From bcec7cc1b3ac7d28793a51ea547e097ada4f113a Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Tue, 12 Dec 2017 00:29:13 +0900
Subject: [PATCH 1/9] Add FLIC dataset

---
 chainercv/datasets/__init__.py                |   2 +
 chainercv/datasets/flic/__init__.py           |   0
 .../datasets/flic/flic_keypoint_dataset.py    | 128 ++++++++++++++++++
 chainercv/datasets/flic/flic_utils.py         |  68 ++++++++++
 4 files changed, 198 insertions(+)
 create mode 100644 chainercv/datasets/flic/__init__.py
 create mode 100644 chainercv/datasets/flic/flic_keypoint_dataset.py
 create mode 100644 chainercv/datasets/flic/flic_utils.py

diff --git a/chainercv/datasets/__init__.py b/chainercv/datasets/__init__.py
index fc0a0a271f..32d35ae741 100644
--- a/chainercv/datasets/__init__.py
+++ b/chainercv/datasets/__init__.py
@@ -15,6 +15,8 @@
 from chainercv.datasets.cub.cub_utils import cub_label_names  # NOQA
 from chainercv.datasets.directory_parsing_label_dataset import directory_parsing_label_names  # NOQA
 from chainercv.datasets.directory_parsing_label_dataset import DirectoryParsingLabelDataset  # NOQA
+from chainercv.datasets.flic.flic_keypoint_dataset import FLICKeypointDataset  # NOQA
+from chainercv.datasets.flic.flic_utils import flic_joint_label_names  # NOQA
 from chainercv.datasets.online_products.online_products_dataset import online_products_super_label_names  # NOQA
 from chainercv.datasets.online_products.online_products_dataset import OnlineProductsDataset  # NOQA
 from chainercv.datasets.transform_dataset import TransformDataset  # NOQA
diff --git a/chainercv/datasets/flic/__init__.py b/chainercv/datasets/flic/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/chainercv/datasets/flic/flic_keypoint_dataset.py b/chainercv/datasets/flic/flic_keypoint_dataset.py
new file mode 100644
index 0000000000..c63521581a
--- /dev/null
+++ b/chainercv/datasets/flic/flic_keypoint_dataset.py
@@ -0,0 +1,128 @@
+import collections
+import glob
+import os
+
+import numpy as np
+
+import chainer
+from chainercv import utils
+from chainercv.datasets.flic import flic_utils
+
+try:
+    from scipy.io import loadmat
+    _scipy_available = True
+except (ImportError, TypeError):
+    _scipy_available = False
+
+
+class FLICKeypointDataset(chainer.dataset.DatasetMixin):
+
+    """`Frames Labaled in Cinema (FLIC)`_ dataset  with annotated keypoints.
+
+    .. _`Frames Labaled in Cinema (FLIC)`:
+        https://bensapp.github.io/flic-dataset.html
+
+    An index corresponds to each image.
+
+    When queried by an index, this dataset returns the corresponding
+    :obj:`img, keypoint`, which is a tuple of an image and keypoints
+    that indicates visible keypoints in the image.
+    The data type of the two elements are :obj:`float32, float32`.
+
+    The keypoints are packed into a two dimensional array of shape
+    :math:`(K, 2)`, where :math:`K` is the number of keypoints.
+    Note that :math:`K=29` in FLIC dataset. Also note that not all
+    keypoints are visible in an image. When a keypoint is not visible,
+    the values stored for that keypoint are :obj:`~numpy.nan`. The second axis
+    corresponds to the :math:`y` and :math:`x` coordinates of the
+    keypoints in the image.
+
+    The torso bounding box is a one-dimensional array of shape :math:`(4,)`.
+    The elements of the bounding box corresponds to
+    :math:`(y_{min}, x_{min}, y_{max}, x_{max})`, where the four attributes are
+    coordinates of the top left and the bottom right vertices.
+    This information can optionally be retrieved from the dataset
+    by setting :obj:`return_torsobox = True`.
+
+    Args:
+        data_dir (string): Path to the root of the training data. If this is
+            :obj:`auto`, this class will automatically download data for you
+            under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/cub`.
+        split ({'train', 'test'}): Select from dataset splits used in
+            the FLIC dataset.
+        return_torsobox (bool): If :obj:`True`, this returns a bounding box
+            around the torso. The default value is :obj:`False`.
+
+    """
+
+    def __init__(self, data_dir='auto', split='train', return_torsobox=False):
