Spaces:
Runtime error
Runtime error
#!/usr/bin/env python3 | |
# -*- coding: utf-8 -*- | |
# Copyright (c) Facebook, Inc. and its affiliates. | |
import copy | |
import json | |
import os | |
from collections import defaultdict | |
# This mapping is extracted from the official LVIS mapping: | |
# https://github.com/lvis-dataset/lvis-api/blob/master/data/coco_to_synset.json | |
COCO_SYNSET_CATEGORIES = [ | |
{"synset": "person.n.01", "coco_cat_id": 1}, | |
{"synset": "bicycle.n.01", "coco_cat_id": 2}, | |
{"synset": "car.n.01", "coco_cat_id": 3}, | |
{"synset": "motorcycle.n.01", "coco_cat_id": 4}, | |
{"synset": "airplane.n.01", "coco_cat_id": 5}, | |
{"synset": "bus.n.01", "coco_cat_id": 6}, | |
{"synset": "train.n.01", "coco_cat_id": 7}, | |
{"synset": "truck.n.01", "coco_cat_id": 8}, | |
{"synset": "boat.n.01", "coco_cat_id": 9}, | |
{"synset": "traffic_light.n.01", "coco_cat_id": 10}, | |
{"synset": "fireplug.n.01", "coco_cat_id": 11}, | |
{"synset": "stop_sign.n.01", "coco_cat_id": 13}, | |
{"synset": "parking_meter.n.01", "coco_cat_id": 14}, | |
{"synset": "bench.n.01", "coco_cat_id": 15}, | |
{"synset": "bird.n.01", "coco_cat_id": 16}, | |
{"synset": "cat.n.01", "coco_cat_id": 17}, | |
{"synset": "dog.n.01", "coco_cat_id": 18}, | |
{"synset": "horse.n.01", "coco_cat_id": 19}, | |
{"synset": "sheep.n.01", "coco_cat_id": 20}, | |
{"synset": "beef.n.01", "coco_cat_id": 21}, | |
{"synset": "elephant.n.01", "coco_cat_id": 22}, | |
{"synset": "bear.n.01", "coco_cat_id": 23}, | |
{"synset": "zebra.n.01", "coco_cat_id": 24}, | |
{"synset": "giraffe.n.01", "coco_cat_id": 25}, | |
{"synset": "backpack.n.01", "coco_cat_id": 27}, | |
{"synset": "umbrella.n.01", "coco_cat_id": 28}, | |
{"synset": "bag.n.04", "coco_cat_id": 31}, | |
{"synset": "necktie.n.01", "coco_cat_id": 32}, | |
{"synset": "bag.n.06", "coco_cat_id": 33}, | |
{"synset": "frisbee.n.01", "coco_cat_id": 34}, | |
{"synset": "ski.n.01", "coco_cat_id": 35}, | |
{"synset": "snowboard.n.01", "coco_cat_id": 36}, | |
{"synset": "ball.n.06", "coco_cat_id": 37}, | |
{"synset": "kite.n.03", "coco_cat_id": 38}, | |
{"synset": "baseball_bat.n.01", "coco_cat_id": 39}, | |
{"synset": "baseball_glove.n.01", "coco_cat_id": 40}, | |
{"synset": "skateboard.n.01", "coco_cat_id": 41}, | |
{"synset": "surfboard.n.01", "coco_cat_id": 42}, | |
{"synset": "tennis_racket.n.01", "coco_cat_id": 43}, | |
{"synset": "bottle.n.01", "coco_cat_id": 44}, | |
{"synset": "wineglass.n.01", "coco_cat_id": 46}, | |
{"synset": "cup.n.01", "coco_cat_id": 47}, | |
{"synset": "fork.n.01", "coco_cat_id": 48}, | |
{"synset": "knife.n.01", "coco_cat_id": 49}, | |
{"synset": "spoon.n.01", "coco_cat_id": 50}, | |
{"synset": "bowl.n.03", "coco_cat_id": 51}, | |
{"synset": "banana.n.02", "coco_cat_id": 52}, | |
{"synset": "apple.n.01", "coco_cat_id": 53}, | |
{"synset": "sandwich.n.01", "coco_cat_id": 54}, | |
{"synset": "orange.n.01", "coco_cat_id": 55}, | |
{"synset": "broccoli.n.01", "coco_cat_id": 56}, | |
{"synset": "carrot.n.01", "coco_cat_id": 57}, | |
{"synset": "frank.n.02", "coco_cat_id": 58}, | |
{"synset": "pizza.n.01", "coco_cat_id": 59}, | |
{"synset": "doughnut.n.02", "coco_cat_id": 60}, | |
{"synset": "cake.n.03", "coco_cat_id": 61}, | |
{"synset": "chair.n.01", "coco_cat_id": 62}, | |
{"synset": "sofa.n.01", "coco_cat_id": 63}, | |
{"synset": "pot.n.04", "coco_cat_id": 64}, | |
{"synset": "bed.n.01", "coco_cat_id": 65}, | |
{"synset": "dining_table.n.01", "coco_cat_id": 67}, | |
{"synset": "toilet.n.02", "coco_cat_id": 70}, | |
{"synset": "television_receiver.n.01", "coco_cat_id": 72}, | |
{"synset": "laptop.n.01", "coco_cat_id": 73}, | |
{"synset": "mouse.n.04", "coco_cat_id": 74}, | |
{"synset": "remote_control.n.01", "coco_cat_id": 75}, | |
