常用scripts整理--2020.05.13

平時在進(jìn)行數(shù)據(jù)處理時，經(jīng)常會用到一些腳本文件，可以提高效率，我把自己常用到的進(jìn)行整理總結(jié)，希望可以有所幫助

1.批量修改圖片名字

#coding=utf-8 ''' code by zzg 2020-04-07 ''' import os import re import sys path = r"***自己的圖片文件夾" fileList = os.listdir(path) # 待修改文件夾 print("修改前：" + str(fileList)) # 輸出文件夾中包含的文件 os.chdir(path) # 將當(dāng)前工作目錄修改為待修改文件夾的位置 num = 0 # 名稱變量 for fileName in fileList: # 遍歷文件夾中所有文件pat = ".+.(jpg|jpeg|JPG)" # 匹配文件名正則表達(dá)式pattern = re.findall(pat, fileName) # 進(jìn)行匹配# print(pattern)print('num：', num, 'filename:', fileName)os.rename(fileName, ('1' + '_' + str(num) + '.'+ pattern[0])) # 文件重新命名num = num + 1 # 改變編號，繼續(xù)下一項 print("---------------------------------------------------") sys.stdin.flush() # 刷新 print("修改后：" + str(os.listdir(path))) # 輸出修改后文件夾中包含的文件

2.批量修改圖片大小

#coding=utf-8 ''' code by zzg 2020-04-07 ''' #提取目錄下所有圖片,更改尺寸后保存到另一目錄 from PIL import Image import os.path import globdef convertjpg(jpgfile,outdir,width=128,height=128):img=Image.open(jpgfile)try:new_img=img.resize((width,height),Image.BILINEAR) new_img.save(os.path.join(outdir,os.path.basename(jpgfile)))except Exception as e:print(e) for jpgfile in glob.glob("train/*.jpg"):convertjpg(jpgfile,"train01/")

3.批量打空標(biāo)簽

# coding:utf-8 ''' code by zzg 2020-04-04''' ##針對負(fù)樣本的圖片批量生成空白標(biāo)簽import os,sys import glob from PIL import Image import pdb# the direction/path of Image,Label src_img_dir = "images/" src_xml_dir = "xml/"img_Lists = glob.glob(src_img_dir + '/*.jpg') # print(img_Lists)img_basenames = [] for item in img_Lists:img_basenames.append(os.path.basename(item)) # print(img_basenames)img_name = [] for item in img_basenames:temp1, temp2 = os.path.splitext(item)img_name.append(temp1) # print(img_name)#pdb.set_trace() for img in img_name:im = Image.open((src_img_dir + '/' + img + '.jpg'))width, height = im.size#print(width)xml_file = open((src_xml_dir + '/' + img + '.xml'), 'w')xml_file.write('<annotation>n')xml_file.write('<folder>VOC2007</folder>n')xml_file.write('<filename>' +str(img) + '.jpg' + '</filename>n')xml_file.write('<source>n')xml_file.write('<database>' + 'Unknown' + '</database>n')xml_file.write('</source>n')xml_file.write('<size>n')xml_file.write('<width>' + str(width) + '</width>n')xml_file.write('<height>' + str(height) + '</height>n')xml_file.write('<depth>3</depth>n')xml_file.write('</size>n')#print(len(gt))xml_file.write('</annotation>')print("finshed convert!!")

4.批量xml轉(zhuǎn)json（一個文件夾下所有xml轉(zhuǎn)到對應(yīng)的json）

''' code by zzg 2020-05-13 ''' #批量修改文件夾下的xml為json并存儲到另一個文件夾import glob import xmltodict import jsonpath = 'xml/' path2 = 'json/'def pythonXmlToJson(path):xml_dir = glob.glob(path + '*.xml')# print(len(xml_dir))for x in xml_dir:with open(x) as fd:convertedDict = xmltodict.parse(fd.read())jsonStr = json.dumps(convertedDict, indent=1)print("jsonStr=",jsonStr)print(x.split('.')[0])json_file = x.split('.')[0].split('/')[-1] +'.json'with open(path2 + '/' + json_file, 'w') as json_file:json_file.write(jsonStr)print("xml_json finished!")print(len(xml_dir)) pythonXmlToJson(path)