+        super(FLICKeypointDataset, self).__init__()
+        if split not in ['train', 'test']:
+            raise ValueError(
+                '\'split\' argment should be eighter \'train\' or \'test\'.')
+
+        if not _scipy_available:
+            raise ImportError(
+                'scipy is needed to extract labales from the .mat file.'
+                'Please install scipy:\n\n'
+                '\t$pip install scipy\n\n')
+
+        if data_dir == 'auto':
+            data_dir = flic_utils.get_flic()
+
+        img_paths = {os.path.basename(fn): fn for fn in glob.glob(
+            os.path.join(data_dir, 'FLIC-full', 'images', '*.jpg'))}
+
+        label_keys = [
+            'poselet_hit_idx',
+            'moviename',
+            'coords',
+            'filepath',
+            'imgdims',
+            'currframe',
+            'torsobox',
+            'istrain',
+            'istest',
+            'isbad',
+            'isunchecked',
+        ]
+        labels = loadmat(os.path.join(data_dir, 'FLIC-full', 'examples.mat'))
+
+        self.img_paths = []
+        self.keypoints = []
+        self.torsoboxes = []
+        self.return_torsobox = return_torsobox
+
+        for label in labels['examples'][0]:
+            label = {label_keys[i]: val for i, val in enumerate(label)}
+            if int(label['isbad']) == 1 or int(label['isunchecked']) == 1:
+                continue
+            if ((split == 'train' and int(label['istrain']) == 0)
+                    or (split == 'test' and int(label['istest']) == 0)):
+                continue
+
+            self.img_paths.append(img_paths[label['filepath'][0]])
+            self.keypoints.append(label['coords'].T[:, ::-1])
+            if return_torsobox:
+                self.torsoboxes.append(label['torsobox'][0, [1, 0, 3, 2]])
+
+    def get_example(self, i):
+        """Returns the i-th example.
+
+        Args:
+            i (int): The index of the example.
+
+        Returns:
+            tuple of an image and keypoints.
+            The image is in CHW format and its color channel is ordered in
+            RGB.
+            If :obj:`return_torsobox = True`,
+            a bounding box is appended to the returned value.
+
+        """
+        img = utils.read_image(self.img_paths[i])
+        keypoint = np.array(self.keypoints[i], dtype=np.float32)
+        if self.return_torsobox:
+            return img, keypoint, self.torsoboxes[i]
+        else:
+            return img, keypoint
diff --git a/chainercv/datasets/flic/flic_utils.py b/chainercv/datasets/flic/flic_utils.py
new file mode 100644
index 0000000000..8d62edd5dc
--- /dev/null
+++ b/chainercv/datasets/flic/flic_utils.py
@@ -0,0 +1,68 @@
+import os
+import shutil
+
+from chainer.dataset import download
+from chainercv import utils
+
+root = 'pfnet/chainercv/flic'
+
+urls = [
+    'http://vision.grasp.upenn.edu/video/FLIC-full.zip',
+
+    'http://cims.nyu.edu/~tompson/data/tr_plus_indices.mat',
+
+]
+
+flic_joint_label_names = [
+    'lsho',
+    'lelb',
+    'lwri',
+    'rsho',
+    'relb',
+    'rwri',
+    'lhip',
+    'lkne',
+    'lank',
+    'rhip',
+    'rkne',
+    'rank',
+    'leye',
+    'reye',
+    'lear',
+    'rear',
+    'nose',
+    'msho',
+    'mhip',
+    'mear',
+    'mtorso',
+    'mluarm',
+    'mruarm',
+    'mllarm',
+    'mrlarm',
+    'mluleg',
+    'mruleg',
+    'mllleg',
+    'mrlleg'
+]
+
+
+def get_flic():
+    data_root = download.get_dataset_directory(root)
+
+    if not os.path.exists(os.path.join(data_root,
+                                       'FLIC-full')):
+        download_file_path = utils.cached_download(urls[0])
+        ext = os.path.splitext(urls[0])[1]
+        utils.extractall(download_file_path,
+                         data_root,
+                         ext)
+
+    if not os.path.exists(os.path.join(data_root,
+                                       'tr_plus_indices.mat')):
+        download_file_path = utils.cached_download(urls[1])
+        shutil.copy(download_file_path,
+
+                    os.path.join(data_root,
+                                 'tr_plus_indices.mat'))
+
+    return data_root

