labelme json文件提取特定区域成新json
作者:互联网
# 读取json文件内容,返回字典格式
from collections import defaultdict, OrderedDict
import json
import cv2
from labelme import utils
def new_json(jsonname,xgpoints,txtpoints,imagepath,imageH,imageW,imagedata,xg_shapetype='rectangle',txt_shapetype="polygon"):
# xg_dist={
# "label":"xg",
# "points": xgpoints,
# "group_id": None,
# "shape_type": xg_shapetype,
# "flags": {}
# }
txt_dist={
"label":"txt",
"points": txtpoints,
"group_id": None,
"shape_type": txt_shapetype,
"flags": {}
}
shape = []
# shape.append(xg_dist)
shape.append(txt_dist)
test_dict = {
'version': "4.5.9",
"flags": {},
"shapes":shape,
"imagePath": imagepath,
"imageData":imagedata,
"imageHeight": imageH,
"imageWidth": imageW
}
json_str = json.dumps(test_dict, indent=4)
with open(jsonname, 'w') as json_file:
json_file.write(json_str)
def savefile(bs,path):
with open(path,'wb') as ds:
ds.write(bytes(bs))
ds.close()
path ='0926305001_10005.json'
with open(path,'r',encoding='utf8')as fp:
newimage_dir ='newimage/'
newjson_dir = 'newjson/'
json_data = json.load(fp)
labels = json_data.get('shapes')
org_imagepath = json_data.get("imagePath")
org_image = cv2.imread(org_imagepath)
print(org_image.shape)
org_point=[]
txt_point =[]
for i in range(len(labels)):
if labels[i]['label'] =='xg':
org_point = labels[i]['points']
st_x = int(org_point[0][0])
st_y = int(org_point[0][1])
ed_x = int(org_point[1][0])
ed_y = int(org_point[1][1])
cut_image =org_image[st_y:ed_y,st_x:ed_x,:]
cut_image_temp = cv2.cvtColor(cut_image,cv2.COLOR_BGR2RGB)
imagedata=utils.img_arr_to_b64(cut_image_temp).decode('utf-8')
cut_image_data =cv2.imencode(".jpg",cut_image)[1].tobytes()
newimage_name = path.split('.')[0]
newimage_path = newimage_dir + newimage_name +'cut.jpg'
json_name = newjson_dir+newimage_name +'cut.json'
savefile(cut_image_data,newimage_path)
elif labels[i]['label'] =='txt':
txt_point = labels[i]['points']
else:
pass
if len(org_point)>0 and len(txt_point)>0:
for i in range(len(txt_point)):
txt_point[i][0]=txt_point[i][0]-org_point[0][0]
txt_point[i][1]=txt_point[i][1]-org_point[0][1]
org_point[1][0] = org_point[1][0]-org_point[0][0]
org_point[1][1] = org_point[1][1]-org_point[0][1]
org_point[0][0] = 0
org_point[0][1] = 0
new_json(json_name,org_point,txt_point,newimage_path,int(org_point[1][0]),int(org_point[1][1]),imagedata)
break
标签:成新,labelme,point,image,json,cut,org,txt 来源: https://blog.csdn.net/qq_51609636/article/details/120554372