5.批量修改圖片后綴（jpg-->JPG）

先在txt中編輯 ren *.JPG *.jpg 后改.txt為.bat

6.批量移動文件夾下的指定文件（比如xml和jpg混合，移出jpg）

code by zzg 2020-05-12 ''' #復(fù)制或者移動一個文件夾下的所有圖片或者其他指定文件到另一個文件夾 import os import shutil path = 'train/' new_path = 'image/' new_path1 = 'xml/' count = 0 for root, dirs, files in os.walk(path):for i in range(len(files)):#if (files[i][-3:] == 'jpg' or files[i][-3:] == 'JPG'):if (files[i][-3:] == 'xml'):count += 1file_path = root + '/' + files[i]new_file_path = new_path1 + '/' + files[i]shutil.copy(file_path, new_file_path)#shutil.move(file_path, new_file_path))print(count) print("move finished!!")

7.為圖片添加m*n的矩形格網(wǎng)

""" code by zzg --2020-05-27 """ ##為圖片添加m*n的矩形格網(wǎng) from PIL import Image from PIL import ImageDraw import osinput_img = r'resize1.jpg'# 生成格網(wǎng) (filepath,filename) = os.path.split(input_img) img = Image.open(input_img) img_d = ImageDraw.Draw(img) x_len, y_len = img.size x_step = x_len/13 y_step = y_len/13 print(x_len) print(y_len) x_len = int(x_len) x_step = int(x_step) y_len = int(y_len) y_step = int(y_step)for x in range(0, x_len, x_step):img_d.line(((x, 0), (x, y_len)), (0, 0, 0)) for y in range(0, y_len, y_step):j = y_len - y - 1img_d.line(((0, j), (x_len, j)), (0, 0, 0)) img.save(os.path.join(filepath,"grid1_13_"+filename) )# 為格網(wǎng)編碼 左下角開始 cnt = 1 for i in range(0,x_len,x_step):img_d.text((i,y_len-y_step), str(cnt).encode("utf8"),fill=(255,0,0))cnt+=1 cnt = 1 for j in range(y_step,y_len,y_step):z = y_len - jimg_d.text((0,z), str(cnt).encode("utf8"),fill=(255,0,0) )cnt+=1 img.save(os.path.join(filepath, "grid_geocoding_"+filename))