From c72a0ac600aefe899148ae8c3076f54f96c0241f Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Tue, 12 Dec 2017 00:33:14 +0900
Subject: [PATCH 2/9] Add __len__

---
 chainercv/datasets/flic/flic_keypoint_dataset.py | 3 +++
 chainercv/datasets/flic/flic_utils.py            | 8 --------
 2 files changed, 3 insertions(+), 8 deletions(-)

diff --git a/chainercv/datasets/flic/flic_keypoint_dataset.py b/chainercv/datasets/flic/flic_keypoint_dataset.py
index c63521581a..0a0ff59599 100644
--- a/chainercv/datasets/flic/flic_keypoint_dataset.py
+++ b/chainercv/datasets/flic/flic_keypoint_dataset.py
@@ -106,6 +106,9 @@ def __init__(self, data_dir='auto', split='train', return_torsobox=False):
             if return_torsobox:
                 self.torsoboxes.append(label['torsobox'][0, [1, 0, 3, 2]])
 
+    def __len__(self):
+        return len(self.img_paths)
+
     def get_example(self, i):
         """Returns the i-th example.
 
diff --git a/chainercv/datasets/flic/flic_utils.py b/chainercv/datasets/flic/flic_utils.py
index 8d62edd5dc..fbce1c50c0 100644
--- a/chainercv/datasets/flic/flic_utils.py
+++ b/chainercv/datasets/flic/flic_utils.py
@@ -57,12 +57,4 @@ def get_flic():
                          data_root,
                          ext)
 
-    if not os.path.exists(os.path.join(data_root,
-                                       'tr_plus_indices.mat')):
-        download_file_path = utils.cached_download(urls[1])
-        shutil.copy(download_file_path,
-
-                    os.path.join(data_root,
-                                 'tr_plus_indices.mat'))
-
     return data_root

From 0a9d46bccdf66a81b8e9786194f064e767595aa5 Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Tue, 12 Dec 2017 00:44:20 +0900
Subject: [PATCH 3/9] Add skip_bad and skip_unchecked arguments

---
 chainercv/datasets/flic/flic_keypoint_dataset.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/chainercv/datasets/flic/flic_keypoint_dataset.py b/chainercv/datasets/flic/flic_keypoint_dataset.py
index 0a0ff59599..ba9018dd89 100644
--- a/chainercv/datasets/flic/flic_keypoint_dataset.py
+++ b/chainercv/datasets/flic/flic_keypoint_dataset.py
@@ -52,10 +52,15 @@ class FLICKeypointDataset(chainer.dataset.DatasetMixin):
             the FLIC dataset.
         return_torsobox (bool): If :obj:`True`, this returns a bounding box
             around the torso. The default value is :obj:`False`.
+        skip_bad (bool): If :obj:`True`, the data which have :obj:`isbad = 1`
+            will be ignored. The default is :obj:`True`.
+        skip_unchecked (bool): If :obj:`True`, the data which have
+            :obj:`isunchecked = 1` will be ignored. The default is :obj:`True`.
 
