小编Ema*_*aci的帖子

我试图在 SegNet 模型上运行预测，但是当它调用预测函数时，我收到了一个错误。

我也尝试使用 运行预测with tf.device('/cpu:0'):，但我收到了同样的错误

if __name__ == '__main__':
    # path to the model
    model = tf.keras.models.load_model('segnet_weightsONNXbackToKeras3.h5')

    model.compile(loss='categorical_crossentropy', optimizer='RMSprop', metrics=['accuracy'])

    model.summary()

    input_shape = [None, 360, 480, 3]
    output_shape = [None, 352, 480, 20]

    img = cv2.imread('test4.jpg')
    input_image = img
    img = cv2.resize(img, (input_shape[2], input_shape[1]))
    img = np.reshape(img, [1, input_shape[1], input_shape[2], input_shape[3]])

    if normalize:
        img = img.astype('float32') / 255

    model.summary()
    classes = model.predict(img)[0]
    colors = []
    for i in range(output_shape[3]):
        colors.append(generate_color())

    maxMatrix = np.amax(classes, axis=2)
    prediction = np.zeros((output_shape[1], …