小编TTA*_*TTA的帖子

我正在尝试训练我的图像。该数据的大小为 50.000 张图像。

我的图像属性是：

如果我应该更改图像属性，我该怎么做？

这是我的第一个图像分类器工作，因此可能会有很多错误。敬请谅解。

你能帮助改进我的代码吗？

这是我的代码

from tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Conv2D,MaxPooling2D,Activation,Dropout,Flatten,Dense\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator,img_to_array,load_img\nimport matplotlib.pyplot as plt\nfrom glob import glob\nfrom PIL import Image\nimport os\n\n\nimport numpy as np\n\ntrain_path="D\xc3\xbczg\xc3\xbcn2/"\n\nimages = [train_path for train_path in os.listdir() if train_path.endswith((\'jpeg\', \'png\', \'jpg\'))]\nfor x in images:\n    img = Image.open(x)\n    img.thumbnail((600,600))\n    img.save("resized_"+x, optimize=True, quality=40)\ntest_path="Test/"\ndata=load_img(train_path + "Basler_acA1440-220um__40052667__20201123_114618747_7932_result.jpg")\nx=np.asarray(data)\n\nplt.imshow(data)\nplt.axis("off")\nplt.show()\n\n\nprint(x.shape)\nclassName=glob(train_path + "/*")\nprint(className)\nnumberOfClass=len(className)\nprint("NumberOfClass:",numberOfClass)\n\n#CNN model\n\nmodel=Sequential()\nmodel.add(Conv2D(32,(3,3),input_shape=(224,224,3)))#xshape burada gelen resimin pixseli 3 ise rgb yi tesmil ediyor so that senin \xc3\xa7ivi resimlerine g\xc3\xb6re ayarla\nmodel.add(Activation("relu"))\nmodel.add(MaxPooling2D())\nmodel.add(Conv2D(32,(3,3)))#xshape …