为什么我的CNN中无法将图像数据放入model.predict中？

如何解决为什么我的CNN中无法将图像数据放入model.predict中？

我已经建立并训练了CNN模型，我想对其进行测试。 我编写了一个脚本，该脚本从指定的目录路径中获取输入图像，然后对该图像进行预处理，并将像素值重新缩放为0到1之间。我还将该图像调整为正确的尺寸，并使用了{{1}进行预测。但是，当我运行代码时：

fun deleteItemFromDb(s: String) = viewModelScope.launch(dispatchersProvider.IO){ 
    repository.deleteItem(s)
}

此错误弹出：

model.predict()

我在做什么错或者我只是想念一些东西？ 另外，我尝试使用from keras.models import Sequential from keras_preprocessing.image import * from keras.layers import * import tensorflow as tf import numpy as np from keras.layers.experimental.preprocessing import Rescaling import os import cv2 from keras.models import * img_size = 250 #Load weights into new model filepath = os.getcwd() + "/trained_model.h5" model = load_model(filepath) print("Loaded model from disk") #Scales the pixel values to between 0 to 1 #datagen = ImageDataGenerator(rescale=1.0/255.0) #Prepares Testing Data testing_dataset = cv2.imread(os.getcwd() + "/cats and dogs images/single test sample/505.png") #img = datagen.flow_from_directory(testing_dataset,target_size=(img_size,img_size)) img = cv2.resize(testing_dataset,(img_size,img_size)) newimg = np.asarray(img) pixels = newimg.astype('float32') pixels /= 255.0 print(pixels.shape) model.predict(x=pixels) 和Loaded model from disk (250,250,3) Traceback (most recent call last): File "C:\Users\Jackson\Documents\Programming\Python Projects\Neural Network That Deteremines Cats and Dogs\Test Trained Model.py",line 34,in <module> model.predict(x=pixels) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py",line 130,in _method_wrapper return method(self,*args,**kwargs) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py",line 1599,in predict tmp_batch_outputs = predict_function(iterator) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\def_function.py",line 780,in __call__ result = self._call(*args,**kwds) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\def_function.py",line 823,in _call self._initialize(args,kwds,add_initializers_to=initializers) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\def_function.py",line 696,in _initialize self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\function.py",line 2855,in _get_concrete_function_internal_garbage_collected graph_function,_,_ = self._maybe_define_function(args,kwargs) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\function.py",line 3213,in _maybe_define_function graph_function = self._create_graph_function(args,line 3065,in _create_graph_function func_graph_module.func_graph_from_py_func( File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\framework\func_graph.py",line 986,in func_graph_from_py_func func_outputs = python_func(*func_args,**func_kwargs) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\eager\def_function.py",line 600,in wrapped_fn return weak_wrapped_fn().__wrapped__(*args,**kwds) File "C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\framework\func_graph.py",line 973,in wrapper raise e.ag_error_metadata.to_exception(e) ValueError: in user code: C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1462 predict_function * return step_function(self,iterator) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1452 step_function ** outputs = model.distribute_strategy.run(run_step,args=(data,)) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1211 run return self._extended.call_for_each_replica(fn,args=args,kwargs=kwargs) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2585 call_for_each_replica return self._call_for_each_replica(fn,args,kwargs) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2945 _call_for_each_replica return fn(*args,**kwargs) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1445 run_step ** outputs = model.predict_step(data) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\training.py:1418 predict_step return self(x,training=False) C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:975 __call__ input_spec.assert_input_compatibility(self.input_spec,inputs,C:\Users\Jackson\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\engine\input_spec.py:191 assert_input_compatibility raise ValueError('Input ' + str(input_index) + ' of layer ' + ValueError: Input 0 of layer sequential is incompatible with the layer: : expected min_ndim=4,found ndim=3. Full shape received: [None,3] 进行相同操作，但出现相同的错误。

解决方法

如果您针对与模型的所需输入形状相匹配的图像输入形状所做的所有操作均正确无误，则模型很可能希望收到一批大小为（250、250、3）的图像，因此如果您要在输入形状上测试的图像的大小应为（1、250、250、3），这表示您正在传递一批大小为1的图像。

错误消息的意思是该模型期望输入形状为4维并且传递了输入形状为3维，您需要包括批处理维，因此我认为在图像标准化后添加此行使它起作用。

pixels = np.expand_dims(pixels,axis=0)

在打印形状线时，像素形状应为（1、250、250、3）