示例：

8.批量截取圖片指定內(nèi)容并保存以及重寫對應(yīng)的xml（或者用作批量修改圖片名字以及對應(yīng)的xml標(biāo)簽）

''' code by zzg 2020-05-30 ''' #!/usr/bin/python # -*- coding: UTF-8 -*- # get annotation object bndbox locationtry:import xml.etree.cElementTree as ET except ImportError:import xml.etree.ElementTree as ETimport os,sys import glob import cv2 from PIL import Image import matplotlib.pyplot as plt import pdb#the direction/path of Image,Label src_img_dir = "image" src_xml_dir = "xml" dst_img_dir = "image-crop" dst_xml_dir = "xml-crop"img_Lists = glob.glob(src_img_dir + '/*.jpeg') #print(img_Lists)img_basenames = [] for item in img_Lists:img_basenames.append(os.path.basename(item))#print(img_basenames)img_name = [] for item in img_basenames:temp1, temp2 = os.path.splitext(item)img_name.append(temp1)# print(img_name)cnt = 0 for img in img_name:# im0 = Image.open((src_img_dir + '/' + img + '.jpeg'))# print(type(im0))# width, height = im0.size# print(im0.size)#print(width)## read the scr_imageim = cv2.imread(src_img_dir + '/' + img + '.jpeg')# print(type(im))# print(im.shape)# width, height = im.shape[:2][::-1] ##get w and h# print(width, height)##read the scr_xmlAnotPath = src_xml_dir + '/' + img + '.xml'# print(AnotPath)tree = ET.ElementTree(file=AnotPath) # print(tree)root = tree.getroot()# print(root)ObjectSet = root.findall('object')ObjBndBoxSet = []ObjBndBoxSet1 = {} for Object in ObjectSet:ObjName = Object.find('name').textBndBox = Object.find('bndbox')x1 = int(BndBox.find('xmin').text)#-1 y1 = int(BndBox.find('ymin').text)#-1x2 = int(BndBox.find('xmax').text)#-1y2 = int(BndBox.find('ymax').text)#-1BndBoxLoc = [ObjName,x1,y1,x2,y2]# print(x1,y1,x2,y2)ObjBndBoxSet.append(BndBoxLoc) # if ObjName in ObjBndBoxSet:# ObjBndBoxSet1[ObjName].append(BndBoxLoc)#如果字典結(jié)構(gòu)中含有這個類別了，那么這個目標(biāo)框要追加到其值的末尾# else:# ObjBndBoxSet1[ObjName] = [BndBoxLoc]#如果字典結(jié)構(gòu)中沒有這個類別，那么這個目標(biāo)框就直接賦值給其值吧 print(ObjBndBoxSet)#get the face [name,x01,y01,x02,y02] = ObjBndBoxSet[0]# print(len(ObjBndBoxSet))width = x02 - x01height = y02 - y01img1 = cv2.rectangle(im,(x01,y01),(x02,y02),(255,0,0),2)img2 = im[y01:y02, x01:x02]# plt.imshow(img2)# plt.show()# save the crop-image in dst_cropcv2.imwrite(dst_img_dir + '/' + img + '.jpeg',img2)# rewrite xml to dst_xmlxml_file = open((dst_xml_dir + '/' + img + '.xml'), 'w')xml_file.write('<annotation>n')xml_file.write('<folder>VOC2007</folder>n')xml_file.write('<filename>' +str(img) + '.jpeg' + '</filename>n')xml_file.write('<size>n')xml_file.write('<width>' + str(width) + '</width>n')xml_file.write('<height>' + str(height) + '</height>n')xml_file.write('<depth>3</depth>n')xml_file.write('</size>n')print("===========start rewrite bndbox==============")for x in ObjBndBoxSet[1:]:# print(x)[classname,x1,y1,x2,y2] = x x1 = x1 - x01y1 = y1 - y01x2 = x2 - x01y2 = y2 - y01 xml_file.write('<object>n')xml_file.write('<name>' + classname + '</name>n')xml_file.write('<pose>Unspecified</pose>n')xml_file.write('<truncated>0</truncated>n')xml_file.write('<difficult>0</difficult>n')xml_file.write('<bndbox>n')xml_file.write('<xmin>' + str(x1) + '</xmin>n')xml_file.write('<ymin>' + str(y1) + '</ymin>n') xml_file.write('<xmax>' + str(x2) + '</xmax>n')xml_file.write('<ymax>' + str(y2) + '</ymax>n')xml_file.write('</bndbox>n')xml_file.write('</object>n') xml_file.write('</annotation>')cnt += 1print(cnt)print("=======================finished!===================")

