more datasets

cars196.py

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+import os
+import torch
+import torch.utils.data as data
+import torchvision
+from torchvision.datasets import ImageFolder
+from torchvision.datasets import CIFAR10
+
+class Cars196(ImageFolder, CIFAR10):
+	base_folder = 'car_ims'
+	url = 'http://imagenet.stanford.edu/internal/car196/car_ims.tgz'
+	filename = 'cars_ims.tgz'
+	tgz_md5 = 'd5c8f0aa497503f355e17dc7886c3f14'
+
+	base_folder_devkit = 'devkit'
+	url_devkit = 'http://ai.stanford.edu/~jkrause/cars/car_devkit.tgz'
+	filename_devkit = 'cars_devkit.tgz'
+	tgz_md5_devkit = 'c3b158d763b6e2245038c8ad08e45376'
+
+	train_list = []
+	test_list = []
+
+	def download(self):
+		pass
+
+	def __init__(self, root, train=False, transform=None, target_transform=None, download=False, **kwargs):
+		self.root = root
+		if download:
+			self.download()
+
+		if not self._check_integrity():
+			raise RuntimeError('Dataset not found or corrupted.' +
+							   ' You can use download=True to download it')
+		ImageFolder.__init__(self, os.path.join(root, self.base_folder), transform = transform, target_transform = target_transform, **kwargs)

stanford_online_products.py

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+import os
+import torch
+import torch.utils.data as data
+import torchvision
+from torchvision.datasets import ImageFolder
+from torchvision.datasets import CIFAR10
+from torchvision.datasets.utils import download_url
+
+class StanfordOnlineProducts(ImageFolder, CIFAR10):
+	base_folder = 'Stanford_Online_Products'
+	url = 'ftp://cs.stanford.edu/cs/cvgl/Stanford_Online_Products.zip'
+	filename = 'Stanford_Online_Products.zip'
+	zip_md5 = '7f73d41a2f44250d4779881525aea32e'
+
+	train_list = [
+		['bicycle_final/111265328556_0.JPG', '77420a4db9dd9284378d7287a0729edb']
+		['chair_final/111182689872_0.JPG', 'ce78d10ed68560f4ea5fa1bec90206ba']
+	]
+	test_list = [
+		['table_final/111194782300_0.JPG', '8203e079b5c134161bbfa7ee2a43a0a1'],
+		['toaster_final/111157129195_0.JPG', 'd6c24ee8c05d986cafffa6af82ae224e']
+	]
+
+	def __init__(self, root, train=None, transform=None, target_transform=None, download=False, **kwargs):
+		self.root = root
+		if download:
+			self.download()
+
+		if not self._check_integrity():
+			raise RuntimeError('Dataset not found or corrupted.' +
+							   ' You can use download=True to download it')
+
+	def download(self):
+		import zipfile
+
+		if self._check_integrity():
+			print('Files already downloaded and verified')
+			return
+
+		root = self.root
+		download_url(self.url, root, self.filename, self.zip_md5)
+
+		# extract file
+		cwd = os.getcwd()
+		zip = zipfile.open(os.path.join(root, self.filename), "r")
+		os.chdir(root)
+		zip.extractall()
+		zip.close()
+		os.chdir(cwd)