Python

!ls Histogram and RoI.ipynb axon02.tif test.jpg Question 2.1 .ipynb cell_nucleus.tif axon01.tif roi.tif from PIL import Image import numpy as np from PIL import ImageOps import matplotlib.pyplot as plt # 打开图片并转换成灰度图 im = Image.open('axon01.tif').convert('L') # 反转颜色 im = ImageOps.invert(im) # display in macOS /Applications/Preview.app # im.show() # display in Jupyter Notebook im ​ ​ # 将灰度...

数据预处理 import matplotlib.pyplot as plt import glob from PIL import Image import numpy as np import cv2 # 训练集图像 img_paths = glob.glob('./../data/vesselseg/DRIVE/training/images/*.tif') img_paths.sort() img_paths ['./../data/vesselseg/DRIVE/training/images/21_training.tif', './../data/vesselseg/DRIVE/training/images/22_training.tif', './../data/vesselseg/DRIVE/training/images/23_training.tif', './../data/vesselseg/DRIVE/training/images/24_training.tif', './../data/vesselseg/DRIVE/training/images/25_training.tif', './../data/vesselseg/DRIVE/training/images/26_training.tif', './../data/vesselseg/DRIVE/training/images/27_training.tif', './../data/vesselseg/DRIVE/training/images/28_training.tif', './../data/vesselseg/DRIVE/training/images/29_training.tif', './../data/vesselseg/DRIVE/training/images/30_training.tif', './../data/vesselseg/DRIVE/training/images/31_training.tif', './../data/vesselseg/DRIVE/training/images/32_training.tif', './../data/vesselseg/DRIVE/training/images/33_training.tif', './../data/vesselseg/DRIVE/training/images/34_training.tif', './../data/vesselseg/DRIVE/training/images/35_training.tif', './../data/vesselseg/DRIVE/training/images/36_training.tif', './../data/vesselseg/DRIVE/training/images/37_training.tif', './../data/vesselseg/DRIVE/training/images/38_training.tif', './../data/vesselseg/DRIVE/training/images/39_training.tif', './../data/vesselseg/DRIVE/training/images/40_training.tif'] 查看不同通道 # 读取其中一张图像 rgb_img = Image.open(img_paths[0])...