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[英]While predicting on trained model I've getting an Image shape error
[英]Error while predicting classes of an trained DNN model
我使用以下程序来预测我的图像的类别。
from tensorflow.keras.preprocessing.image import load_img, img_to_array x = load_img("8-SignLanguageMNIST/test1.jpg", target_size = (28, 28)) x = img_to_array(x) x = np.expand_dims(x, axis = 0) x = np.vstack([x]) classes = model.predict(x) print(classes[0])
我用于训练的图像是形状 (28, 28, 1)。
在这里,我上传了一个形状为 (28, 28, 3) 的 RGB 图像,我尝试将该图像转换为灰度,然后进行预测,但一直出现以下错误。
ValueError: Input 0 of layer sequential is incompatible with the layer: expected axis -1 of input shape to have value 1 but received input with shape [None, 28, 28, 3]
谁能告诉我我做错了什么,并帮助我解决这个问题。
您需要将转换应用于灰度,如下所示:
load_img(path, color_mode='grayscale')
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