     """
 
-    def __init__(self, data_dir='auto', split='train', return_torsobox=False):
+    def __init__(self, data_dir='auto', split='train', return_torsobox=False,
+                 skip_bad=True, skip_unchecked=True):
         super(FLICKeypointDataset, self).__init__()
         if split not in ['train', 'test']:
             raise ValueError(
@@ -95,7 +100,9 @@ def __init__(self, data_dir='auto', split='train', return_torsobox=False):
 
         for label in labels['examples'][0]:
             label = {label_keys[i]: val for i, val in enumerate(label)}
-            if int(label['isbad']) == 1 or int(label['isunchecked']) == 1:
+            if skip_bad and int(label['isbad']) == 1:
+                continue
+            if skip_unchecked and int(label['isunchecked']) == 1:
                 continue
             if ((split == 'train' and int(label['istrain']) == 0)
                     or (split == 'test' and int(label['istest']) == 0)):

From 6921c7290cea5676b262b92f70640be1c28d67fa Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Tue, 12 Dec 2017 22:39:31 +0900
Subject: [PATCH 4/9] Update flic_utils.py

---
 chainercv/datasets/flic/flic_utils.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/chainercv/datasets/flic/flic_utils.py b/chainercv/datasets/flic/flic_utils.py
index fbce1c50c0..0c863066f1 100644
--- a/chainercv/datasets/flic/flic_utils.py
+++ b/chainercv/datasets/flic/flic_utils.py
@@ -1,5 +1,4 @@
 import os
-import shutil
 
 from chainer.dataset import download
 from chainercv import utils

From aa6d40d6125714aa0e06744f941aaa7d4e6008cf Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Wed, 13 Dec 2017 11:32:15 +0900
Subject: [PATCH 5/9] Fix styles

---
 .../datasets/flic/flic_keypoint_dataset.py    |  9 +--
 chainercv/datasets/imagenet/__init__.py       |  0
 .../imagenet/imagenet_label_dataset.py        | 73 +++++++++++++++++++
 chainercv/datasets/imagenet/imagenet_utils.py | 22 ++++++
 chainercv/datasets/lsp/__init__.py            |  0
 .../datasets/lsp/lsp_keypoint_dataset.py      |  0
 6 files changed, 99 insertions(+), 5 deletions(-)
 create mode 100644 chainercv/datasets/imagenet/__init__.py
 create mode 100644 chainercv/datasets/imagenet/imagenet_label_dataset.py
 create mode 100644 chainercv/datasets/imagenet/imagenet_utils.py
 create mode 100644 chainercv/datasets/lsp/__init__.py
 create mode 100644 chainercv/datasets/lsp/lsp_keypoint_dataset.py

diff --git a/chainercv/datasets/flic/flic_keypoint_dataset.py b/chainercv/datasets/flic/flic_keypoint_dataset.py
index ba9018dd89..f2be12a531 100644
--- a/chainercv/datasets/flic/flic_keypoint_dataset.py
+++ b/chainercv/datasets/flic/flic_keypoint_dataset.py
@@ -1,12 +1,11 @@
-import collections
 import glob
 import os
 
 import numpy as np
 
 import chainer
-from chainercv import utils
 from chainercv.datasets.flic import flic_utils
+from chainercv import utils
 
 try:
     from scipy.io import loadmat
@@ -93,9 +92,9 @@ def __init__(self, data_dir='auto', split='train', return_torsobox=False,
         ]
         labels = loadmat(os.path.join(data_dir, 'FLIC-full', 'examples.mat'))
 
-        self.img_paths = []
-        self.keypoints = []
-        self.torsoboxes = []
+        self.img_paths = list()
+        self.keypoints = list()
+        self.torsoboxes = list()
         self.return_torsobox = return_torsobox
 
