python - Can't use LFW dataset in sklearn -


it seems fetch_lfw_people function don't work, can't understand why.

here test code:

in [1]: import numpy np  in [2]: sklearn import datasets  in [3]: lfw= datasets.fetch_lfw_people()  ioerror                                   traceback (most recent call last) <ipython-input-3-1f0795d3f6a9> in <module>() ----> 1 lfw= datasets.fetch_lfw_people()  c:\python27\lib\site-packages\sklearn\datasets\lfw.pyc in fetch_lfw_people(data_ home, funneled, resize, min_faces_per_person, color, slice_, download_if_missing )     270     faces, target, target_names = load_func(     271         data_folder_path, resize=resize, --> 272         min_faces_per_person=min_faces_per_person, color=color, slice_=s lice_)     273     274     # pack results bunch instance  c:\python27\lib\site-packages\sklearn\externals\joblib\memory.pyc in __call__(se lf, *args, **kwargs)     169                           'directory %s'     170                         % (name, argument_hash, output_dir)) --> 171             return self.call(*args, **kwargs)     172         else:     173             try:  c:\python27\lib\site-packages\sklearn\externals\joblib\memory.pyc in call(self, *args, **kwargs)     321         if self._verbose:     322             print self.format_call(*args, **kwargs) --> 323         output = self.func(*args, **kwargs)     324         self._persist_output(output, output_dir)     325         duration = time.time() - start_time  c:\python27\lib\site-packages\sklearn\datasets\lfw.pyc in _fetch_lfw_people(data _folder_path, slice_, color, resize, min_faces_per_person)     195     target = np.searchsorted(target_names, person_names)     196 --> 197     faces = _load_imgs(file_paths, slice_, color, resize)     198     199     # shuffle faces deterministic rng scheme avoid having  c:\python27\lib\site-packages\sklearn\datasets\lfw.pyc in _load_imgs(file_paths,  slice_, color, resize)     149         if % 1000 == 0:     150             logger.info("loading face #%05d / %05d", + 1, n_faces) --> 151         face = np.asarray(imread(file_path)[slice_], dtype=np.float32)     152         face /= 255.0  # scale uint8 coded colors [0.0, 1.0] floa ts     153         if resize not none:  c:\python27\lib\site-packages\scipy\misc\pilutil.pyc in imread(name, flatten)     100     """     101 --> 102     im = image.open(name)     103     return fromimage(im,flatten=flatten)     104  c:\python27\lib\site-packages\pil\image.pyc in open(fp, mode)    1978                 pass    1979 -> 1980     raise ioerror("cannot identify image file")    1981    1982 #  ioerror: cannot identify image file


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