Change Config API

- deprecate `datasets_from_config()`
- Config.load_datasets() instead
- Config.from_dict()

README.md

@@ -60,7 +60,7 @@ Find full guides at [bioimageloader-docs:User Guides]
     Load DSB2018 and [_Triple Negative Breast Cancer (TNBC)_](https://ieeexplore.ieee.org/document/8438559)
 
     ```python
-    from bioimageloader import datasets_from_config, ConcatDataset
+    from bioimageloader import Config, ConcatDataset
     from bioimageloader.collections import DSB2018, TNBC
     import albumentations as A
 
@@ -73,7 +73,8 @@ Find full guides at [bioimageloader-docs:User Guides]
         'DSB2018': { 'root_dir': 'path/to/root_dir' },
         'TNBC'   : { 'root_dir': 'path/to/root_dir' },
     }
-    datasets = datasets_from_config(cfg, transforms=transforms)
+    config = Config.from_dict(cfg)
+    datasets = config.load_datasets(transforms=transforms)
     cat = ConcatDataset(datasets)
     for meow in cat:
         image = meow['image']

bioimageloader/__init__.py

@@ -4,11 +4,10 @@
 """
 
 from .batch import BatchDataloader, ConcatDataset
-from .config import Config, datasets_from_config
+from .config import Config
 
 __all__ = [
     'BatchDataloader',
     'ConcatDataset',
     'Config',
-    'datasets_from_config',
 ]

bioimageloader/config.py

@@ -17,38 +17,47 @@ class Config(dict):
     """
     def __init__(self, filename):
         self.filename = filename
-        cfg = Config.read_yaml(filename)
-        for k, i in cfg.items():
-            self[k] = i
+        cfg = self._read_yaml()
+        for k, v in cfg.items():
+            self[k] = v
 
-    @staticmethod
-    def read_yaml(filename: str) -> dict:
-        with open(filename, 'r') as f:
+    def _read_yaml(self) -> dict:
+        with open(self.filename, 'r') as f:
             cfg = yaml.safe_load(f)
         return cfg
 
-
-def datasets_from_config(
-    config: Config,
-    transforms: Optional[Union[albumentations.Compose, Dict[str, albumentations.Compose]]] = None,
-) -> List[Dataset]:
-    """Load multiple datasets from a yaml file
-
-    Parameters
-    ----------
-    config : configuration object
-        Config instance that contains acronyms and arguments to initialize
-        each dataset
-    transforms : albumentations.Compose or dictionary, optional
-        Either apply a single composed transformations for every datasets or
-        pass a dictionary that defines transformations for each dataset with
-        keys being the acronyms of datsets.
-
-    """
-    datasets: List[Dataset] = []
-    for dataset, kwargs in config.items():
-        if isinstance(transforms, dict):
-            exec(f'datasets.append({dataset}(transforms=transforms[dataset], **kwargs))')
-        else:
-            exec(f'datasets.append({dataset}(transforms=transforms, **kwargs))')
-    return datasets
+    @staticmethod
+    def from_dict(d: dict):
+        return _Config(d)
+
+    def load_datasets(
+        self,
+        transforms: Optional[Union[albumentations.Compose, Dict[str, albumentations.Compose]]] = None,
+    ) -> List[Dataset]:
+        """Load multiple datasets from a yaml file
+
+        Parameters
+        ----------
+        config : configuration object
+            Config instance that contains acronyms and arguments to initialize
+            each dataset
+        transforms : albumentations.Compose or dictionary, optional
+            Either apply a single composed transformations for every datasets or
+            pass a dictionary that defines transformations for each dataset with
+            keys being the acronyms of datsets.
+
+        """
+        datasets: List[Dataset] = []
+        for dataset, kwargs in self.items():
+            if isinstance(transforms, dict):
+                exec(f'datasets.append({dataset}(transforms=transforms[dataset], **kwargs))')
+            else:
+                exec(f'datasets.append({dataset}(transforms=transforms, **kwargs))')
+        return datasets
+
+
+class _Config(Config):
+    """Config.from_dict()"""
+    def __init__(self, d: dict):
+        for k, v in d.items():
+            self[k] = v

bioimageloader/transforms.py

@@ -23,14 +23,15 @@ class HWCToCHW(albumentations.ImageOnlyTransform):
     Examples
     --------
     >>> import albumentations as A
-    >>> from bioimageloader import Config, datasets_from_config
+    >>> from bioimageloader import Config
 
     >>> cfg = Config('config.yml')
     >>> transforms = A.Compose([
             HWCToCHW(),
         ])
-    >>> dataset = datasets_from_config(cfg, transforms=transforms)
-    >>> data = dataset[0]
+    >>> datasets = cfg.load_datasets(transforms=transforms)
+    >>> dset = datasets[0]  # select only the first dataset
+    >>> data = dset[0]  # select only the first image
     >>> print(data['image'].shape)
     (3, H, W)
 
@@ -68,15 +69,16 @@ class SqueezeGrayImageCHW(albumentations.ImageOnlyTransform):
     Examples
     --------
     >>> import albumentations as A
-    >>> from bioimageloader import Config, datasets_from_config
+    >>> from bioimageloader import Config
 
     >>> cfg = Config('config.yml')
     >>> transforms = A.Compose([
             HWCToCHW(),
             SqueezeGrayImageCHW(),
         ])
-    >>> dataset = datasets_from_config(cfg, transforms=transforms)
-    >>> data = dataset[0]
+    >>> datasets = cfg.load_datasets(transforms=transforms)
+    >>> dset = datasets[0]  # select only the first dataset
+    >>> data = dset[0]  # select only the first image
     >>> print(data['image'].shape)
     (1, H, W)
 
@@ -87,8 +89,9 @@ class SqueezeGrayImageCHW(albumentations.ImageOnlyTransform):
             HWCToCHW(),
             SqueezeGrayImageCHW(keep_dim=False),  # drop channel axis
         ])
-    >>> dataset = datasets_from_config(cfg, transforms=transforms)
-    >>> data = dataset[0]
+    >>> datasets = cfg.load_datasets(transforms=transforms)
+    >>> dset = datasets[0]  # select only the first dataset
+    >>> data = dset[0]  # select only the first image
     >>> print(data['image'].shape)
     (H, W)
 
@@ -139,14 +142,15 @@ class SqueezeGrayImageHWC(albumentations.ImageOnlyTransform):
     Examples
     --------
     >>> import albumentations as A
-    >>> from bioimageloader import Config, datasets_from_config
+    >>> from bioimageloader import Config
 
     >>> cfg = Config('config.yml')
     >>> transforms = A.Compose([
             SqueezeGrayImageHWC(),
         ])
-    >>> dataset = datasets_from_config(cfg, transforms=transforms)
-    >>> data = dataset[0]
+    >>> datasets = cfg.load_datasets(transforms=transforms)
+    >>> dset = datasets[0]  # select only the first dataset
+    >>> data = dset[0]  # select only the first image
     >>> print(data['image'].shape)
     (H, W)