def publish_images(self, img_inds, preproc, bucket_name, dummy_upload=False): ids = [ get_id(str(image_id) + repr(preproc)) for image_id in self.meta['id'][img_inds] ] source = get_img_source() if preproc is not None: raise NotImplementedError else: filenames = np.array(self.meta['filename'][img_inds]) conn = boto.connect_s3() b = conn.create_bucket(bucket_name) urls = [] i = 0 for image_id, filename in zip(ids, filenames): i += 1 if i % 100 == 0: print i / float(len(filenames)) if not dummy_upload: k = b.new_key(image_id + '.jpg') k.set_contents_from_file(source.get(str(filename)), policy='public-read') urls.append('https://s3.amazonaws.com/' + bucket_name + '/' + image_id + '.jpg') return urls
def __init__(self, data=None): """ :param data: data specifying how to build this dataset. should uniquely identify dataset among all datasets :raise: ValueError if instantiated directly """ cname = self.__class__.__name__ if cname == 'Imagenet_Base': print 'The Imagenet base class should not be directly instantiated' raise ValueError img_path = self.imagenet_home('images') self.specific_name = self.__class__.__name__ + '_' + get_id(data) if not os.path.exists(img_path): os.makedirs(img_path) self.img_path = img_path self.meta_path = self.local_home('meta') if not os.path.exists(self.meta_path): os.makedirs(self.meta_path) self.default_preproc = { 'resize_to': (256, 256), 'mode': 'RGB', 'dtype': 'float32', 'crop': None, 'mask': None, 'normalize': False } super(Imagenet_Base, self).__init__(data)
def __init__(self, data=None): """ :param data: data specifying how to build this dataset. should uniquely identify dataset among all datasets :raise: ValueError if instantiated directly """ cname = self.__class__.__name__ if cname == "Imagenet_Base": print "The Imagenet base class should not be directly instantiated" raise ValueError img_path = self.imagenet_home("images") self.specific_name = self.__class__.__name__ + "_" + get_id(data) if not os.path.exists(img_path): os.makedirs(img_path) self.img_path = img_path self.meta_path = self.local_home("meta") if not os.path.exists(self.meta_path): os.makedirs(self.meta_path) self.default_preproc = { "resize_to": (256, 256), "mode": "RGB", "dtype": "float32", "crop": None, "mask": None, "normalize": False, } super(Imagenet_Base, self).__init__(data)
def publish_images(self, img_inds, preproc, bucket_name, dummy_upload=False): ids = [get_id(str(image_id) + repr(preproc)) for image_id in self.meta["id"][img_inds]] source = get_img_source() if preproc is not None: raise NotImplementedError else: filenames = np.array(self.meta["filename"][img_inds]) conn = boto.connect_s3() b = conn.create_bucket(bucket_name) urls = [] i = 0 for image_id, filename in zip(ids, filenames): i += 1 if i % 100 == 0: print i / float(len(filenames)) if not dummy_upload: k = b.new_key(image_id + ".jpg") k.set_contents_from_file(source.get(str(filename)), policy="public-read") urls.append("https://s3.amazonaws.com/" + bucket_name + "/" + image_id + ".jpg") return urls