labelme 标注json转换为带旋转角度的yolov5标记文件。其中opencv 4.5.3

Posted 2021-08-28 东东就是我

1.每个版本的opencv 的minAreaRect 角度的范围都是不一样的。自己检查一下

import numpy as np
import math
import cv2


def draw_rbbox(img, points):
    rect = cv2.minAreaRect(points)
    c_x = rect[0][0]
    c_y = rect[0][1]
    width = rect[1][0]
    height= rect[1][1]
    theta = rect[-1]
    if width != max(width, height):  # 若width不是最长边
        longside = height
        shortside = width
        theta_longside = -(90-theta)
    else:  # 若width是最长边(包括正方形的情况)
        longside = width
        shortside = height
        theta_longside = theta
    tran=((c_x, c_y), (longside, shortside), theta_longside)
    print(theta_longside)
    points_rect = cv2.boxPoints(tran)
    box = np.int0(points_rect)
    img = cv2.drawContours(img, [box], 0, (0, 0, 255), 2)
    return img

img = np.zeros([500, 500, 3], dtype=np.uint8)
x1=250
y1=250
x2=250
y2=400
x3=300
y3=400
x4=300
y4=250

for i  in range(9):
    nAgree=i*(180/9)
    dRot=nAgree*math.pi/180
    dSinRot=math.sin(dRot)
    dCosRot=math.cos(dRot)

    newx1=x1
    newy1=y1

    newx2=x1 + dCosRot * (x2 - x1) - dSinRot * (y2 - y1)
    newy2=y1 + dSinRot * (x2 - x1) + dCosRot * (y2 - y1)

    newx3= x1 + dCosRot * (x3 - x1) - dSinRot * (y3 - y1)
    newy3=y1 + dSinRot * (x3 - x1) + dCosRot * (y3 - y1)

    newx4=x1 + dCosRot * (x4 - x1) - dSinRot * (y4 - y1)
    newy4=y1 + dSinRot * (x4 - x1) + dCosRot * (y4 - y1)

    draw_rbbox(img,np.array([[newx1,newy1],[newx2,newy2],[newx3,newy3],[newx4,newy4]],dtype=np.int64))

cv2.imwrite(r'111.jpg', img)

这里的范围是【0，90】 我扩充到【0，180】

# -*- coding: utf-8 -*-
# import dota_utils as util

import numpy as np
import json
import cv2
import os

def dota2LongSideFormat(path,json_name):
    # print(json_name)
    json_path = os.path.join(path, json_name)
    img_path=os.path.join(path, json_name.split('.')[0]+'.bmp')
    img=cv2.imread(img_path)
    with open(json_path,'r') as f:
        data=json.load(f)
        shapes=data['shapes']
        imageHeight=data['imageHeight']
        imageWidth=data['imageWidth']
    txt_name=json_name.split('.')[0] + '.txt'
    txt_path=os.path.join(path,txt_name)
    with open(txt_path, 'w') as f_out:
        for shape in shapes:
            points = shape['points']
            poly = np.float32(np.array(points))
            # 四点坐标归一化
            poly[:, 0] = poly[:, 0] / imageWidth
            poly[:, 1] = poly[:, 1] / imageHeight
            rect = cv2.minAreaRect(poly)  # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）

            c_x = rect[0][0]
            c_y = rect[0][1]
            w = rect[1][0]
            h = rect[1][1]
            theta = rect[-1]  # Range for angle is [-90，0)

            trans_data = cvminAreaRect2longsideformat(c_x, c_y, w, h, theta)

            c_x, c_y, longside, shortside, theta_longside = trans_data
            bbox = np.array((c_x, c_y, longside, shortside))
            theta_label = int(theta_longside + 90)  # range int[0,180] 四舍五入
            if theta_label == 180:  # range int[0,179]
                theta_label = 179
            outline = str(0) + ' ' + ' '.join(list(map(str, bbox))) + ' ' + str(theta_label)
            f_out.write(outline + '\\n')  # 写入txt文件中并加上换行符号 \\n


def cvminAreaRect2longsideformat(x_c, y_c, width, height, theta):

    if width != max(width, height):  # 若width不是最长边
        longside = height
        shortside = width
        theta_longside = -(90-theta)
    else:  # 若width是最长边(包括正方形的情况)
        longside = width
        shortside = height
        theta_longside = theta

    # return x_c, y_c, longside, shortside, theta_longside
    return x_c, y_c, longside, shortside, theta_longside





if __name__ == '__main__':
    ## an example
    path='F:/mmdetection-2.7.0/dataset/bottle'
    file=os.listdir(path)
    for filename in file:
        if filename.endswith('.json'):

            dota2LongSideFormat(path,filename)