{"synset": "computer_keyboard.n.01", "coco_cat_id": 76}, | |
{"synset": "cellular_telephone.n.01", "coco_cat_id": 77}, | |
{"synset": "microwave.n.02", "coco_cat_id": 78}, | |
{"synset": "oven.n.01", "coco_cat_id": 79}, | |
{"synset": "toaster.n.02", "coco_cat_id": 80}, | |
{"synset": "sink.n.01", "coco_cat_id": 81}, | |
{"synset": "electric_refrigerator.n.01", "coco_cat_id": 82}, | |
{"synset": "book.n.01", "coco_cat_id": 84}, | |
{"synset": "clock.n.01", "coco_cat_id": 85}, | |
{"synset": "vase.n.01", "coco_cat_id": 86}, | |
{"synset": "scissors.n.01", "coco_cat_id": 87}, | |
{"synset": "teddy.n.01", "coco_cat_id": 88}, | |
{"synset": "hand_blower.n.01", "coco_cat_id": 89}, | |
{"synset": "toothbrush.n.01", "coco_cat_id": 90}, | |
] | |
def cocofy_lvis(input_filename, output_filename): | |
""" | |
Filter LVIS instance segmentation annotations to remove all categories that are not included in | |
COCO. The new json files can be used to evaluate COCO AP using `lvis-api`. The category ids in | |
the output json are the incontiguous COCO dataset ids. | |
Args: | |
input_filename (str): path to the LVIS json file. | |
output_filename (str): path to the COCOfied json file. | |
""" | |
with open(input_filename, "r") as f: | |
lvis_json = json.load(f) | |
lvis_annos = lvis_json.pop("annotations") | |
cocofied_lvis = copy.deepcopy(lvis_json) | |
lvis_json["annotations"] = lvis_annos | |
# Mapping from lvis cat id to coco cat id via synset | |
lvis_cat_id_to_synset = {cat["id"]: cat["synset"] for cat in lvis_json["categories"]} | |
synset_to_coco_cat_id = {x["synset"]: x["coco_cat_id"] for x in COCO_SYNSET_CATEGORIES} | |
# Synsets that we will keep in the dataset | |
synsets_to_keep = set(synset_to_coco_cat_id.keys()) | |
coco_cat_id_with_instances = defaultdict(int) | |
new_annos = [] | |
ann_id = 1 | |
for ann in lvis_annos: | |
lvis_cat_id = ann["category_id"] | |
synset = lvis_cat_id_to_synset[lvis_cat_id] | |
if synset not in synsets_to_keep: | |
continue | |
coco_cat_id = synset_to_coco_cat_id[synset] | |
new_ann = copy.deepcopy(ann) | |
new_ann["category_id"] = coco_cat_id | |
new_ann["id"] = ann_id | |
ann_id += 1 | |
new_annos.append(new_ann) | |
coco_cat_id_with_instances[coco_cat_id] += 1 | |
cocofied_lvis["annotations"] = new_annos | |
for image in cocofied_lvis["images"]: | |
for key in ["not_exhaustive_category_ids", "neg_category_ids"]: | |
new_category_list = [] | |
for lvis_cat_id in image[key]: | |
synset = lvis_cat_id_to_synset[lvis_cat_id] | |
if synset not in synsets_to_keep: | |
continue | |
coco_cat_id = synset_to_coco_cat_id[synset] | |
new_category_list.append(coco_cat_id) | |
coco_cat_id_with_instances[coco_cat_id] += 1 | |
image[key] = new_category_list | |
coco_cat_id_with_instances = set(coco_cat_id_with_instances.keys()) | |
new_categories = [] | |
for cat in lvis_json["categories"]: | |
synset = cat["synset"] | |
if synset not in synsets_to_keep: | |
continue | |
coco_cat_id = synset_to_coco_cat_id[synset] | |
if coco_cat_id not in coco_cat_id_with_instances: | |
continue | |
new_cat = copy.deepcopy(cat) | |
new_cat["id"] = coco_cat_id | |
new_categories.append(new_cat) | |
cocofied_lvis["categories"] = new_categories | |
with open(output_filename, "w") as f: | |
json.dump(cocofied_lvis, f) | |
print("{} is COCOfied and stored in {}.".format(input_filename, output_filename)) | |
if __name__ == "__main__": | |
dataset_dir = os.path.join(os.getenv("DETECTRON2_DATASETS", "datasets"), "lvis") | |
for s in ["lvis_v0.5_train", "lvis_v0.5_val"]: | |
print("Start COCOfing {}.".format(s)) | |
cocofy_lvis( | |
os.path.join(dataset_dir, "{}.json".format(s)), | |
os.path.join(dataset_dir, "{}_cocofied.json".format(s)), | |
) | |