image_processing.py 文件源码

def load_image_array(image_file, image_size,
                     image_id, data_dir='Data/datasets/mscoco/train2014',
                     mode='train'):
    img = None
    if os.path.exists(image_file):
        #print('found' + image_file)
        img = skimage.io.imread(image_file)
    else:
        print('notfound' + image_file)
        img = skimage.io.imread('http://mscoco.org/images/%d' % (image_id))
        img_path = os.path.join(data_dir, 'COCO_%s2014_%.12d.jpg' % ( mode,
                                                                      image_id))
        skimage.io.imsave(img_path, img)

    # GRAYSCALE
    if len(img.shape) == 2:
        img_new = np.ndarray( (img.shape[0], img.shape[1], 3), dtype = 'uint8')
        img_new[:,:,0] = img
        img_new[:,:,1] = img
        img_new[:,:,2] = img
        img = img_new

    img_resized = skimage.transform.resize(img, (image_size, image_size))

    # FLIP HORIZONTAL WIRH A PROBABILITY 0.5
    if random.random() > 0.5:
        img_resized = np.fliplr(img_resized)

    return img_resized.astype('float32')