/data/readers/reader_wds.py

@@ -29,6 +29,7 @@ except ImportError:
     wds = None
     expand_urls = None
 
+from .class_map import load_class_map
 from .reader import Reader
 from .shared_count import SharedCount
 
@@ -42,13 +43,13 @@ def _load_info(root, basename='info'):
     info_yaml = os.path.join(root, basename + '.yaml')
     err_str = ''
     try:
-        with wds.gopen.gopen(info_json) as f:
+        with wds.gopen(info_json) as f:
             info_dict = json.load(f)
         return info_dict
     except Exception as e:
         err_str = str(e)
     try:
-        with wds.gopen.gopen(info_yaml) as f:
+        with wds.gopen(info_yaml) as f:
             info_dict = yaml.safe_load(f)
         return info_dict
     except Exception:
@@ -110,8 +111,8 @@ def _parse_split_info(split: str, info: Dict):
                 filenames=split_filenames,
             )
     else:
-        if split not in info['splits']:
-            raise RuntimeError(f"split {split} not found in info ({info['splits'].keys()})")
+        if 'splits' not in info or split not in info['splits']:
+            raise RuntimeError(f"split {split} not found in info ({info.get('splits', {}).keys()})")
         split = split
         split_info = info['splits'][split]
         split_info = _info_convert(split_info)
@@ -290,6 +291,7 @@ class ReaderWds(Reader):
             batch_size=None,
             repeats=0,
             seed=42,
+            class_map=None,
             input_name='jpg',
             input_image='RGB',
             target_name='cls',
@@ -320,6 +322,12 @@ class ReaderWds(Reader):
         self.num_samples = self.split_info.num_samples
         if not self.num_samples:
             raise RuntimeError(f'Invalid split definition, no samples found.')
+        self.remap_class = False
+        if class_map:
+            self.class_to_idx = load_class_map(class_map)
+            self.remap_class = True
+        else:
+            self.class_to_idx = {}
 
         # Distributed world state
         self.dist_rank = 0
@@ -431,7 +439,10 @@ class ReaderWds(Reader):
         i = 0
         # _logger.info(f'start {i}, {self.worker_id}')  # FIXME temporary debug
         for sample in ds:
-            yield sample[self.image_key], sample[self.target_key]
+            target = sample[self.target_key]
+            if self.remap_class:
+                target = self.class_to_idx[target]
+            yield sample[self.image_key], target
             i += 1
         # _logger.info(f'end {i}, {self.worker_id}')  # FIXME temporary debug