dataset prepration

[BlcaKHat]

I have downloaded mrked object image datset from openImage. the annotation files is in the format( class_name x y, h w).
how do i convert this file into .xml file ?

[ankitAMD]

Use this file and generate xml file ......please change location in the given file. save the code in two python file .

File name ...........> gen_xml.py (first file)

import os
import cv2
from lxml import etree
import xml.etree.cElementTree as ET

def write_xml(folder, img, objects, tl, br, savedir):
if not os.path.isdir(savedir):
os.mkdir(savedir)

image = cv2.imread(img.path)
height, width, depth = image.shape

annotation = ET.Element('annotation')
ET.SubElement(annotation, 'folder').text = folder
ET.SubElement(annotation, 'filename').text = img.name
ET.SubElement(annotation, 'segmented').text = '0'
size = ET.SubElement(annotation, 'size')
ET.SubElement(size, 'width').text = str(width)
ET.SubElement(size, 'height').text = str(height)
ET.SubElement(size, 'depth').text = str(depth)
for obj, topl, botr in zip(objects, tl, br):
    ob = ET.SubElement(annotation, 'object')
    ET.SubElement(ob, 'name').text = obj
    ET.SubElement(ob, 'pose').text = 'Unspecified'
    ET.SubElement(ob, 'truncated').text = '0'
    ET.SubElement(ob, 'difficult').text = '0'
    bbox = ET.SubElement(ob, 'bndbox')
    ET.SubElement(bbox, 'xmin').text = str(topl[0])
    ET.SubElement(bbox, 'ymin').text = str(topl[1])
    ET.SubElement(bbox, 'xmax').text = str(botr[0])
    ET.SubElement(bbox, 'ymax').text = str(botr[1])

xml_str = ET.tostring(annotation)
root = etree.fromstring(xml_str)
xml_str = etree.tostring(root, pretty_print=True)
save_path = os.path.join(savedir, img.name.replace('jpeg', 'xml'))
with open(save_path, 'wb') as temp_xml:
    temp_xml.write(xml_str)

#below this line we test our code only on one image but above write_xml function we have to import in draw_box python file so we can convert the png file in xml file.

if name == 'main':
"""
for testing
"""

folder = '/home/assetone04/Music/Darkflow-object-detection-master/new_model_data/images'
img = [im for im in os.scandir('/home/assetone04/Music/Darkflow-object-detection-master/new_model_data/images') if '1' in im.name][0]
objects = ['solar_panel']
tl = [(10, 10)]
br = [(100, 100)]
savedir = '/home/assetone04/Music/Darkflow-object-detection-master/new_model_data/annotations'
write_xml(folder, img, objects, tl, br, savedir)

File name ...........> draw_box.py (New python file.)

import os
import matplotlib.pyplot as plt
import cv2
from matplotlib.widgets import RectangleSelector
from gen_xml import write_xml

global constants

img = None
tl_list = []
br_list = []
object_list = []

constants

image_folder = '/home/assetone04/Music/Darkflow-object-detection-master/new_model_data/images'
savedir = '/home/assetone04/Music/Darkflow-object-detection-master/new_model_data/annotations'
obj = 'solar_panel'

def line_select_callback(clk, rls):
global tl_list
global br_list
global object_list
tl_list.append((int(clk.xdata), int(clk.ydata)))
br_list.append((int(rls.xdata), int(rls.ydata)))
object_list.append(obj)

def onkeypress(event):
global object_list
global tl_list
global br_list
global img
if event.key == 'q': # if we click q than automatically it save where you given the path otherwise if we save through button on image viewer it did not generate the xml file.
#print(object_list)
write_xml(image_folder, img, object_list, tl_list, br_list, savedir)
tl_list = []
br_list = []
object_list = []
img = None

def toggle_selector(event):
toggle_selector.RS.set_active(True)

if name == 'main':
for n, image_file in enumerate(os.scandir(image_folder)):
img = image_file
fig, ax = plt.subplots(1, figsize=(10.5, 8))
#mngr = plt.get_current_fig_manager()
#mngr.window.setGeometry(250, 40, 800, 600)
image = cv2.imread(image_file.path)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
ax.imshow(image)

    toggle_selector.RS = RectangleSelector(
        ax, line_select_callback,
        drawtype='box', useblit=True,
        button=[1], minspanx=5, minspany=5,
        spancoords='pixels', interactive=True,
    )
    bbox = plt.connect('key_press_event', toggle_selector)
    key = plt.connect('key_press_event', onkeypress)
    plt.tight_layout()
    plt.show()
    plt.close(fig)