         for label in labels['examples'][0]:
diff --git a/chainercv/datasets/imagenet/__init__.py b/chainercv/datasets/imagenet/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/chainercv/datasets/imagenet/imagenet_label_dataset.py b/chainercv/datasets/imagenet/imagenet_label_dataset.py
new file mode 100644
index 0000000000..bbc75ffb06
--- /dev/null
+++ b/chainercv/datasets/imagenet/imagenet_label_dataset.py
@@ -0,0 +1,73 @@
+import numpy as np
+import os
+
+import chainer
+from chainercv import utils
+from chainercv.datasets.imagenet import imagenet_utils
+
+
+class ImageNetLabelDataset(chainer.dataset.DatasetMixin):
+
+    """`ImageNet`_ dataset with annotated class labels.
+
+    .. _`ImageNet`:
+        http://image-net.org/challenges/LSVRC/2015/download-images-3j16.php
+
+    When queried by an index, this dataset returns a corresponding
+    :obj:`img, label`, a tuple of an image and class id.
+    The image is in RGB and CHW format.
+    The class id is between 0 and 999.
+
+    Args:
+        data_dir (string): Path to the root of the training data. If this is
+            :obj:`auto`, this class will automatically download data for you
+            under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/imagenet`.
+
+    """
+
+    def __init__(self, data_dir='auto'):
+        super(ImageNetLabelDataset, self).__init__()
+        if data_dir == 'auto':
+
+
+        image_class_labels_file = os.path.join(
+            self.data_dir, 'image_class_labels.txt')
+        labels = [int(d_label.split()[1]) - 1 for
+                  d_label in open(image_class_labels_file)]
+        self._labels = np.array(labels, dtype=np.int32)
+
+    def get_example(self, i):
+        """Returns the i-th example.
+
+        Args:
+            i (int): The index of the example.
+
+        Returns:
+            tuple of an image and its label.
+            The image is in CHW format and its color channel is ordered in
+            RGB.
+            If :obj:`return_bb = True`,
+            a bounding box is appended to the returned value.
+            If :obj:`return_mask = True`,
+            a probability map is appended to the returned value.
+
+        """
+        img = utils.read_image(
+            os.path.join(self.data_dir, 'images', self.paths[i]),
+            color=True)
+        label = self._labels[i]
+
+        if not self.return_prob_map:
+            if self.return_bb:
+                return img, label, self.bbs[i]
+            else:
+                return img, label
+
+        prob_map = utils.read_image(self.prob_map_paths[i],
+                                    dtype=np.uint8, color=False)
+        prob_map = prob_map.astype(np.float32) / 255  # [0, 255] -> [0, 1]
+        prob_map = prob_map[0]  # (1, H, W) --> (H, W)
+        if self.return_bb:
+            return img, label, self.bbs[i], prob_map
+        else:
+            return img, label, prob_map
diff --git a/chainercv/datasets/imagenet/imagenet_utils.py b/chainercv/datasets/imagenet/imagenet_utils.py
new file mode 100644
index 0000000000..cdd54ed44a
--- /dev/null
+++ b/chainercv/datasets/imagenet/imagenet_utils.py
@@ -0,0 +1,22 @@
+from chainer.dataset import download
+
+from chainercv import utils
+
+
+urls = [
+    'cls_loc': 'http://image-net.org/image/ILSVRC2015/'
+               'ILSVRC2015_CLS-LOC.tar.gz',
+    'det': 'http://image-net.org/image/ILSVRC2015/ILSVRC2015_DET.tar.gz',
+    'det_test': 'http://image-net.org/image/ILSVRC2015/'
+                'ILSVRC2015_DET_test.tar.gz',
+    'det_test_new': 'http://image-net.org/image/ILSVRC2015/'
+                    'ILSVRC2015_DET_test_new.tar.gz'
+    'info': 'http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz'
+]
+
+def get_imagenet():
+    download_file_path = utils.cached_download(url)
+    ext = os.path.splitext(url)[1]
+    utils.extractall(download_file_path, data_root, ext)
+    return base_path
+
diff --git a/chainercv/datasets/lsp/__init__.py b/chainercv/datasets/lsp/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/chainercv/datasets/lsp/lsp_keypoint_dataset.py b/chainercv/datasets/lsp/lsp_keypoint_dataset.py
new file mode 100644
index 0000000000..e69de29bb2

From 708cc1d18fa3fde99979c40b5204d34ce54172c1 Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Wed, 13 Dec 2017 12:09:13 +0900
Subject: [PATCH 6/9] Remove unrelated files

