出现Fail to create pixmap with Tk_GetPixmap in TkImgPhotoInstanceSetSize报错问题

Question

进行深度学习（特征可视化部分）学习时，出现的这个报错。

                                                #卷积神经网络的可视化（中间激活的可视化）
#载入训练好的模型
model = load_model('datas of cats and dogs.h5')
#输入目标图像
img_path = 'C:/Users/10175/Desktop/learning/deep learning/datas of cats and dogs/test/cats/cat.1700.jpg'
#图像预处理
img = image.load_img(img_path, target_size=(150, 150))
img_tensor = image.img_to_array(img)
img_tensor = np.expand_dims(img_tensor, axis=0)
img_tensor /= 255.
#提取模型前8层的输出
from keras import models
layer_outputs = [layer.output for layer in model.layers[:8]]
activation_model = models.Model(inputs=model.input, outputs=layer_outputs)
activations = activation_model.predict(img_tensor)
#将每个中间激活的所有通道特征可视化
layer_names = []
for layer in model.layers[:8]:
    layer_names.append(layer.name)
images_per_row = 16
for layer_name, layer_activation in zip(layer_names, activations):
    n_features = layer_activation.shape[-1]
    size = layer_activation.shape[1]
    n_cols = n_features // images_per_row
    display_grid = np.zeros((size * n_cols, images_per_row * size))
    for col in range(n_cols):
        for row in range(images_per_row):
            channel_image = layer_activation[0, :, :, col * images_per_row + row]
            channel_image -= channel_image.mean()
            channel_image /= channel_image.std()
            channel_image *= 64
            channel_image += 128
            channel_image = np.clip(channel_image, 0, 255).astype('uint8')
            display_grid[col * size: (col + 1) * size, row * size: (row + 1) * size] = channel_image
            scale = 1. / size
            plt.figure(figsize=(scale * display_grid.shape[1], scale * display_grid.shape[0]))
            plt.title(layer_name)
            plt.grid(False)
            plt.imshow(display_grid, aspect='auto', cmap='viridis')

报错内容：Fail to create pixmap with Tk_GetPixmap in TkImgPhotoInstanceSetSize

Answer 1

这个可能是图片数据有问题，具体得分析是图片尺寸大小还是格式问题