层“sequential_3”的输入 0 与层不兼容：预期形状=(None, 256, 256, 3)，找到形状=(None, 324, 500, 3)

xiaoxingxing tensorflow 277

原文标题 ：Input 0 of layer “sequential_3” is incompatible with the layer: expected shape=(None, 256, 256, 3), found shape=(None, 324, 500, 3)

如果有人可以提供帮助，我遇到问题请发表评论

input_shape=(BATCH_SIZE,256,256,3)
model=models.Sequential([
        resize_and_rescale,
        data_augmentation,

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

        layers.Conv2D(64,kernel_size=(3,3), activation="relu"),
        layers.MaxPooling2D((2,2)),
        layers.Conv2D(64,kernel_size=(3,3), activation="relu"),
        layers.MaxPooling2D((2,2)),
        
        layers.Conv2D(64,(3,3), activation="relu"),
        layers.MaxPooling2D((2,2)),
        layers.Conv2D(64,(3,3), activation="relu"),
        layers.MaxPooling2D((2,2)),
        layers.Conv2D(64,(3,3), activation="relu"),
        layers.MaxPooling2D((2,2)),

        layers.Flatten(),
        layers.Dense(64,activation="relu"),

        layers.Dense(n_classes, activation="softmax")

  ])
  model.build(input_shape=input_shape)

这是我的模型，它工作得很好，但是当我从邮递员发布不同于 256,256 的任何尺寸的图像时

@app.post("/predict")
async def predict(
file: UploadFile = File(...)
):
image = read_file_as_image(await file.read())
img_batch = np.expand_dims(image, 0)

predictions = MODEL.predict(img_batch)

predicted_class = CLASS_NAMES[np.argmax(predictions[0])]
confidence = np.max(predictions[0])
return {
    'class': predicted_class,
    'confidence': float(confidence)
}

if __name__ == "__main__":
uvicorn.run(app, host='localhost', port=8000)

这是我的快速 api 返回的内容->

层“sequential_3”的输入 0 与层不兼容：预期形状=(None, 256, 256, 3)，找到形状=(None, 324, 500, 3)

我尝试从 Pillow 调整图像大小，但没有成功，我对 fastapi 了解不多，所以如果有人知道如何解决此错误，请发表评论。

原文链接：https://stackoverflow.com//questions/71447801/input-0-of-layer-sequential-3-is-incompatible-with-the-layer-expected-shape

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  • Gerry P的头像
    Gerry P 评论

    什么是 read_file_as_image(await file.read())，是你写的函数吗？试试这个

    import matplotlib.pyplot as plt
import cv2
img_path= define the full path to the image here
img=plt.imread(img_path)
img=cv2.resize(img, (256,256,3)
img=np.expand_dims(img, axis=0)
print (img.shape)
    2年前 0条评论
  • I'mahdi的头像
    I'mahdi 评论

    在使用此之前，您需要调整图像大小：

    import cv2
...
image = read_file_as_image(await file.read())
image = cv2.resize(image, (256,256,3))
img_batch = np.expand_dims(image, 0) 
# OR
img_batch = image[None,...]
...

    更多解释：

    >>> import numpy as np
>>> a = np.array([[1,2],[2,3]])

>>> a.shape
(2, 2)

>>> a[None, ...].shape
(1, 2, 2)

>>> np.expand_dims(a, 0).shape
(1, 2, 2)
    2年前 0条评论

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