MCPcopy Index your code
hub / github.com/tensorlayer/TensorLayer / load_cyclegan_dataset

Function load_cyclegan_dataset

tensorlayer/files/utils.py:1220–1264  ·  view source on GitHub ↗

Load images from CycleGAN's database, see `this link `__. Parameters ------------ filename : str The dataset you want, see `this link `__. pa

(filename='summer2winter_yosemite', path='data')

Source from the content-addressed store, hash-verified

1218
1219
1220def load_cyclegan_dataset(filename='summer2winter_yosemite', path='data'):
1221 """Load images from CycleGAN&#x27;s database, see `this link <https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/>`__.
1222
1223 Parameters
1224 ------------
1225 filename : str
1226 The dataset you want, see `this link <https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/>`__.
1227 path : str
1228 The path that the data is downloaded to, defaults is `data/cyclegan`
1229
1230 Examples
1231 ---------
1232 >>> im_train_A, im_train_B, im_test_A, im_test_B = load_cyclegan_dataset(filename='summer2winter_yosemite')
1233
1234 """
1235 path = os.path.join(path, 'cyclegan')
1236 url = 'https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/'
1237
1238 if folder_exists(os.path.join(path, filename)) is False:
1239 logging.info("[*] {} is nonexistent in {}".format(filename, path))
1240 maybe_download_and_extract(filename + '.zip', path, url, extract=True)
1241 del_file(os.path.join(path, filename + '.zip'))
1242
1243 def load_image_from_folder(path):
1244 path_imgs = load_file_list(path=path, regx='\\.jpg', printable=False)
1245 return visualize.read_images(path_imgs, path=path, n_threads=10, printable=False)
1246
1247 im_train_A = load_image_from_folder(os.path.join(path, filename, "trainA"))
1248 im_train_B = load_image_from_folder(os.path.join(path, filename, "trainB"))
1249 im_test_A = load_image_from_folder(os.path.join(path, filename, "testA"))
1250 im_test_B = load_image_from_folder(os.path.join(path, filename, "testB"))
1251
1252 def if_2d_to_3d(images): # [h, w] --> [h, w, 3]
1253 for i, _v in enumerate(images):
1254 if len(images[i].shape) == 2:
1255 images[i] = images[i][:, :, np.newaxis]
1256 images[i] = np.tile(images[i], (1, 1, 3))
1257 return images
1258
1259 im_train_A = if_2d_to_3d(im_train_A)
1260 im_train_B = if_2d_to_3d(im_train_B)
1261 im_test_A = if_2d_to_3d(im_test_A)
1262 im_test_B = if_2d_to_3d(im_test_B)
1263
1264 return im_train_A, im_train_B, im_test_A, im_test_B
1265
1266
1267def download_file_from_google_drive(ID, destination):

Callers

nothing calls this directly

Calls 5

folder_existsFunction · 0.85
del_fileFunction · 0.85
load_image_from_folderFunction · 0.70
if_2d_to_3dFunction · 0.70

Tested by

no test coverage detected

Used in the wild real call sites across dependent graphs

searching dependent graphs…