vdalv/crop_classes.md

## crop_classes.md

      
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              crop_classes.md
            
          
    Export Class Images from PascalVOC Annotations

This script reads PascalVOC xml files, and crops the class instances into seperate image files.
Note: This script relies on ImageMagick for the crop (convert) functionality. It comes pre-installed on most recent versions of Ubuntu.
Disclaimer: This code is a modified version of Dat Tran's xml_to_csv.py
Example:

Let's say we have this image in our train folder:

And we annotate it like so:

Upon running the script, our train folder now looks like this:

And the class folders (head, leg) contain the following:

crop_classes.py:

import os
import glob
import subprocess
import xml.etree.ElementTree as ET

classes_dict = {}

def crop_classes(path):
    xml_list = []
    for xml_file in glob.glob(path + '/*.xml'):
        tree = ET.parse(xml_file)
        root = tree.getroot()
        for member in root.findall('object'):
            value = (root.find('filename').text,
                     member[0].text,
                     int(member[4][0].text),
                     int(member[4][1].text),
                     int(member[4][2].text),
                     int(member[4][3].text)
                     )
            class_name = member[0].text
            save_folder = path + "/" + class_name
            if not os.path.isdir(save_folder):
                os.makedirs(save_folder)
        
            if not class_name in classes_dict.keys():
                classes_dict[class_name] = 1;

            #http://www.imagemagick.org/Usage/crop/
            #convert -crop {x2 - x1}x{y2 - y1}+{x1}+{y1} {folder_name}/{image_name} {folder_name}/{class_name}/{class_name}-{count}-{image_name}
            call = ['convert', '-crop', str(value[4] - value[2]) + 'x' + str(value[5] - value[3]) + "+" + str(value[2]) + "+" + str(value[3]), path + "/" + value[0], save_folder + "/" + value[1] + "-" + str(classes_dict[class_name]) + "-" + value[0]]
            subprocess.call(call)

            classes_dict[class_name] += 1

def main():
    for folder_name in ['train', 'val']:
        image_path = os.path.join(os.getcwd(), folder_name)
        crop_classes(image_path)
        print('Successfully cropped classes in the ' + folder_name + ' folder.')

main()