python目标检测给图画框,bbox画到图上并保存案例

import os
import xml.dom.minidom
import cv2 as cv
 
ImgPath = 'C:/Users/49691/Desktop/gangjin/gangjin_test/JPEGImages/'
AnnoPath = 'C:/Users/49691/Desktop/gangjin/gangjin_test/Annotations/' #xml文件地址
save_path = ''
def draw_anchor(ImgPath,AnnoPath,save_path):
  imagelist = os.listdir(ImgPath)
  for image in imagelist:
 
    image_pre, ext = os.path.splitext(image)
    imgfile = ImgPath + image
    xmlfile = AnnoPath + image_pre + '.xml'
    # print(image)
    # 打开xml文档
    DOMTree = xml.dom.minidom.parse(xmlfile)
    # 得到文档元素对象
    collection = DOMTree.documentElement
    # 读取图片
    img = cv.imread(imgfile)
 
    filenamelist = collection.getElementsByTagName("filename")
    filename = filenamelist[0].childNodes[0].data
    print(filename)
    # 得到标签名为object的信息
    objectlist = collection.getElementsByTagName("object")
 
    for objects in objectlist:
      # 每个object中得到子标签名为name的信息
      namelist = objects.getElementsByTagName('name')
      # 通过此语句得到具体的某个name的值
      objectname = namelist[0].childNodes[0].data
 
      bndbox = objects.getElementsByTagName('bndbox')
      # print(bndbox)
      for box in bndbox:
        x1_list = box.getElementsByTagName('xmin')
        x1 = int(x1_list[0].childNodes[0].data)
        y1_list = box.getElementsByTagName('ymin')
        y1 = int(y1_list[0].childNodes[0].data)
        x2_list = box.getElementsByTagName('xmax')  #注意坐标，看是否需要转换
        x2 = int(x2_list[0].childNodes[0].data)
        y2_list = box.getElementsByTagName('ymax')
        y2 = int(y2_list[0].childNodes[0].data)
        cv.rectangle(img, (x1, y1), (x2, y2), (255, 255, 255), thickness=2)
        cv.putText(img, objectname, (x1, y1), cv.FONT_HERSHEY_COMPLEX, 0.7, (0, 255, 0),
              thickness=2)
        # cv.imshow('head', img)
        cv.imwrite(save_path+'/'+filename, img)  #save picture

000004 0.972 302.8 94.5 512.0 150.0
000004 0.950 348.1 166.1 512.0 242.9
000004 0.875 1.0 25.7 292.6 126.3
000004 0.730 1.0 138.5 488.3 230.0
000004 0.699 1.0 120.9 145.5 139.9
000004 0.592 54.4 227.4 431.9 343.4
000004 0.588 1.0 159.8 18.8 231.6
000004 0.126 1.0 247.1 342.3 270.0
000004 0.120 1.0 225.4 185.7 309.3

import os
import os.path
import numpy as np
import xml.etree.ElementTree as xmlET
from PIL import Image, ImageDraw
import cPickle as pickle 

txt_name = 'comp4_8a226fd7-753d-40fc-8013-f68d2a465579_det_test_ship.txt'
file_path_img = '/home/JPEGImages'
save_file_path = '/home/detect_results'


source_file = open(txt_name)

img_names = []
for line in source_file:
  staff = line.split()
  img_name = staff[0]
  img_names.append(img_name)

name_dict = {}
for i in img_names:
  if img_names.count(i) 0:
    name_dict[i] = img_names.count(i) 

source_file.close()

source_file = open(txt_name)
for idx in name_dict:
  img = Image.open(os.path.join(file_path_img, idx + '.jpg')) 
  draw = ImageDraw.Draw(img)
  for i in xrange(name_dict[idx]):
    line = source_file.readline()
    staff = line.split()
    score = staff[1]
    box = staff[2:6]
    draw.rectangle([int(np.round(float(box[0]))), int(np.round(float(box[1]))), 
          int(np.round(float(box[2]))), int(np.round(float(box[3])))], outline=(255, 0, 0))
  img.save(os.path.join(save_file_path, idx + '.jpg')) 

source_file.close()