9.轉(zhuǎn)csv為voc_xml格式，用于目標(biāo)檢測

CSV格式''' code by zzg-2020-06-02 ''' import os import numpy as np import codecs import pandas as pd import json from glob import glob import cv2 import shutil from sklearn.model_selection import train_test_split from IPython import embed#1.標(biāo)簽路徑 csv_file = "train.csv" saved_path = "VOC2007/" #保存路徑 image_save_path = "./JPEGImages/" image_raw_parh = "train/"#2.創(chuàng)建要求文件夾 if not os.path.exists(saved_path + "Annotations"):os.makedirs(saved_path + "Annotations") if not os.path.exists(saved_path + "JPEGImages/"):os.makedirs(saved_path + "JPEGImages/") if not os.path.exists(saved_path + "ImageSets/Main/"):os.makedirs(saved_path + "ImageSets/Main/")#3.獲取待處理文件 data = pd.read_csv(csv_file,header=None,index_col=False,names=['image_id','width','height','bbox','source'])##合并相同名字的行 data_lite = data[['image_id','bbox']] # print(data_lite) data_lite['bbox'] = data_lite['bbox'].apply(lambda x: ','+ x) data1 = data_lite.groupby(by='image_id').sum() # data1 = data_lite.groupby(by='image_id')['bbox'].sum() data1['bbox'] = data1['bbox'].apply(lambda x : x[1:]) data1 = data1[0:3373] ##去除最后一行標(biāo)簽 # print(data1)total_csv_annotations = {} for row in data1.itertuples():# print(row[0],row[1])total_csv_annotations[row[0]] = row[1]##適用于沒用行中沒有相同名字的csv # total_csv_annotations = {} # annotations = pd.read_csv(csv_file,header=None).values # print(annotations )# key = annotation[0].split(os.sep)[-1] # value = np.array(annotation[3:]) # value = value[0] # # print(key) # # print(type(value)) # # print(value) # # print(total_csv_annotations.keys())# # total_csv_annotations[key] = value # total = total_csv_annotations # print(total)#4.讀取標(biāo)注信息并寫入 xml # print(total_csv_annotations.items())count = 0 for filename,label in total_csv_annotations.items():#embed()# print(filename)count += 1print(count)height, width, channels = cv2.imread(image_raw_parh + filename + '.jpg').shape#embed()with codecs.open(saved_path + "Annotations/"+filename+'.xml',"w","utf-8") as xml:xml.write('<annotation>n')xml.write('t<folder>' + 'VOC2007' + '</folder>n')xml.write('t<filename>' + filename + '.jpg' + '</filename>n')xml.write('t<source>n')xml.write('tt<database>Unknown</database>n')xml.write('t</source>n')xml.write('t<size>n')xml.write('tt<width>'+ str(width) + '</width>n')xml.write('tt<height>'+ str(height) + '</height>n')xml.write('tt<depth>' + str(channels) + '</depth>n')xml.write('t</size>n')xml.write('tt<segmented>0</segmented>n')if isinstance(label,float):## 空白xml.write('</annotation>')continue# print(label)label = label.replace('[','').replace(']','').replace(' ', '').split(',')# print(label)box_cnt = len(label) // 4# print(label[3])for i in range(box_cnt):xmin = int(float(label[i*4]))ymin = int(float(label[i*4+1]))width = int(float(label[i*4+2]))height= int(float(label[i*4+3]))xmax = xmin + widthymax = ymin + height# classname = 'wheat'if xmax <= xmin:passelif ymax <= ymin:passelse:xml.write('t<object>n')xml.write('tt<name>'+'wheat'+'</name>n')xml.write('tt<pose>Unspecified</pose>n')xml.write('tt<truncated>1</truncated>n')xml.write('tt<difficult>0</difficult>n')xml.write('tt<bndbox>n')xml.write('ttt<xmin>' + str(xmin) + '</xmin>n')xml.write('ttt<ymin>' + str(ymin) + '</ymin>n')xml.write('ttt<xmax>' + str(xmax) + '</xmax>n')xml.write('ttt<ymax>' + str(ymax) + '</ymax>n')xml.write('tt</bndbox>n')xml.write('t</object>n')print(filename,xmin,ymin,xmax,ymax)xml.write('</annotation>')#5.split files for txt txtsavepath = saved_path + "ImageSets/Main/" ftrainval = open(txtsavepath+'/trainval.txt', 'w') # ftest = open(txtsavepath+'/test.txt', 'w') ftrain = open(txtsavepath+'/train.txt', 'w') fval = open(txtsavepath+'/val.txt', 'w') total_files = glob(saved_path+"./Annotations/*.xml") total_files = [i.split("/")[-1].split(".xml")[0] for i in total_files] #test_filepath = "" for file in total_files:ftrainval.write(file + "n")#6.move images to voc JPEGImages folder for image in glob(image_raw_parh+"/*.jpg"):shutil.copy(image,saved_path+image_save_path)train_files,val_files = train_test_split(total_files,test_size=0.15,random_state=42)for file in train_files:ftrain.write(file + "n") #val for file in val_files:fval.write(file + "n")ftrainval.close() ftrain.close() fval.close()

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