概述
pycocotools coco格式数据集可视化
import cv2
import os
import numpy as np
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 = 'train/images'
annFile = 'train/annotations/train.json'
save_path = 'train/images_vis'
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)
# catIds = coco.getCatIds(catNms=['Crack','Manhole', 'Net', 'Pothole','Patch-Crack', "Patch-Net", "Patch-Pothole", "other"])
# catIds = coco.getCatIds()
# imgIds = coco.getImgIds(catIds=catIds)
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)
# coco.showAnns(anns)
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)
最后
以上就是会撒娇小猫咪为你收集整理的pycocotools coco格式数据集可视化的全部内容,希望文章能够帮你解决pycocotools coco格式数据集可视化所遇到的程序开发问题。
如果觉得靠谱客网站的内容还不错,欢迎将靠谱客网站推荐给程序员好友。
本图文内容来源于网友提供,作为学习参考使用,或来自网络收集整理,版权属于原作者所有。
发表评论 取消回复