Visualize the .xml annotations in python

Visualization of the bounding boxes using the .xml annotations of PASCAL VOC format

Clone the repo:

git clone https://github.com/Piyush-Kulkarni/Visualize-the-XML-annotations.git

Organize the data:

1. Images (All the images)
2. Annotations (All the .xml annotations)
3. Visualization (Output folder for images with Bounding Boxes)

Replace the path for the following three variables: image_path, annotation_path & flag

import os
import cv2
import  xml.dom.minidom
 
image_path="C:/Users/piyus/Documents/ObjectDetectionUdemy/PascalVOC-to-Images/data/images/"
annotation_path="C:/Users/piyus/Documents/ObjectDetectionUdemy/PascalVOC-to-Images/data/annotations/"
 
files_name = os.listdir(image_path)
for filename_ in files_name:
	filename, extension= os.path.splitext(filename_)
	img_path =image_path+filename+'.jpg'
	xml_path =annotation_path+filename+'.xml'
	print(img_path)
	img = cv2.imread(img_path)
	if img is None:
		pass
	dom = xml.dom.minidom.parse(xml_path)
	root = dom.documentElement
	objects=dom.getElementsByTagName("object")
	print(objects)
	i=0
	for object in objects:
        
		bndbox = root.getElementsByTagName('bndbox')[i]
		xmin = bndbox.getElementsByTagName('xmin')[0]
		ymin = bndbox.getElementsByTagName('ymin')[0]
		xmax = bndbox.getElementsByTagName('xmax')[0]
		ymax = bndbox.getElementsByTagName('ymax')[0]
		xmin_data=xmin.childNodes[0].data
		ymin_data=ymin.childNodes[0].data
		xmax_data=xmax.childNodes[0].data
		ymax_data=ymax.childNodes[0].data
		print(object)        
		print(xmin_data)
		print(ymin_data)
        
		i= i +1 
		cv2.rectangle(img,(int(xmin_data),int(ymin_data)),(int(xmax_data),int(ymax_data)),(55,255,155),5)
	flag=0
	flag=cv2.imwrite("C:/Users/piyus/Documents/ObjectDetectionUdemy/PascalVOC-to-Images/data/Visualization/{}.jpg".format(filename),img)
	if(flag):
		print(filename,"done")
print("all done ====================================")

This visualization could be useful to check the training or testing data is rightly annotated for Object Detection task.

To learn more: check out

Written by:

Piyush Kulkarni

(Data Scientist)