Create my1.py

reid/datasets/my1.py

@@ -0,0 +1,198 @@
+from __future__ import print_function, absolute_import
+import os.path as osp
+
+import numpy as np
+
+from ..utils.data import Dataset
+from ..utils.osutils import mkdir_if_missing
+from ..utils.serialization import write_json
+
+
+class MY1(Dataset):
+    def __init__(self, root, split_id=0, num_val=100, download=False):
+        super(MY1, self).__init__(root, split_id=split_id)
+
+        if download:
+            self.download()
+
+        if not self._check_integrity():
+            raise RuntimeError("Dataset not found or corrupted. " +
+                               "You can use download=True to download it.")
+        self.load(num_val)
+
+    def download(self):
+        if self._check_integrity():
+            print("Files already downloaded and verified")
+            return
+
+
+###### ..............................................................MARK1501
+
+
+        from six.moves import urllib
+
+        import re
+
+        import hashlib
+        import shutil
+        from glob import glob
+        from zipfile import ZipFile
+        from scipy.misc import imsave, imread
+        import h5py
+        raw_dir = osp.join(self.root, 'raw')
+        mkdir_if_missing(raw_dir)
+
+        # Download the raw zip file
+        fpath = osp.join(raw_dir, 'Market-1501-v15.09.15.zip')
+        # if osp.isfile(fpath) and \
+        #   hashlib.md5(open(fpath, 'rb').read()).hexdigest() == self.md5:
+        #     print("Using downloaded file: " + fpath)
+        # else:
+        #     raise RuntimeError("Please download the dataset manually from {} "
+        #                        "to {}".format(self.url, fpath))
+
+        # Extract the file
+        exdir = osp.join(raw_dir, 'Market-1501-v15.09.15')
+        if not osp.isdir(exdir):
+            print("Extracting zip file")
+            with ZipFile(fpath) as z:
+                z.extractall(path=raw_dir)
+
+        # Format
+        images_dir = osp.join(self.root, 'images')
+        mkdir_if_missing(images_dir)
+
+        # 1501 identities (+1 for background) with 6 camera views each
+        identities = [[[] for _ in range(6)] for _ in range(1502)]
+
+        def register(subdir, pattern=re.compile(r'([-\d]+)_c(\d)')):
+            fpaths = sorted(glob(osp.join(exdir, subdir, '*.jpg')))
+            pids = set()
+            for fpath in fpaths:
+                fname = osp.basename(fpath)
+                pid, cam = map(int, pattern.search(fname).groups())
+                if pid == -1: continue  # junk images are just ignored
+                assert 0 <= pid <= 1501  # pid == 0 means background
+                assert 1 <= cam <= 6
+                cam -= 1
+                pids.add(pid)
+                fname = ('{:08d}_{:02d}_{:04d}.jpg'
+                         .format(pid, cam, len(identities[pid][cam])))
+                identities[pid][cam].append(fname)
+                shutil.copy(fpath, osp.join(images_dir, fname))
+            return pids
+#....................................................................cukn03
+
+        # Extract the file
+        fpath = osp.join(raw_dir, 'cuhk03_release.zip')
+        exdir = osp.join(raw_dir, 'cuhk03_release')
+        if not osp.isdir(exdir):
+            print("Extracting zip file")
+            with ZipFile(fpath) as z:
+                z.extractall(path=raw_dir)
+
+        # Format
+        images_dir = osp.join(self.root, 'images')
+        mkdir_if_missing(images_dir)
+        matdata = h5py.File(osp.join(exdir, 'cuhk-03.mat'), 'r')
+
+        def deref(ref):
+            return matdata[ref][:].T
+
+        def dump_(refs, pid, cam, fnames):
+            for ref in refs:
+                img = deref(ref)
+                if img.size == 0 or img.ndim < 2: break
