第一次作业：深度学习基础

2、代码训练

2.1 图像处理基本练习

1. 下载并显示图像

!wget https://raw.githubusercontent.com/summitgao/ImageGallery/master/yeast_colony_array.jpg

import matplotlib
import numpy as np
import matplotlib.pyplot as plt

import skimage
from skimage import data
from skimage import io

colony = io.imread('yeast_colony_array.jpg') print(type(colony)) print(colony.shape)

(406, 604, 3)

# Plot all channels of a real image
plt.subplot(121)
plt.imshow(colony[:,:,:])
plt.title('3-channel image')
plt.axis('off')

# Plot one channel only
plt.subplot(122)
plt.imshow(colony[:,:,0]) plt.title('1-channel image') plt.axis('off');

2. 读取并改变图像像素值

# Get the pixel value at row 10, column 10 on the 10th row and 20th column
camera = data.camera()
print(camera[10, 20])

# Set a region to black
camera[30:100, 10:100] = 0
plt.imshow(camera, 'gray')

153

# Set the first ten lines to black
camera = data.camera()
camera[:10] = 0
plt.imshow(camera, 'gray')

# Set to "white" (255) pixels where mask is True
camera = data.camera()
mask = camera < 80
camera[mask] = 255
plt.imshow(camera, 'gray')

# Change the color for real images
cat = data.chelsea()
plt.imshow(cat)

# Set brighter pixels to red
red_cat = cat.copy()
reddish = cat[:, :, 0] > 160
red_cat[reddish] = [255, 0, 0]
plt.imshow(red_cat)

# Change RGB color to BGR for openCV
BGR_cat = cat[:, :, ::-1]
plt.imshow(BGR_cat)

3. 转换图像数据类型

from skimage import img_as_float, img_as_ubyte
float_cat = img_as_float(cat)
uint_cat = img_as_ubyte(float_cat)

4. 显示图像直方图

img = data.camera()
plt.hist(img.ravel(), bins=256, histtype='step', color='black');

5. 图像分割

# Use colony image for segmentation
colony = io.imread('yeast_colony_array.jpg')

# Plot histogram
img = skimage.color.rgb2gray(colony)
plt.hist(img.ravel(), bins=256, histtype='step', color='black');

# Use thresholding
plt.imshow(img>0.5)