Function run_image

examples/DoReFa-Net/resnet-dorefa.py:117–141

(model, sess_init, inputs)

def run_image(model, sess_init, inputs):
    pred_config = PredictConfig(
        model=model,
        session_init=sess_init,
        input_names=['input'],
        output_names=['output']
    )
    predict_func = OfflinePredictor(pred_config)
    meta = dataset.ILSVRCMeta()
    words = meta.get_synset_words_1000()

    transformers = get_inference_augmentor()
    for f in inputs:
        assert os.path.isfile(f)
        img = cv2.imread(f).astype('float32')
        assert img is not None

        img = transformers.augment(img)[np.newaxis, :, :, :]
        o = predict_func(img)
        prob = o[0][0]
        ret = prob.argsort()[-10:][::-1]

        names = [words[i] for i in ret]
        print(f + ":")
        print(list(zip(names, prob[ret])))


if __name__ == '__main__':