def encode_entry(self, entry): """ Return numpy.ndarray """ feature_image_file = entry[0] label_image_file = entry[1] feature_image = self.encode_PIL_Image( image.load_image(feature_image_file)) label_image = self.encode_PIL_Image(image.load_image(label_image_file)) return feature_image, label_image
def encode_entry(self, entry): """ Return numpy.ndarray """ feature_image_file = entry[0] label_image_file = entry[1] feature_image = self.encode_PIL_Image( image.load_image(feature_image_file)) label_image = self.encode_PIL_Image( image.load_image(label_image_file)) return feature_image, label_image
def encode_entry(self, entry): """ Return numpy.ndarray """ feature_image_file = entry[0] label_image_file = entry[1] # feature image feature_image = self.encode_PIL_Image( image.load_image(feature_image_file), self.channel_conversion) # label image label_image = self.load_label(label_image_file) if label_image.getpalette() != self.userdata[COLOR_PALETTE_ATTRIBUTE]: raise ValueError("All label images must use the same palette") label_image = self.encode_PIL_Image(label_image) return feature_image, label_image
def scale_image(self, filename): im = np.array(image.load_image(filename)) # center crop if self.userdata['center_crop_size']: crop_size = int(self.userdata['center_crop_size']) width, height = im.shape[0:2] i = (width // 2) - crop_size // 2 j = (height // 2) - crop_size // 2 im = im[i:i + crop_size, j:j + crop_size, :] # resize if self.userdata['resize']: resize = int(self.userdata['resize']) im = image.resize_image(im, resize, resize, resize_mode='squash') # transpose to CHW feature = im.transpose(2, 0, 1) return feature