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[Doc]: add document about how python read images
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| - [读取并显示图像](#读取并显示图像) | ||
| - [opencv3库](#opencv3库) | ||
| - [scikit-image库](#scikit-image库) | ||
| - [PIL库](#pil库) | ||
| - [读取图像结果分析](#读取图像结果分析) | ||
| - [打印图像信息](#打印图像信息) | ||
| - [skimage获取图像信息](#skimage获取图像信息) | ||
| - [PIL获取图像信息](#pil获取图像信息) | ||
| - [读取并显示图像方法总结](#读取并显示图像方法总结) | ||
| - [PIL库读取图像](#pil库读取图像) | ||
| - [Opencv3读取图像](#opencv3读取图像) | ||
| - [scikit-image库读取图像](#scikit-image库读取图像) | ||
| - [参考资料](#参考资料) | ||
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| 学习数字图像处理，第一步就是读取图像。这里我总结下如何使用 opencv3,scikit-image, PIL 图像处理库读取图片并显示。 | ||
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| ## 读取并显示图像 | ||
| ### opencv3库 | ||
| opencv 读取图像，返回的是矩阵数据，RGB 图像的 shape 是 (height, weight, channel)，dtype 是 uint8。 | ||
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| 示例代码如下： | ||
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| ```python | ||
| import cv2 | ||
| # 读入一副彩色图像 | ||
| img_cv2 = cv2.imread('test.jpg',cv2.IMREAD_COLOR) | ||
| # 打印图像尺寸,形状，图像元素数据类型 | ||
| print(type(img_cv2)) | ||
| print(img_cv2.shape) # (height, width, channel) | ||
| print(img_cv2.dtype) # uint8 | ||
| # matplotlib绘制显示图像 | ||
| plt.figure(1) | ||
| plt.imshow(img_PIL) | ||
| plt.show() | ||
| # cv2绘制显示图像 | ||
| # cv2.imshow() | ||
| # cv2.namedWindow('image', cv2.WINDOW_NORMAL) | ||
| # cv2.imshow('image',img_cv2) | ||
| # cv2.waitKey(0) | ||
| # cv2.destroyAllWindows() | ||
| ``` | ||
| ### scikit-image库 | ||
| 示例代码如下： | ||
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| ```python | ||
| from skimage import io | ||
| img_skimage = io.imread('test.jpg') | ||
| # 打印图像尺寸 | ||
| print(img_skimage.shape) #(height, width, channel) | ||
| # 绘制显示图像 | ||
| io.imshow(img_skimage) | ||
| # import matplotlib.pyplot as plt | ||
| # plt.imshow(img_skimage) | ||
| ``` | ||
| 注意：io.imshow(img\_skimage)，这一行代码的实质是利用matplotlib包对图片进行绘制，绘制成功后，返回一个matplotlib类型的数据。也就是说scikit-image库对图像的绘制实际上是调用了matplotlib库imshow显示函数。 | ||
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| cv2和skimage读取图像，图像的尺寸可以通过其shape属性来获取，shape返回的是一个tuple元组，第一个元素表示图像的高度，第二个表示图像的宽度，第三个表示像素的通道数。 | ||
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| ### PIL库 | ||
| 示例代码如下： | ||
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| ```python | ||
| # PIL库读取绘制显示图像 | ||
| # plt 用于显示图片 | ||
| from PIL import Image | ||
| import matplotlib.pyplot as plt | ||
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| import numpy as np | ||
| img_PIL = Image.open('test.jpg') | ||
| img_PIL = np.array(img_PIL) | ||
| # 打印图像类型,尺寸和总像素个数 | ||
| print(type(img_PIL)) # <class 'numpy.ndarray'> | ||
| print(img_PIL.shape) # (height, width, channel), (1200, 1793, 3) | ||
| print(img_PIL.size) # 6454800 = 1200*1793*3 | ||
| # 绘制显示图像 | ||
| plt.figure(1) | ||
| plt.imshow(img_PIL) | ||
| plt.show() | ||
| ``` | ||
| ### 读取图像结果分析 | ||
| 分别用Opnecv3和sckit-image读取图像，并用matplotlib库显示。示例代码如下： | ||
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| ```python | ||
| import cv2 | ||
| from skimage import io | ||
| import matplotlib.pyplot as plt | ||
| img_cv2 = cv2.imread('test.jpg',cv2.IMREAD_COLOR) | ||
| img_skimage = io.imread('test.jpg') | ||
| # matplotlib显示cv2库读取的图像 | ||
| plt.figure('imread picture',figsize=(25,25)) | ||
| plt.subplot(121) | ||
| plt.title('cv2 imread picture') | ||
| plt.imshow(img_cv2) | ||
| # matplotlib显示skimage库读取的图像 | ||
| plt.subplot(122) | ||
| plt.title('skimage imread picture') | ||
| plt.imshow(img_skimage) | ||
| # 打印图像尺寸,总像素个数,和图像元素数据类型 | ||
| print(img_cv2.shape) | ||
| print(img_cv2.size) | ||
| print(img_cv2.dtype) | ||
| ``` | ||
|  | ||
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| 通过以上输出结果对比图，我们会发现，matplotlib绘制显示的cv2库读取的图像与原图有所差别，这是因为opencv3库读取图像的通道时BGR，而正常图像读取的通道都是RGB，matplotlib库显示图像也是按照RGB顺序通道来的，解释完毕。 | ||
