RuixuanZhang的博客

python实现ROA算子边缘检测算法讲解略代码import numpy as npimport cv2 as cvdef ROA(image_path, save_path, threshold): img = cv.imread(image_path) image = cv.cvtColor(img, cv.COLOR_RGB2GRAY) new = np.zeros((512, 512), dtype=np.float64) # 开辟存储空间 widt

python实现深度学习中多图像叠置输出讲解略代码from PIL import Imagedef add_alpha_channel(img): img = Image.open(img) img = img.convert('RGBA') # 更改图像透明度 # factor = 0.7 # img_blender = Image.new('RGBA', img.size, (0, 0, 0, 0)) # img = Image.blend(

批量下载sentinel精密轨道数据

from PIL import Imageimport osimport json# 获取四个值# TP：被模型预测为正类的正样本(预测道路且标签道路)# TN：被模型预测为负类的负样本（预测背景且真实背景）# FP：被模型预测为正类的负样本（预测道路但真实背景）# FN：被模型预测为负类的正样本（预测背景但真实道路）def get_vaslue(predict_folders_path, label_folders_path): # 加载文件夹 predict_fold

import osimport pandas as pddef writefilename2excel(folder_path, excel_path, txt_path): # 加载文件夹 folder = os.listdir(folder_path) file_list = [] # 文件名 satellite_list = [] # 卫星 sensor_list = [] # 传感器 longitude_list = [] # 中心经度

import osdef renaming(file): ext = os.path.splitext(file) if ext[1] == '.jpg': new_name = ext[0] + '.png' os.rename(file, new_name)def batch_opera(folder_path): folder = os.listdir(folder_path) for file in folder:

python实现图像固定尺寸批量缩放import cv2import osif __name__ == "__main__": path = r'' # 目标文件夹路径 folders = os.listdir(path) for folder in folders: folder_path = os.path.join(path, folder) img = cv2.imread(folder_path) print(img

import cv2import mathimport numpy as npimport osclass data_stength: def __init__(self, imgae, rows, cols, center=[0, 0]): self.src = imgae # 图像 self.rows = rows # 行尺寸 self.cols = cols # 列尺寸 self.center = center

python实现Excel内数据转存import xlrdimport xlwtdef excel_demo(path, new_path): book = xlrd.open_workbook(path) table = book.sheets()[0] rows = int(table.nrows) cols = int(table.ncols) print("excel_size:{}行{}列".format(rows, cols)) num

python实现文件夹中文件数目批量识别并导出预选文件夹名单为Excel讲解略代码import osimport xlwt# 将数据写入新文件 file_path为目标Excel（不存在时会自动创建）def data_write(file_path, datas): f = xlwt.Workbook() sheet1 = f.add_sheet(u'sheet1', cell_overwrite_ok=True) j = -1 sheet1.writ

python实现基于八方向判断的断裂连接讲解略代码''' 八方向连接算法'''import numpy as npimport matplotlib.image as mpimgfrom PIL import Imagedef compute_conv(fm, kernel, judge=None, kernel_num=3): [h, w] = fm.shape k = kernel_num r = int(k / 2) padding_fm =

python实现批量提取指定文件夹下同类型文件讲解略代码import osimport shutildef take_samefile(or_path, tar_path, tar_type): tar_path = tar_path if not os.path.exists(tar_path): os.makedirs(tar_path) path = or_path files = os.listdir(path) # 读取or_pat

python实现形态学操作（膨胀、侵蚀）讲解略代码import cv2import numpy as npdef dilate(image_path, save_path): pic = image_path src = cv2.imread(pic, cv2.IMREAD_UNCHANGED) kernel = np.ones((5, 5), np.uint8) # 初始化窗口 dilate = cv2.dilate(src, kernel) # 侵蚀操

python实现深度学习中原始图像与预测结果叠置输出讲解略代码from PIL import Imagedef add_alpha_channel(img): img = Image.open(img) img = img.convert('RGBA') # 更改图像透明度 # factor = 0.7 # img_blender = Image.new('RGBA', img.size, (0, 0, 0, 0)) # img = Image.

python实现对labelme_json_to_dataset内label批量提取讲解1、库：os，shutil2、代码效果：实现对labelme_json_to_dataset内label批量提取3、代码原理：用os.listdir()遍历文件同时用shutil.copy实现复制转存代码import osimport shutildef take_file_from_files_both_rename(or_path, tar_path): determination = o

python实现固定尺寸图像拼接讲解1、代码效果：固定尺寸图像拼接代码import osimport cv2import numpy as npdef joint(or_path, tar_path, size): determination = tar_path if not os.path.exists(determination): os.makedirs(determination) path = or_path folders =

python实现将原图裁剪为固定尺寸小图讲解1、代码效果：实现labelme_json_to dataset批量处理代码import numpy as npimport pandas as pdimport osimport torch as timport torchvision.transforms.functional as fffrom torch.utils.data import Datasetfrom PIL import Imageimport torchvision.

python实现labelme_json_to dataset批量处理讲解1、库：os2、代码效果：实现labelme_json_to dataset批量处理3、代码原理：os.system调用conda命令同时用os.listdir遍历代码import osdef labelme_bothall(path): path = path folders = os.listdir(path) folders_name = [] for folder in fol

python实现图像RGB拾取讲解1、库：PIL.Image2、代码效果：对指定图像内非背景RGB进行拾取3、代码原理：getpixel实现像素值拾取代码from PIL import Imagedef got_RGB(img_path): img = Image.open(img_path) width, height = img.size img = img.convert('RGB') array = [] for i in range(wid

Python实现文件夹分区讲解1、库：os，shutil.copy2、代码效果：对指定文件夹内文件等量分配到新的文件夹3、代码原理：用os.listdir()遍历文件同时用shutil.copy实现复制转存代码import osfrom shutil import copydef folder_segmentation(path, new_path): i = 0 k = 0 save_dir = new_path if not os.path.isdir

Python实现文件批量重命名讲解1、库：os2、代码效果：对指定文件夹内所有文件重命名为1，2，3…3、代码原理：使用os.listdir()遍历文件同时用os.rename()实现重命名代码import osdef reName(dirname): count = 0 for cur_file in os.listdir(dirname): count += 1 oldDir = os.path.join(dirname, cur_fil