网站做权重的好处网络营销主要做些什么工作

背景

如果我们想要根据json标注文件，获取里面的指定目标的裁剪区域，那么我们可以根据以下代码来实现（也可以校验标注情况）。

代码

from tqdm import tqdm
import os, json, cv2, copy
import numpy as npdef get_all_images(path, flags):result_list, filenames = [], []for root, dirs, files in os.walk(path):for file in files:filename, file_extension = os.path.splitext(file)if file_extension.lower() in flags:result_list.append(os.path.join(root, file))filenames.append(file)return result_list, filenamesdef get_labelme_info(label_file, target):anno = json.load(open(label_file, "r", encoding="utf-8"))shapes = anno['shapes']image_path = os.path.basename(anno['imagePath'])labels = []boxes = []for s in shapes:pts = s['points']x1, y1 = pts[0]x2, y2 = pts[1]label = s['label']if label in target:labels.append(label)boxes.append([x1, y1, x2, y2])return image_path, boxes, labelsdef plot_one_ori(image, boxs, label, color, mask_alpha=0.4):[x1, y1, x2, y2] = boxsmask_img = copy.deepcopy(image) # 1ori_img = copy.deepcopy(mask_img) # 1cropped_image = ori_img[y1:y2, x1:x2]img_height, img_width = image.shape[:2]size = min([img_height, img_width]) * 0.0006text_thickness = int(min([img_height, img_width]) * 0.001)cv2.rectangle(image, (x1, y1), (x2, y2), color, 3)caption = f'{"原标签-"}{label}'(tw, th), _ = cv2.getTextSize(text=caption, fontFace=cv2.FONT_HERSHEY_SIMPLEX,fontScale=size, thickness=text_thickness)th = int(th * 1.2)cv2.rectangle(image, (x1, y2),(x1 + tw, y2 + th), color, -1)cv2.rectangle(mask_img, (x1, y2),(x1 + tw, y2 + th), color, -1)cv2.putText(image, caption, (x1, y2 + th), cv2.FONT_HERSHEY_SIMPLEX, size, (255, 255, 255), text_thickness, cv2.LINE_AA)cv2.putText(mask_img, caption, (x1, y2 + th), cv2.FONT_HERSHEY_SIMPLEX, size, (255, 255, 255), text_thickness, cv2.LINE_AA)image = cv2.addWeighted(mask_img, mask_alpha, image, 1 - mask_alpha, 0)return image, cropped_imagedef cv_imread(filePath):cv_img = cv2.imdecode(np.fromfile(filePath, dtype=np.uint8), flags=cv2.IMREAD_COLOR)return cv_imgif __name__ == "__main__":img_folder = r"\\DSJ_NAS_90*******" # 原图和JSON文件位置save_target_path = r"\\DSJ_NA************" # 保存位置target = ["red_face"] # 获取指定目标，可传多个os.makedirs(save_target_path, exist_ok=True)img_list, filenames = get_all_images(img_folder, flags=[".jpg", ".png", ".jpeg"])print(filenames)for filename in filenames:fn, file_extension = os.path.splitext(filename)image_path = os.path.join(img_folder, filename)  # 图片名json_path = os.path.join(img_folder, "{}.json".format(fn))  # 标签文件名save_path = os.path.join(save_target_path, "{}.jpg".format(fn))_, ori_boxes, ori_labels = get_labelme_info(json_path, target)for box, label in zip(ori_boxes, ori_labels):x1, y1, x2, y2 = list(map(int, box))image = cv_imread(image_path)image, crop_image = plot_one_ori(image, [x1, y1, x2, y2], label, color=(0,0,255))# cv2.imshow("1",crop_image)# cv2.waitKey(1)cv2.imencode('.jpg', crop_image)[1].tofile(save_path)