export.py

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### Author/Developer: Nicolas CHEN
### Filename: export.py
### Version: 1.0
### Field of research: Deep Learning in medical imaging
### Purpose: This Python script creates the CSV file from XML files.
### Output: This Python script creates the file "test.csv"
### with all data needed: filename, class_name, x1,y1,x2,y2

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### HISTORY
### Version | Date          | Author       | Evolution 
### 1.0     | 17/11/2018    | Nicolas CHEN | Initial version 
######################################################################################

import os, sys, random
import xml.etree.ElementTree as ET
from glob import glob
import pandas as pd
from shutil import copyfile

annotations = glob('BCCD/Annotations/*.xml')

df = []
cnt = 0
for file in annotations:
    #filename = file.split('/')[-1].split('.')[0] + '.jpg'
    #filename = str(cnt) + '.jpg'
    filename = file.split('\\')[-1]
    filename =filename.split('.')[0] + '.jpg'
    row = []
    parsedXML = ET.parse(file)
    for node in parsedXML.getroot().iter('object'):
        blood_cells = node.find('name').text
        xmin = int(node.find('bndbox/xmin').text)
        xmax = int(node.find('bndbox/xmax').text)
        ymin = int(node.find('bndbox/ymin').text)
        ymax = int(node.find('bndbox/ymax').text)

        row = [filename, blood_cells, xmin, xmax, ymin, ymax]
        df.append(row)
        cnt += 1

data = pd.DataFrame(df, columns=['filename', 'cell_type', 'xmin', 'xmax', 'ymin', 'ymax'])

data[['filename', 'cell_type', 'xmin', 'xmax', 'ymin', 'ymax']].to_csv('test.csv', index=False)