---
 chainercv/datasets/imagenet/__init__.py       |  0
 .../imagenet/imagenet_label_dataset.py        | 73 -------------------
 chainercv/datasets/imagenet/imagenet_utils.py | 22 ------
 3 files changed, 95 deletions(-)
 delete mode 100644 chainercv/datasets/imagenet/__init__.py
 delete mode 100644 chainercv/datasets/imagenet/imagenet_label_dataset.py
 delete mode 100644 chainercv/datasets/imagenet/imagenet_utils.py

diff --git a/chainercv/datasets/imagenet/__init__.py b/chainercv/datasets/imagenet/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/chainercv/datasets/imagenet/imagenet_label_dataset.py b/chainercv/datasets/imagenet/imagenet_label_dataset.py
deleted file mode 100644
index bbc75ffb06..0000000000
--- a/chainercv/datasets/imagenet/imagenet_label_dataset.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import numpy as np
-import os
-
-import chainer
-from chainercv import utils
-from chainercv.datasets.imagenet import imagenet_utils
-
-
-class ImageNetLabelDataset(chainer.dataset.DatasetMixin):
-
-    """`ImageNet`_ dataset with annotated class labels.
-
-    .. _`ImageNet`:
-        http://image-net.org/challenges/LSVRC/2015/download-images-3j16.php
-
-    When queried by an index, this dataset returns a corresponding
-    :obj:`img, label`, a tuple of an image and class id.
-    The image is in RGB and CHW format.
-    The class id is between 0 and 999.
-
-    Args:
-        data_dir (string): Path to the root of the training data. If this is
-            :obj:`auto`, this class will automatically download data for you
-            under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/imagenet`.
-
-    """
-
-    def __init__(self, data_dir='auto'):
-        super(ImageNetLabelDataset, self).__init__()
-        if data_dir == 'auto':
-
-
-        image_class_labels_file = os.path.join(
-            self.data_dir, 'image_class_labels.txt')
-        labels = [int(d_label.split()[1]) - 1 for
-                  d_label in open(image_class_labels_file)]
-        self._labels = np.array(labels, dtype=np.int32)
-
-    def get_example(self, i):
-        """Returns the i-th example.
-
-        Args:
-            i (int): The index of the example.
-
-        Returns:
-            tuple of an image and its label.
-            The image is in CHW format and its color channel is ordered in
-            RGB.
-            If :obj:`return_bb = True`,
-            a bounding box is appended to the returned value.
-            If :obj:`return_mask = True`,
-            a probability map is appended to the returned value.
-
-        """
-        img = utils.read_image(
-            os.path.join(self.data_dir, 'images', self.paths[i]),
-            color=True)
-        label = self._labels[i]
-
-        if not self.return_prob_map:
-            if self.return_bb:
-                return img, label, self.bbs[i]
-            else:
-                return img, label
-
-        prob_map = utils.read_image(self.prob_map_paths[i],
-                                    dtype=np.uint8, color=False)
-        prob_map = prob_map.astype(np.float32) / 255  # [0, 255] -> [0, 1]
-        prob_map = prob_map[0]  # (1, H, W) --> (H, W)
-        if self.return_bb:
-            return img, label, self.bbs[i], prob_map
-        else:
-            return img, label, prob_map
diff --git a/chainercv/datasets/imagenet/imagenet_utils.py b/chainercv/datasets/imagenet/imagenet_utils.py
deleted file mode 100644
index cdd54ed44a..0000000000
--- a/chainercv/datasets/imagenet/imagenet_utils.py
+++ /dev/null
@@ -1,22 +0,0 @@
-from chainer.dataset import download
-
-from chainercv import utils
-
-
-urls = [
-    'cls_loc': 'http://image-net.org/image/ILSVRC2015/'
-               'ILSVRC2015_CLS-LOC.tar.gz',
-    'det': 'http://image-net.org/image/ILSVRC2015/ILSVRC2015_DET.tar.gz',
-    'det_test': 'http://image-net.org/image/ILSVRC2015/'
-                'ILSVRC2015_DET_test.tar.gz',
-    'det_test_new': 'http://image-net.org/image/ILSVRC2015/'
-                    'ILSVRC2015_DET_test_new.tar.gz'
-    'info': 'http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz'
-]
-
-def get_imagenet():
-    download_file_path = utils.cached_download(url)
-    ext = os.path.splitext(url)[1]
-    utils.extractall(download_file_path, data_root, ext)
-    return base_path
-

