model.fit giving ValueError : Error when checking input: expected conv2d got array with shape ()

Question

大家好，我在使用 model.fit() 训练模型时收到 ValueError.. 我尝试了很多方法来解决它但没有用。看一看.. 但是我确实将所有图像调整为 (512, 512)

................
................
................

def resizing(image, label):
  image = tf.image.resize(image, (512, 512))/255.0
  return image, label

mapped_training_set = train_set.map(resizing)
mapped_testing_set = test_set.map(resizing)
mapped_valid_set = valid_set.map(resizing)

tf.keras.layers.Conv2D(32, (3, 3), input_shape=(512, 512, 3), activation="relu"),
tf.keras.layers.MaxPooling2D((2, 2)),
.........
.........
.........

tf.keras.layers.Flatten(),
tf.keras.layers.Dense(512, activation="relu"),
tf.keras.layers.Dense(101, activation="softmax")


model.compile(optimizer="adam",
              loss="sparse_categorical_crossentropy",
              metrics=["accuracy"])

hist = model.fit(mapped_training_set,
                 epochs=10,
                 validation_data=mapped_valid_set,
                 )

**我收到此错误：**

<ipython-input-31-1d134652773c> in <module>()
      1 hist = model.fit(mapped_training_set,
      2                  epochs=10,
----> 3                  validation_data=mapped_valid_set,
      4                  )

16 frames
/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/impl/api.py in wrapper(*args, **kwargs)
    235       except Exception as e:  # pylint:disable=broad-except
    236         if hasattr(e, 'ag_error_metadata'):
--> 237           raise e.ag_error_metadata.to_exception(e)
    238         else:
    239           raise

ValueError: in converted code:

    /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py:677 map_fn
        batch_size=None)
    /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training.py:2410 _standardize_tensors
        exception_prefix='input')
    /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_utils.py:573 standardize_input_data
        'with shape ' + str(data_shape))

    ValueError: Error when checking input: expected conv2d_32_input to have 4 dimensions, but got array with shape (512, 512, 3)

我试图搜索修复错误，现在已经超过 2 小时了，我没有找到答案..

我找到的所有结果和解决方案都不是我的主题。

请帮助我卡在这里。

提前致谢

Answer 1

您需要向模型传递 (batch_size, height, width, channels) 的输入形状。这就是为什么它说它需要 4 个维度。相反，您向它传递了 (512, 512, 3).

的单个图像

如果您想在单张图片上训练您的模型，您应该通过 image = tf.expand_dims(image, axis=0) 更改每张图片的形状。这可以在 resize 函数中完成。

如果您想批量训练您的模型，您应该在 map 之后添加 mapped_training_set = mapped_training_set.batch(batch_size)。然后其他两个数据集也一样。

model.fit giving ValueError : Error when checking input: expected conv2d got array with shape ()

model.fit giving ValueError : Error when checking input: expected conv2d got array with shape ()

python

deep-learning

keras

tensorflow

valueerror