COCO格式数据集可视化

import cv2
import os
from pycocotools.coco import COCO

colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 255, 0), (255, 0, 255), (0, 255, 255)]

img_path = "D:/w_dataset/Object Detection v2/Uncompressed Version/images/val/val/"
annFile = "D:/w_dataset/Object Detection v2/Uncompressed Version/annotations/annotations/instances_val.json"
save_path = "D:/w_dataset/Object Detection v2/Uncompressed Version/see_images_coco_val/"

if not os.path.exists(save_path):
    os.makedirs(save_path)


def draw_rectangle(coordinates, image, image_name):
    for coordinate in coordinates:
        left, top, right, bottom, label = map(int, coordinate)
        color = colors[label % len(colors)]
        cv2.rectangle(image, (left, top), (right, bottom), color, 2)
        cv2.putText(image, str(label), (left, top), cv2.FONT_HERSHEY_SIMPLEX, 1.2, color, 2)

    cv2.imwrite(save_path + '/' + image_name, image)


coco = COCO(annFile)
imgIds = coco.getImgIds()

for imgId in imgIds:

    img = coco.loadImgs(imgId)[0]
    image_name = img['file_name']
    annIds = coco.getAnnIds(imgIds=img['id'], catIds=[], iscrowd=None)
    anns = coco.loadAnns(annIds)
    coordinates = []
    img_raw = cv2.imread(os.path.join(img_path, image_name))
    for j in range(len(anns)):
        coordinate = anns[j]['bbox']
        coordinate[2] += coordinate[0]
        coordinate[3] += coordinate[1]
        coordinate.append(anns[j]['category_id'])
        coordinates.append(coordinate)

    draw_rectangle(coordinates, img_raw, image_name)

img_path 是图片所在的文件夹

img_path = "D:/w_dataset/Object Detection v2/Uncompressed Version/images/val/val/"

 annFile 是json文件的路径

annFile = "D:/w_dataset/Object Detection v2/Uncompressed Version/annotations/instances_val.json"

 save_path 是将可视化图片保存的路径。

save_path = "D:/w_dataset/Object Detection v2/Uncompressed Version/see_images_coco_val/"

 可视化结果如图