【数据处理】如何在图片中随机采样

在图片中随机采样，而且不与已经标注的物体重合，啥也不说直接上代码：

"""
在图片随机采样宽为150，高为80的负样本
"""

import os
import json
import random

import cv2
import numpy as np

oimg_path = r"C:\Users\9ling\Desktop\YiLiuWuDataset_hardsample\original_dataset\yuedongguan_01"
ojson_path = r"C:\Users\9ling\Desktop\YiLiuWuDataset_hardsample\original_dataset\yuedongguan_01.json"

train_imgpath = r"C:\Users\9ling\Desktop\YiLiuWuDataset_hardsample\YiliuwuDataset\train\yuedongguan01"
train_jsonpath = r"C:\Users\9ling\Desktop\YiLiuWuDataset_hardsample\YiliuwuDataset\train\yuedongguan01\yuedongguan01.json"


def IoU(boxA, boxB):
    boxA = [int(x) for x in boxA]
    boxB = [int(x) for x in boxB]
    xA = max(boxA[0], boxB[0])
    yA = max(boxA[1], boxB[1])
    xB = min(boxA[2], boxB[2])
    yB = min(boxA[3], boxB[3])
    interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)
    boxAArea = (boxA[2] - boxA[0] + 1) * (boxA[3] - boxA[1] + 1)
    boxBArea = (boxB[2] - boxB[0] + 1) * (boxB[3] - boxB[1] + 1)
    iou = interArea / float(boxAArea + boxBArea - interArea)
    return iou


json_list = {"labels": []}


def gain(ojson_path):
    jdata = json.load(open(ojson_path))["labels"]
    for item in jdata:
        sImg_path = os.path.join(oimg_path, item["filename"].split("\\")[-1])
        im = cv2.imdecode(np.fromfile(sImg_path), 1)
        height, width = im.shape[:-1]
        while True:
            rlist = []
            rx1 = random.choice(range(1, width - 150 - 1, 1))
            ry1 = random.choice(range(1, height - 80 - 1, 1))
            rx2 = min(rx1 + 150, width - 1)
            ry2 = min(ry1 + 80, height - 1)
            rlist.extend([rx1, ry1, rx2, ry2])
            sum_ious = 0
            for anno in item["annotations"]:
                alist = []
                ax1 = anno["x"]
                ay1 = anno["y"]
                ax2 = ax1 + anno["width"] - 1
                ay2 = ay1 + anno["height"] - 1
                alist.extend([ax1, ay1, ax2, ay2])
                if IoU(rlist, alist) == 0:
                    sum_ious += IoU(rlist, alist)
                    continue
                else:
                    sum_ious += IoU(rlist, alist)
                    break
            if sum_ious == 0:
                item["annotations"].append({"class": "negativesample01",
                                            "height": ry2 - ry1 + 1,
                                            "width": rx2 - rx1 + 1,
                                            "x": rx1,
                                            "y": ry1})
                break
        json_list["labels"].append(item)


gain(ojson_path)
json_test_str = json.dumps(json_list, indent=4)
with open(train_jsonpath, 'w') as json_file:
    json_file.write(json_test_str)