【Clipping input data to the .... for integers).】的解決辦法

【Clipping input data to the .... for integers).】的解決辦法：

          參考資料：https://www.freesion.com/article/7534157435/

          在用matplotlib.pyplot顯示輸入圖像時，一直報警告錯誤“Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).”，但圖像顯示結果是正常的。

          檢索了一些資料，有博主報錯的原因是用float32的圖像佔位符直接顯示了uint8格式的圖像，添加了“image = image/255”後停止報錯，但我添加後沒有效果。

          出現這個錯誤的根本原因是要顯示的圖像像素值超出了inshow（）函數的有效範圍【integers：[0,255];floats:[0,1]】，可以先print出現問題的圖像找出問題的根本原因，我的圖像打印爲：

tensor([[[-0.7804, -0.7804, -0.7882,  ...,  0.2706,  0.2549,  0.3020],
         [-0.7725, -0.7725, -0.7725,  ...,  0.2863,  0.2941,  0.2941],
         [-0.7725, -0.7725, -0.7647,  ...,  0.2235,  0.2706,  0.3098],
         ...,
         [ 0.2627,  0.2000,  0.1922,  ...,  0.2784,  0.2157,  0.2392],
         [ 0.3569,  0.3176,  0.3098,  ...,  0.2706,  0.1922,  0.2706],
         [ 0.3490,  0.3020,  0.3725,  ...,  0.2941,  0.2157,  0.2627]],

        [[-0.7804, -0.7804, -0.7882,  ...,  0.2706,  0.2549,  0.3020],
         [-0.7725, -0.7725, -0.7725,  ...,  0.2863,  0.2941,  0.2941],
         [-0.7725, -0.7725, -0.7647,  ...,  0.2235,  0.2706,  0.3098],
         ...,
         [ 0.2627,  0.2000,  0.1922,  ...,  0.2784,  0.2157,  0.2392],
         [ 0.3569,  0.3176,  0.3098,  ...,  0.2706,  0.1922,  0.2706],
         [ 0.3490,  0.3020,  0.3725,  ...,  0.2941,  0.2157,  0.2627]],

        [[-0.7804, -0.7804, -0.7882,  ...,  0.2706,  0.2549,  0.3020],
         [-0.7725, -0.7725, -0.7725,  ...,  0.2863,  0.2941,  0.2941],
         [-0.7725, -0.7725, -0.7647,  ...,  0.2235,  0.2706,  0.3098],
         ...,
         [ 0.2627,  0.2000,  0.1922,  ...,  0.2784,  0.2157,  0.2392],
         [ 0.3569,  0.3176,  0.3098,  ...,  0.2706,  0.1922,  0.2706],
         [ 0.3490,  0.3020,  0.3725,  ...,  0.2941,  0.2157,  0.2627]]])
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).

tensor([[[ 0.3647,  0.3647,  0.3882,  ...,  0.3255,  0.3176,  0.2941],
         [ 0.3647,  0.3804,  0.4039,  ...,  0.3176,  0.3569,  0.3647],
         [ 0.3490,  0.3412,  0.3725,  ...,  0.2784,  0.3255,  0.3333],
         ...,
         [ 0.2941,  0.3255,  0.2863,  ..., -0.1137, -0.5843, -0.6784],
         [ 0.2784,  0.2784,  0.2941,  ..., -0.1922, -0.6235, -0.6706],
         [ 0.2706,  0.2784,  0.2314,  ..., -0.3412, -0.6392, -0.6784]],

        [[ 0.3647,  0.3647,  0.3882,  ...,  0.3255,  0.3176,  0.2941],
         [ 0.3647,  0.3804,  0.4039,  ...,  0.3176,  0.3569,  0.3647],
         [ 0.3490,  0.3412,  0.3725,  ...,  0.2784,  0.3255,  0.3333],
         ...,
         [ 0.2941,  0.3255,  0.2863,  ..., -0.1137, -0.5843, -0.6784],
         [ 0.2784,  0.2784,  0.2941,  ..., -0.1922, -0.6235, -0.6706],
         [ 0.2706,  0.2784,  0.2314,  ..., -0.3412, -0.6392, -0.6784]],

        [[ 0.3647,  0.3647,  0.3882,  ...,  0.3255,  0.3176,  0.2941],
         [ 0.3647,  0.3804,  0.4039,  ...,  0.3176,  0.3569,  0.3647],
         [ 0.3490,  0.3412,  0.3725,  ...,  0.2784,  0.3255,  0.3333],
         ...,
         [ 0.2941,  0.3255,  0.2863,  ..., -0.1137, -0.5843, -0.6784],
         [ 0.2784,  0.2784,  0.2941,  ..., -0.1922, -0.6235, -0.6706],
         [ 0.2706,  0.2784,  0.2314,  ..., -0.3412, -0.6392, -0.6784]]])
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).

          可見我的程序報出警告的原因是待顯示圖像的像素值中出現了負值，不符合imshow（）函數的要求，添加了“img[img < 0] = 0”一句將小於0的部分置0後停止報錯。如果造成警告的是其他問題可以根據輸出的圖像情況修改，進行歸一化/剪裁等對應操作。

img = x[0]
img[img < 0] = 0
img = img.numpy()                   # FloatTensor轉爲ndarray
img = np.transpose(img, (1, 2, 0))  # 把channel那一維放到最後
plt.imshow(img)