From 562fafd92130775211a0b672f61780fa87c22c64 Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Thu, 28 Dec 2017 00:41:35 +0900
Subject: [PATCH 7/9] Remove lsp files

---
 chainercv/datasets/lsp/__init__.py             | 0
 chainercv/datasets/lsp/lsp_keypoint_dataset.py | 0
 2 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 chainercv/datasets/lsp/__init__.py
 delete mode 100644 chainercv/datasets/lsp/lsp_keypoint_dataset.py

diff --git a/chainercv/datasets/lsp/__init__.py b/chainercv/datasets/lsp/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/chainercv/datasets/lsp/lsp_keypoint_dataset.py b/chainercv/datasets/lsp/lsp_keypoint_dataset.py
deleted file mode 100644
index e69de29bb2..0000000000

From ce8dbcd72e5b9cd65b4ed03b20275f139626f4f0 Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Thu, 28 Dec 2017 00:50:35 +0900
Subject: [PATCH 8/9] Reflect reviews

---
 chainercv/datasets/__init__.py                |  2 +-
 .../datasets/flic/flic_keypoint_dataset.py    | 27 ++++++++++---------
 chainercv/datasets/flic/flic_utils.py         | 24 ++++++-----------
 3 files changed, 23 insertions(+), 30 deletions(-)

diff --git a/chainercv/datasets/__init__.py b/chainercv/datasets/__init__.py
index 32d35ae741..1193802bb4 100644
--- a/chainercv/datasets/__init__.py
+++ b/chainercv/datasets/__init__.py
@@ -16,7 +16,7 @@
 from chainercv.datasets.directory_parsing_label_dataset import directory_parsing_label_names  # NOQA
 from chainercv.datasets.directory_parsing_label_dataset import DirectoryParsingLabelDataset  # NOQA
 from chainercv.datasets.flic.flic_keypoint_dataset import FLICKeypointDataset  # NOQA
-from chainercv.datasets.flic.flic_utils import flic_joint_label_names  # NOQA
+from chainercv.datasets.flic.flic_utils import flic_joint_names  # NOQA
 from chainercv.datasets.online_products.online_products_dataset import online_products_super_label_names  # NOQA
 from chainercv.datasets.online_products.online_products_dataset import OnlineProductsDataset  # NOQA
 from chainercv.datasets.transform_dataset import TransformDataset  # NOQA
diff --git a/chainercv/datasets/flic/flic_keypoint_dataset.py b/chainercv/datasets/flic/flic_keypoint_dataset.py
index f2be12a531..2d41e3f0e8 100644
--- a/chainercv/datasets/flic/flic_keypoint_dataset.py
+++ b/chainercv/datasets/flic/flic_keypoint_dataset.py
@@ -46,20 +46,21 @@ class FLICKeypointDataset(chainer.dataset.DatasetMixin):
     Args:
         data_dir (string): Path to the root of the training data. If this is
             :obj:`auto`, this class will automatically download data for you
-            under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/cub`.
+            under :obj:`$CHAINER_DATASET_ROOT/pfnet/chainercv/flic/FLIC-full`.
         split ({'train', 'test'}): Select from dataset splits used in
             the FLIC dataset.
         return_torsobox (bool): If :obj:`True`, this returns a bounding box
             around the torso. The default value is :obj:`False`.
-        skip_bad (bool): If :obj:`True`, the data which have :obj:`isbad = 1`
-            will be ignored. The default is :obj:`True`.
-        skip_unchecked (bool): If :obj:`True`, the data which have
-            :obj:`isunchecked = 1` will be ignored. The default is :obj:`True`.
+        use_bad (bool): If :obj:`False`, the data which have :obj:`isbad = 1`
+            will be ignored. The default is :obj:`False`.
+        use_unchecked (bool): If :obj:`False`, the data which have
+            :obj:`isunchecked = 1` will be ignored. The default is
+            :obj:`False`.
 