+                fname = '{:08d}_{:02d}_{:04d}.jpg'.format(pid+1501, cam, len(fnames))
+                imsave(osp.join(images_dir, fname), img)
+                fnames.append(fname)
+
+        #identities = []
+        for labeled, detected in zip(
+                matdata['labeled'][0], matdata['detected'][0]):
+            labeled, detected = deref(labeled), deref(detected)
+            assert labeled.shape == detected.shape
+            for i in range(labeled.shape[0]):
+                pid = len(identities)
+                images = [[], []]
+                dump_(labeled[i, :5], pid, 0, images[0])
+                dump_(detected[i, :5], pid, 0, images[0])
+                dump_(labeled[i, 5:], pid, 1, images[1])
+                dump_(detected[i, 5:], pid, 1, images[1])
+                identities.append(images)
+#............................................viper
+
+        fpath = osp.join(raw_dir, 'VIPeR.v1.0.zip')
+        exdir = osp.join(raw_dir, 'VIPeR')
+        if not osp.isdir(exdir):
+            print("Extracting zip file")
+            with ZipFile(fpath) as z:
+                z.extractall(path=raw_dir)
+
+        #Format
+        images_dir = osp.join(self.root, 'images')
+        mkdir_if_missing(images_dir)
+        cameras = [sorted(glob(osp.join(exdir, 'cam_a', '*.bmp'))),
+                   sorted(glob(osp.join(exdir, 'cam_b', '*.bmp')))]
+        assert len(cameras[0]) == len(cameras[1])
+        # identities = []
+        for pid, (cam1, cam2) in enumerate(zip(*cameras)):
+            images = []
+            # view-0
+            # fname = '{:08d}_{:02d}_{:04d}.jpg'.format(pid, 0, 0)
+            fname = '{:08d}_{:02d}_{:04d}.jpg'.format(pid+2968, 0, 0)
+            imsave(osp.join(images_dir, fname), imread(cam1))
+            images.append([fname])
+            # view-1
+            fname = '{:08d}_{:02d}_{:04d}.jpg'.format(pid+2968, 1, 0)
+            imsave(osp.join(images_dir, fname), imread(cam2))
+            images.append([fname])
+            identities.append(images)
+#............................
+        fpath = osp.join(raw_dir, 'CUHK01.zip')
+        # Extract the file
+        exdir = osp.join(raw_dir, 'campus')
+        if not osp.isdir(exdir):
+            print("Extracting zip file")
+            with ZipFile(fpath) as z:
+                z.extractall(path=raw_dir)
+
+        # Format
+        images_dir = osp.join(self.root, 'images')
+        mkdir_if_missing(images_dir)
+
+        identities1 = [[[] for _ in range(2)] for _ in range(971)]
+
+        files = sorted(glob(osp.join(exdir, '*.png')))
+        for fpath in files:
+            fname = osp.basename(fpath)
+            pid, cam = int(fname[:4]), int(fname[4:7])
+            assert 1 <= pid <= 971
+            assert 1 <= cam <= 4
+            pid, cam = pid - 1, (cam - 1) // 2
+            fname = ('{:08d}_{:02d}_{:04d}.png'
+                     .format(pid+3590, cam, len(identities1[pid][cam])))
+            identities1[pid][cam].append(fname)
+            shutil.copy(fpath, osp.join(images_dir, fname))
+
+
+        for a1 in identities1:
+            identities.append(a1)
+
+#...........................................
+        meta = {'name': 'MY', 'shot': 'multiple', 'num_cameras': 10,
+                'identities': identities}
+        write_json(meta, osp.join(self.root, 'meta.json'))
+
+        # Randomly create ten training and test split
+        num = len(identities)
+        splits = []
+        for _ in range(10):
+            pids = np.random.permutation(num).tolist()
+            trainval_pids = sorted(pids[:num // 2])
+            test_pids = sorted(pids[num // 2:])
+            split = {'trainval': trainval_pids,
+                     'query': test_pids,
+                     'gallery': test_pids}
+            splits.append(split)
+        write_json(splits, osp.join(self.root, 'splits.json'))