util.py 文件源码

def load_images(image_dir, convert_to_grayscale=True, dist="bernoulli"):
    dataset = []
    fs = os.listdir(image_dir)
    print "loading", len(fs), "images..."
    for fn in fs:
        f = open("%s/%s" % (image_dir, fn), "rb")
        if convert_to_grayscale:
            img = np.asarray(Image.open(StringIO(f.read())).convert("L"), dtype=np.float32) / 255.0
        else:
            img = np.asarray(Image.open(StringIO(f.read())).convert("RGB"), dtype=np.float32).transpose(2, 0, 1) / 255.0
        if dist == "bernoulli":
            # Sampling
            img = preprocessing.binarize(img, threshold=0.5)
            pass
        elif dist == "gaussian":
            pass
        else:
            raise Exception()
        dataset.append(img)
        f.close()
    return dataset