CODE EXAMPLE FOR PYTHON

delet categories from coco dataset

from pycocotools.coco import COCO
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
import os
from os.path import join
from tqdm import tqdm
import json

class coco_category_filter:
 """
 Downloads images of one category & filters jsons 
 to only keep annotations of this category
 """
 def __init__(self, json_path, imgs_dir, categ='person'):
     self.coco = COCO(json_path) # instanciate coco class
     self.json_path = json_path
     self.imgs_dir = imgs_dir
     self.categ = categ
     self.images = self.get_imgs_from_json()        
     
 def get_imgs_from_json(self):
     """returns image names of the desired category"""
     # instantiate COCO specifying the annotations json path
     # Specify a list of category names of interest
     catIds = self.coco.getCatIds(catNms=[self.categ])
     print("catIds: ", catIds)
     # Get the corresponding image ids and images using loadImgs
     imgIds = self.coco.getImgIds(catIds=catIds)
     images = self.coco.loadImgs(imgIds)
     print(f"{len(images)} images in '{self.json_path}' with '{self.categ}' instances")
     self.catIds = catIds # list
     return images
 
 def save_imgs(self):
     """saves the images of this category"""
     print("Saving the images with required categories ...")
     os.makedirs(self.imgs_dir, exist_ok=True)
     # Save the images into a local folder
     ################################################# Modified lines
     session = requests.Session()
     retry = Retry(connect=3, backoff_factor=0.5)
     adapter = HTTPAdapter(max_retries=retry)
     session.mount('http://', adapter)
     session.mount('https://', adapter)
     #################################################
     for im in tqdm(self.images):
         img_data = session.get(im['coco_url']).content
         with open(os.path.join(self.imgs_dir, im['file_name']), 'wb') as handler:
             handler.write(img_data)
 
 def filter_json_by_category(self, new_json_path):
     """creates a new json with the desired category"""
     # {'supercategory': 'person', 'id': 1, 'name': 'person'}
     ### Filter images:
     print("Filtering the annotations ... ")
     json_parent = os.path.split(new_json_path)[0]
     os.makedirs(json_parent, exist_ok=True)
     imgs_ids = [x['id'] for x in self.images] # get img_ids of imgs with the category
     new_imgs = [x for x in self.coco.dataset['images'] if x['id'] in imgs_ids]
     catIds = self.catIds
     ### Filter annotations
     new_annots = [x for x in self.coco.dataset['annotations'] if x['category_id'] in catIds]
     ### Reorganize the ids
     new_imgs, annotations = self.modify_ids(new_imgs, new_annots)
     ### Filter categories
     new_categories = [x for x in self.coco.dataset['categories'] if x['id'] in catIds]
     print("new_categories: ", new_categories)
     data = {
         "info": self.coco.dataset['info'],
         "licenses": self.coco.dataset['licenses'],
         "images": new_imgs, 
         "annotations": new_annots,
         "categories": new_categories 
         }
     print("saving json: ")
     with open(new_json_path, 'w') as f:
         json.dump(data, f)

 def modify_ids(self, images, annotations):
     """
     creates new ids for the images. I.e., reorganizes the ids and returns the dictionaries back
     images: list of images dictionaries
     imId_counter: image id starting from one (each dicto will start with id of last json +1)
     """
     print("Reinitialicing images and annotation IDs ...")
     ### Images
     old_new_imgs_ids = {}  # necessary for the annotations!
     for n,im in enumerate(images):
         old_new_imgs_ids[images[n]['id']] = n+1  # dicto with old im_ids and new im_ids
         images[n]['id'] = n+1 # reorganize the ids
     ### Annotations
     for n,ann in enumerate(annotations):
         annotations[n]['id'] = n+1
         old_image_id = annotations[n]['image_id']
         annotations[n]['image_id'] = old_new_imgs_ids[old_image_id]  # replace im_ids in the annotations as well
     return images, annotations


def main(subset, year, root_dir, category='person'):
 json_file = join(os.path.split(root_dir)[0], 'instances_'+subset+year+'.json')   # local path
 imgs_dir = join(root_dir, category + '_' + subset)
 new_json_file = join(root_dir, 'annotations', subset+".json")
 coco_filter = coco_category_filter(json_file, imgs_dir, categ=category) # instanciate class
 coco_filter.save_imgs()
 coco_filter.filter_json_by_category(new_json_file)


if __name__ == '__main__':
 subset, year='train', '2017'
 root_dir = './datasets/COCO/annotations'
 main(subset, year, root_dir, category='person')