使用全局对比度标准化-Python pylearn2 [英] Using Global Contrast Normalization - Python pylearn2

问题描述

我正在尝试将我的图像输入此方法，但是当我尝试绘制图像时，它完全变成黑色.

Im attempting to input my image to this method, but when i try to draw the image, it comes totally black.

我尝试仅输入一张图像并输入整个MNIST数据集. 结果相同.

I tried inputing just one image and inputing the whole MNIST dataset. Same result.

https://github.com/lisa- lab/pylearn2/blob/master/pylearn2/expr/preprocessing.py

if GCN is True:
    trainingFolder = "../inputData/converted_training/GCN/"
    testingFolder = "../inputData/converted_testing/GCN/"

    img0 = (data[1,1:]).reshape((28,28)).astype('uint8')*255
    im = Image.fromarray(img0)
    im.show()

    #GCN#
    img_gcn = global_contrast_normalize(data)
    img_gcn_1 = Image.fromarray(img_gcn[1,1:].reshape((28,28)).astype('uint8')*255)
    img_gcn_1.show()

第二张图片img_gcn_1变黑了.

The second image, which is img_gcn_1 comes blacked.

我在做什么错?

推荐答案

您是否尝试形象化图像而不乘以255? 即

Have you tried to visualize the image without multiplying by 255? i.e.,

import matplotlib.pyplot as plt

img = img_gcn[:, 0]
img = img.reshape(28, 28, order='F')    
plt.imshow(img, cmap=plt.get_cmap('gray'))

我认为该程序应该有效.

I think that procedure should work.

这篇关于使用全局对比度标准化-Python pylearn2的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！