     """
 
     def __init__(self, data_dir='auto', split='train', return_torsobox=False,
-                 skip_bad=True, skip_unchecked=True):
+                 use_bad=False, use_unchecked=False):
         super(FLICKeypointDataset, self).__init__()
         if split not in ['train', 'test']:
             raise ValueError(
@@ -75,9 +76,9 @@ def __init__(self, data_dir='auto', split='train', return_torsobox=False,
             data_dir = flic_utils.get_flic()
 
         img_paths = {os.path.basename(fn): fn for fn in glob.glob(
-            os.path.join(data_dir, 'FLIC-full', 'images', '*.jpg'))}
+            os.path.join(data_dir, 'images', '*.jpg'))}
 
-        label_keys = [
+        label_annos = [
             'poselet_hit_idx',
             'moviename',
             'coords',
@@ -90,18 +91,18 @@ def __init__(self, data_dir='auto', split='train', return_torsobox=False,
             'isbad',
             'isunchecked',
         ]
-        labels = loadmat(os.path.join(data_dir, 'FLIC-full', 'examples.mat'))
+        annos = loadmat(os.path.join(data_dir, 'examples.mat'))
 
         self.img_paths = list()
         self.keypoints = list()
         self.torsoboxes = list()
         self.return_torsobox = return_torsobox
 
-        for label in labels['examples'][0]:
-            label = {label_keys[i]: val for i, val in enumerate(label)}
-            if skip_bad and int(label['isbad']) == 1:
+        for label in annos['examples'][0]:
+            label = {label_annos[i]: val for i, val in enumerate(label)}
+            if not use_bad and int(label['isbad']) == 1:
                 continue
-            if skip_unchecked and int(label['isunchecked']) == 1:
+            if not use_unchecked and int(label['isunchecked']) == 1:
                 continue
             if ((split == 'train' and int(label['istrain']) == 0)
                     or (split == 'test' and int(label['istest']) == 0)):
diff --git a/chainercv/datasets/flic/flic_utils.py b/chainercv/datasets/flic/flic_utils.py
index 0c863066f1..cdd389cd41 100644
--- a/chainercv/datasets/flic/flic_utils.py
+++ b/chainercv/datasets/flic/flic_utils.py
@@ -5,14 +5,9 @@
 
 root = 'pfnet/chainercv/flic'
 
-urls = [
-    'http://vision.grasp.upenn.edu/video/FLIC-full.zip',
+url = 'http://vision.grasp.upenn.edu/video/FLIC-full.zip'
 
-    'http://cims.nyu.edu/~tompson/data/tr_plus_indices.mat',
-
-]
-
-flic_joint_label_names = [
+flic_joint_names = [
     'lsho',
     'lelb',
     'lwri',
@@ -47,13 +42,10 @@
 
 def get_flic():
     data_root = download.get_dataset_directory(root)
+    dataset_dir = os.path.join(data_root, 'FLIC-full')
+    if not os.path.exists(dataset_dir):
+        download_file_path = utils.cached_download(url)
+        ext = os.path.splitext(url)[1]
+        utils.extractall(download_file_path, data_root, ext)
 
-    if not os.path.exists(os.path.join(data_root,
-                                       'FLIC-full')):
-        download_file_path = utils.cached_download(urls[0])
-        ext = os.path.splitext(urls[0])[1]
-        utils.extractall(download_file_path,
-                         data_root,
-                         ext)
-
-    return data_root
+    return dataset_dir

From b1e7afd104da399c06afca09b39ff7aa15483917 Mon Sep 17 00:00:00 2001
From: Shunta Saito <shunta.saito@gmail.com>
Date: Thu, 28 Dec 2017 00:52:02 +0900
Subject: [PATCH 9/9] Add to reference

---
 docs/source/reference/datasets.rst | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/docs/source/reference/datasets.rst b/docs/source/reference/datasets.rst
index 853d77bc0e..d82a1a28ae 100644
--- a/docs/source/reference/datasets.rst
+++ b/docs/source/reference/datasets.rst
@@ -54,6 +54,12 @@ CUBKeypointDataset
 ~~~~~~~~~~~~~~~~~~~
 .. autoclass:: CUBKeypointDataset
 
+FLIC
+----
+
+FLICKeypointDataset
+~~~~~~~~~~~~~~~~~~~
+.. autoclass:: FLICKeypointDataset
 
 OnlineProducts
 --------------