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| 一点疑惑，我通过查询库函数可知plt.show()第一个参数为要显示的对象（array\_like），字面意思理解为类似数组的对象，但是很明显，PIL库返回的不是’numpy.ndarray’对象，而是’PIL.JpegImagePlugin.JpegImageFile’对象，那为什么plt.show()函数还是能显示Image.open()函数读取图像返回的结果呢？ | ||
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| 程序如下图所示： | ||
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|  | ||
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| ## 打印图像信息 | ||
| 图像常用信息有图像尺寸，像素个数，通道数等。 | ||
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| ### skimage获取图像信息 | ||
| **注意：scikit-image 库读取和缩放图像速度要慢 opencv 库 近 4 倍。** | ||
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| ```Plain Text | ||
| from skimage import io, data | ||
| # create coffee image, return (300, 451, 3) uint8 ndarray | ||
| img = data.coffee() | ||
| io.imshow(img) # 显示图片 | ||
| print(type(img)) # 显示类型 | ||
| print(img.dtype) # 显示图像元素数据类型 | ||
| print(img.shape) # 显示尺寸 | ||
| print(img.shape[0]) # 图片高度 | ||
| print(img.shape[1]) # 图片宽度 | ||
| print(img.shape[2]) # 图片通道数 | ||
| print(img.size) # 显示总像素个数=shape[0]*shape[1]*shape[2] | ||
| print(img.max()) # 最大像素值 | ||
| print(img.min()) # 最小像素值 | ||
| print(img.mean()) # 像素平均值 | ||
| print(img[0][0]) # 图像第一行第一列的像素值 | ||
| ``` | ||
| 输出结果如下图： | ||
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|  | ||
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| ### PIL获取图像信息 | ||
| ```Plain Text | ||
| # 获取PIL image图片信息 | ||
| im = Image.open('test.jpg') | ||
| print (type(im)) | ||
| print (im.size) #图片的尺寸 | ||
| print (im.mode) #图片的模式 | ||
| print (im.format) #图片的格式 | ||
| print (im.getpixel((0,0)))#得到像素： | ||
| # img读出来的图片获得某点像素用getpixel((w,h))可以直接返回这个点三个通道的像素值 | ||
| ``` | ||
| 输出结果如下： | ||
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| plt.show函数定义如下： | ||
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| > Signature: plt.imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=None, filternorm=1, filterrad=4.0, imlim=None, resample=None, url=None, hold=None, data=None, \*\*kwargs) | ||
| Docstring: | ||
| Display an image on the axes. | ||
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| > Parameters | ||
| ———- | ||
| X : array\_like, shape (n, m) or (n, m, 3) or (n, m, 4). Display the image in XX to current axes. XX may be an array or a PIL image. If XX is an array, it can have the following shapes and types: | ||
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| > – MxN — values to be mapped (float or int) | ||
| – MxNx3 — RGB (float or uint8) | ||
| – MxNx4 — RGBA (float or uint8) | ||
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| > The value for each component of MxNx3 and MxNx4 float arrays should be in the range 0.0 to 1.0. MxN arrays are mapped to colors based on the ∥∥∥∥ (mapping scalar to scalar) and the cmapcmap (mapping the normed scalar to a color). | ||
| ## 读取并显示图像方法总结 | ||
| ### PIL库读取图像 | ||
| > PIL.Image.open + numpy | ||
| scipy.misc.imread | ||
| scipy.ndimage.imread | ||
| 这些方法都是通过调用PIL.Image.open 读取图像的信息； | ||
| **PIL.Image.open 不直接返回numpy对象**，可以用numpy提供的函数进行转换，参考Image和Ndarray互相转换； | ||
| scipy.ndimage.imread直接返回numpy.ndarray对象，通道顺序为RGB，通道值得默认范围为0-255。 | ||
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| ### Opencv3读取图像 | ||
| > cv2.imread: 使用opencv读取图像，直接返回numpy.ndarray 对象，通道顺序为BGR ，注意是**BGR**，通道值默认范围0-255。 | ||
| ### scikit-image库读取图像 | ||
| > skimage.io.imread: 直接返回numpy.ndarray 对象，通道顺序为RGB，通道值默认范围0-255。 | ||
| ### 参考资料 | ||
| * [https://blog.csdn.net/renelian1572/article/details/78761278](https://blog.csdn.net/renelian1572/article/details/78761278) | ||
| * [https://pillow.readthedocs.io/en/5.3.x/index.html](https://pillow.readthedocs.io/en/5.3.x/index.html) | ||
| * [http://scikit-image.org/docs/stable/user\_guide.html](http://scikit-image.org/docs/stable/user_guide.html) |
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