你好，我是一个新手与Numpy, Keras和stackoverflow，我有一个问题，我在一个循环
roi = roi.reshape(28,28)
roi = (np.linalg.norm(roi))
probas = model.predict(roi)[0]
#number = np.argmax(probas[i])
#i+=1
我确信我的重塑是有效的结果是
ValueError Traceback (most recent call last)
<ipython-input-385-3ee67baef91d> in <module>()
----> 1 detect_digits("/content/drive/MyDrive/Colab Notebooks/photo1.jpg", network)
3 frames
<ipython-input-384-79a58876db55> in detect_digits(image_name, model)
49 # 2. Use 'model' to make a prediction
50
---> 51 probas = model.predict(roi)[0]
52
53 # 3. Based on the prediction, determine the class (a number between 0 and 9)
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/training.py in predict(self, x, batch_size, verbose, steps, callbacks, max_queue_size, workers, use_multiprocessing)
1606 use_multiprocessing=use_multiprocessing,
1607 model=self,
-> 1608 steps_per_execution=self._steps_per_execution)
1609
1610 # Container that configures and calls `tf.keras.Callback`s.
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/data_adapter.py in __init__(self, x, y, sample_weight, batch_size, steps_per_epoch, initial_epoch, epochs, shuffle, class_weight, max_queue_size, workers, use_multiprocessing, model, steps_per_execution)
1097 self._steps_per_execution_value = steps_per_execution.numpy().item()
1098
-> 1099 adapter_cls = select_data_adapter(x, y)
1100 self._adapter = adapter_cls(
1101 x,
/usr/local/lib/python3.7/dist-packages/tensorflow/python/keras/engine/data_adapter.py in select_data_adapter(x, y)
962 "Failed to find data adapter that can handle "
963 "input: {}, {}".format(
--> 964 _type_name(x), _type_name(y)))
965 elif len(adapter_cls) > 1:
966 raise RuntimeError(
ValueError: Failed to find data adapter that can handle input: <class 'numpy.float32'>, <class 'NoneType'>
我解决了我的问题，解决方案是:
roi = roi.reshape((1,28*28))
min = np.min(roi)
max = np.max(roi)
roi = (roi - min) * (1.0/(max - min))
probas = model.predict(roi)[0]
number = np.argmax(probas)
我正在重塑我的矩阵成一个矢量，这就是为什么我的代码不工作，非常感谢你的帮助!