在python里面,读取出json标注格式文件,每一个字段虽然是list,实际上是一个dict,Object Keypoint这种格式的文件从头至尾按照顺序分为以下段落如下所示: { "info": info, # dict "licenses": [license], # list ,内部是dict "images": [image], # list ,内部是dict "annotations": [annotation], # list ,...
for dataset in datasets_list: # ./COCO/annotations/instances_train2017.json annFile = '{}/annotations/instances_{}.json'.format(dataDir, dataset) # 使用COCO API用来初始化注释数据 coco = COCO(annFile) # 获取COCO数据集中的所有类别 classes = id2name(coco) # print(classes) # [1, 2, 3...
root=tree.getroot()formemberinroot.findall("object"): classes_names.append(member[0].text) classes_names=list(set(classes_names)) classes_names.sort()return{name: ifori, nameinenumerate(classes_names)}defconvert(xml_files, json_file): json_dict= {"images": [],"type":"instances","anno...
并处理所有需要的json数据50defprocess_json_data(annFile):51#获取COCO_json的数据52coco =COCO(annFile)53#拿到所有需要的图片数据的id54classes_ids = coco.getCatIds(catNms =classes_names)55#加载所有需要的类别信息56classes_list =coco.loadCats(classes_ids)57#取所有类别的并集的所有图片id58#如果想要...
(coco): classes = dict() for cat in coco.dataset['categories']: classes[cat['id']] = cat['name'] return classes def show_image(image_path, anno_path, show=False, plot_image=False): assert os.path.exists(image_path), "image path:{} dose not exists".format(image_path) assert ...
gt.json'CLASSES=('A','B','C')class_num=len(CLASSES)cocoGt=COCO(gt_json)cocoDt=cocoGt.loadRes(det_json)cocoEval=COCOeval(cocoGt,cocoDt,"bbox")cocoEval.params.iouThrs=np.linspace(0.5,0.95,int(np.round((0.95-.5)/.05))+1,endpoint=True)cocoEval.params.maxDets=list((100,300,1000...
dataset_List classes_names dataDir from pycocotools.coco import COCO import os import shutil from tqdm import tqdm import skimage.io as io import matplotlib.pyplot as plt import cv2 from PIL import Image, ImageDraw #the path you want to save your results for coco to voc savepath="/coco_...
3.voc_annotations : path to your VOC dataset Annotations """val_files_num =500test_files_num =0voc_annotations ='E:/dataset/VOCdataset/VOCdevkit/VOC2007/Annotations/'# remember to modify the pathmain_path ='E:/dataset/VOCdataset/VOCdevkit'coco_name ='VOC2007'# split = voc_annotations....
plt.show()returnobjsfordatasetindatasets_list:#./COCO/annotations/instances_train2014.jsonannFile='{}/annotations/instances_{}.json'.format(dataDir,dataset)#COCO API for initializing annotated datacoco = COCO(annFile)#show all classes in cococlasses = id2name(coco)print(classes)#[1, 2, 3,...
('img_path',help='The root path of images')#图像类别list,这里的输入是一个txt文件,然后返回类别list#可以直接在代码写一个listparser.add_argument('classes',type=str,help='The text file name of storage class list')#保存文件名称parser.add_argument('out',type=str,help='The output annotation ...