feat: add Caltech101 Silouettes dataset (#1158)

* feat: add Caltech101 dataset

* feat: rename as Caltech101Silhouettes and split in train, val and test

tensorpack/dataflow/dataset/__init__.py

@@ -10,6 +10,7 @@ if STATICA_HACK:
     from .ilsvrc import *
     from .mnist import *
     from .svhn import *
+    from .caltech101 import *
 
 from pkgutil import iter_modules
 import os

tensorpack/dataflow/dataset/caltech101.py

+# -*- coding: utf-8 -*-
+# File: caltech101.py
+
+
+import os
+from six.moves import range
+
+from ...utils import logger
+from ...utils.fs import download, get_dataset_path
+from ..base import RNGDataFlow
+
+__all__ = ["Caltech101Silhouettes"]
+
+
+def maybe_download(url, work_directory):
+    """Download the data from Marlin's website, unless it's already here."""
+    filename = url.split("/")[-1]
+    filepath = os.path.join(work_directory, filename)
+    if not os.path.exists(filepath):
+        logger.info("Downloading to {}...".format(filepath))
+        download(url, work_directory)
+    return filepath
+
+
+class Caltech101Silhouettes(RNGDataFlow):
+    """
+    Produces [image, label] in Caltech101 Silhouettes dataset,
+    image is 28x28 in the range [0,1], label is an int in the range [0,100].
+    """
+
+    _DIR_NAME = "caltech101_data"
+    _SOURCE_URL = "https://people.cs.umass.edu/~marlin/data/"
+
+    def __init__(self, name, shuffle=True, dir=None):
+        """
+        Args:
+            name (str): 'train', 'test', 'val'
+            shuffle (bool): shuffle the dataset
+        """
+        if dir is None:
+            dir = get_dataset_path(self._DIR_NAME)
+        assert name in ['train', 'test', 'val']
+        self.name = name
+        self.shuffle = shuffle
+
+        def get_images_and_labels(data_file):
+            f = maybe_download(self._SOURCE_URL + data_file, dir)
+            data = scipy.io.loadmat(f)
+            return data
+
+        self.data = get_images_and_labels("caltech101_silhouettes_28_split1.mat")
+
+        if self.train_or_test == "train":
+            self.images = self.data["train_data"].reshape((4100, 28, 28))
+            self.labels = self.data["train_labels"].ravel() - 1
+        elif self.name == "test":
+            self.images = self.data["test_data"].reshape((2307, 28, 28))
+            self.labels = self.data["test_labels"].ravel() - 1
+        else:
+            self.images = self.data["val_data"].reshape((2264, 28, 28))
+            self.labels = self.data["val_labels"].ravel() - 1
+
+    def __len__(self):
+        return self.images.shape[0]
+
+    def __iter__(self):
+        idxs = list(range(self.__len__()))
+        if self.shuffle:
+            self.rng.shuffle(idxs)
+        for k in idxs:
+            img = self.images[k]
+            label = self.labels[k]
+            yield [img, label]
+
+
+try:
+    import scipy.io
+except ImportError:
+    from ...utils.develop import create_dummy_class
+    Caltech101Silhouettes = create_dummy_class('Caltech101Silhouettes', 'scipy.io') # noqa
+
+
+if __name__ == "__main__":
+    ds = Caltech101Silhouettes("train")
+    ds.reset_state()
+    for (img, label) in ds:
+        from IPython import embed
+
+        embed()
+        break