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医学图像预处理 1）搭建运行环境，运行Brain Tumor Detection代码中裁剪功能 预先安装好相关模块，安装Jupyter Notebook交互式计算环境 conda install jupyter 首先导入相关包 import tensorflow as tf from tensorflow.keras.layers import Conv2D, Input, ZeroPadding2D, BatchNormalization, Activation, MaxPooling2D, Flatten, Dense from tensorflow.keras.models import Model, load_model from tensorflow.keras.callbacks import TensorBoard, ModelCheckpoint from sklearn.model_selection import train_test_split from sklearn.metrics import f1_score from sklearn.utils import shuffle import cv2 import imutils import numpy as np import matplotlib.pyplot as plt import time from os import listdir %matplotlib inline 因为这里只是进行图形预处理，对Brain Tumor图片进行裁剪，主要用到的包是cv2, imutils, numpy, matplotlib....

1.jpg 2.jpg 1.对1.jpg 分别作灰度化, 模糊化处理. 代码如下 """ @Project: imageProcessing @Author: loyio @Date: 3/20/21 """ from PIL import Image, ImageFilter if __name__ == '__main__': # greyscale imgfileOne = "Sample/1" sample_img = Image.open(imgfileOne+".jpg").convert('L') sample_img.save(imgfileOne+"_processed_gray.jpg") # Blur # sample_img = Image.open(imgfileOne+".jpg").filter(ImageFilter.BLUR) sample_img = Image.open(imgfileOne+".jpg").filter(ImageFilter.BoxBlur(5)) sample_img.save(imgfileOne + "_processed_blur.jpg") 图片效果如下 灰度处理 模糊处理 2.对2.jpg生成手绘效果 代码如下 """ @Project: imageProcessing @Author: loyio @Date: 3/20/21 """ from PIL import Image, ImageFilter import numpy as np if __name__ == '__main__': # Paint imgfileTwo = "Sample/2" sample_img_ary = np....