test_submit_multithreaded.py 文件源码

def predictor(q, ):
    for i in tqdm(range(0, len(ids_test), batch_size)):
        x_batch = q.get()
        with graph.as_default():
            preds = model.predict_on_batch(x_batch)
        preds = np.squeeze(preds, axis=3)
        for pred in preds:
            prob = cv2.resize(pred, (orig_width, orig_height))
            mask = prob > threshold
            rle = run_length_encode(mask)
            rles.append(rle)