Upload bounding boxes Pascal VOC along with IMG files - google-cloud-ml

Question

While uploading the IMG files, I am thinking about uploading the respective bounding box data as well through Pascal VOC files. How can I do that on Vertex AI or do I need to do any transformation of the Pascal VOC data?

Answer 1

You can do object detection using AutoML Vision which is available for Vertex-AI.
Preparing training dataset for Object detection in AutoML Vision requires your data to be in .csv format.
You can refer to this link to convert your Pascal VOC files to Cloud AutoML Vision csv.
To prepare and format data for object detection:
Prepare your training data according to the supported image files and
bounding box requirements mentioned here.
After preparing training data you can then create a CSV file with bounding boxes. Doc
For more details on how to build object detection models on AutoML Vision follow this quickstart.

Answer 2

You can refer to this link to convert your Pascal VOC files to Cloud
AutoML Vision csv.
This requires upgraded membership of roboflow.com. Following code serves the purpose locally on your machine!
Note: It requires you to have your images and annotations (xml files) stored on a GCS bucket.
from google.cloud import storage
import os
import csv
import xml.etree.ElementTree as ET
os.environ['GOOGLE_APPLICATION_CREDENTIALS']= 'path-to-credentials-json-file'
bucket_name = 'your-bucket-name'
client = storage.Client()
bucket = client.get_bucket(bucket_name)
blobs = client.list_blobs(bucket_name,prefix=None,delimiter='/')
#download all xmls files to local directory or one can paste all the xmls in current working directory and comment downloading part
print('Downloading xml files...')
xml_files = [blob.name for blob in blobs if blob.name.endswith('.xml')]
[bucket.blob(xml).download_to_filename(xml) for xml in xml_files]
allowed_extensions = ['jpg','png','jpeg','gif','bmp','ico']
csv_file_name = 'vertex_ai_annos.csv'
csvfile = open(csv_file_name,'w', newline='')
csvwriter = csv.writer(csvfile, escapechar=' ', quoting=csv.QUOTE_NONE)
blobs = client.list_blobs(bucket_name,prefix=None,delimiter='/') #reinitialize list_blobs iterator
for blob in blobs:
ext = blob.name.split('.')[-1]
if ext in allowed_extensions:
tree = ET.parse(f"{blob.name.split('.')[0]}.xml")
width = int(tree.find('size').find('width').text)
height = int(tree.find('size').find('height').text)
objs = tree.findall('object')
for obj in objs:
label = obj.find('name').text
xmin = int(obj.find('bndbox').find('xmin').text)/width
ymin = int(obj.find('bndbox').find('ymin').text)/height
xmax = int(obj.find('bndbox').find('xmax').text)/width
ymax = int(obj.find('bndbox').find('ymax').text)/height
data = f"gs://{bucket_name}/{blob.name},{label},{xmin},{ymin},,,{xmax},{ymax},,"
# print(data)
csvwriter.writerow([f'gs://{bucket_name}/{blob.name},{label},{xmin},{ymin},,,{xmax},{ymax},,'])
print(f'{csv_file_name} has been created!')