YoloV5训练V3Det数据集实战

摘要

V3Det：一个庞大的词汇视觉检测数据集，在大量真实世界图像上具有精确注释的边界框，其包含13029个类别中的245k个图像（比LVIS大10倍），数据集已经开源！

图片的数量比COCO多一些，类别种类比较多！数据集大小由33G，数据集标注格式和COCO一致！
论文链接：https://arxiv.org/abs/2304.03752

这个数据集最大的特点就是类别多，还有些千奇百怪不可描述的图片！
在这里插入图片描述

下载V3Det的标注文件

官方提供了两种下载方式，见：https://v3det.openxlab.org.cn/download
第一种，点击左侧的链接，将其中的文件都下载下来！
在这里插入图片描述
v3det_2023_v1_train.json和v3det_2023_v1_val.json是数据集！
v3det_image_download.py是下载图片的脚本。
category_name_13204_v3det_2023_v1.txt 是类别！
第二种下载方式如下：

采用命令行，注册后输入密钥就能下载！下载下来的文件和第一种下载方式的文件一样，都没有图像，只能运行脚本下载图片！

下载图片的脚本

由于总所周知的原因不太好链接，多试几次，总有成功的时候。

import io
import argparse
import concurrent.futures
import json
import os
import time
import urllib.error
import urllib.requestfrom tqdm import tqdmparser = argparse.ArgumentParser()
parser.add_argument("--output_folder", type=str, default="V3Det")
parser.add_argument("--max_retries", type=int, default=3)
parser.add_argument("--max_workers", type=int, default=16)
args = parser.parse_args()
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36'}def cache(response):f = io.BytesIO()block_sz = 8192while True:buffer = response.read(block_sz)if not buffer:breakf.write(buffer)return fdef download_image(url, path, timeout):result = {"status": "","url": url,"path": path,}cnt = 0while True:try:response = urllib.request.urlopen(urllib.request.Request(url=url, headers=headers), timeout=timeout)image_path = os.path.join(args.output_folder, path)os.makedirs(os.path.dirname(image_path), exist_ok=True)f = cache(response)with open(image_path, "wb") as fp:fp.write(f.getvalue())result["status"] = "success"except Exception as e:if not isinstance(e, urllib.error.HTTPError):cnt += 1if cnt <= args.max_retries:continueif isinstance(e, urllib.error.HTTPError):result["status"] = "expired"else:result["status"] = "timeout"breakreturn resultdef main():start = time.time()if os.path.exists(args.output_folder) and os.listdir(args.output_folder):try:c = input(f"'{args.output_folder}' already exists and is not an empty directory, continue? (y/n) ")if c.lower() not in ["y", "yes"]:exit(0)except KeyboardInterrupt:exit(0)if not os.path.exists(args.output_folder):os.makedirs(args.output_folder)image_folder_path = os.path.join(args.output_folder, "images")record_path = os.path.join(args.output_folder, "records.json")record = {'success': [], 'expired': [], 'timeout': []}if os.path.isfile(record_path):try:with open(record_path, encoding="utf8") as f:record['success'] = json.load(f)['success']except:passif not os.path.exists(image_folder_path):os.makedirs(image_folder_path)list_url = 'https://raw.githubusercontent.com/V3Det/v3det_resource/main/resource/download_list.txt'response = urllib.request.urlopen(urllib.request.Request(url=list_url, headers=headers), timeout=100)url_list = [url for url in response.read().decode('utf-8').split('\n') if len(url) > 0]image2url = {}for url in url_list:response = urllib.request.urlopen(urllib.request.Request(url=url, headers=headers), timeout=100)image2url.update(eval(response.read().decode('utf-8')))data = []rec_suc = set(record['success'])for image, url in image2url.items():if image not in rec_suc:data.append((url, image))with tqdm(total=len(data)) as pbar:with concurrent.futures.ThreadPoolExecutor(max_workers=args.max_workers) as executor:# Submit up to `chunk_size` tasks at a time to avoid too many pending tasks.chunk_size = min(5000, args.max_workers * 500)for i in range(0, len(data), chunk_size):futures = [executor.submit(download_image, url, path, 10)for url, path in data[i: i + chunk_size]]for future in concurrent.futures.as_completed(futures):r = future.result()record[r["status"]].append(r["path"])pbar.update(1)with open(record_path, "w", encoding="utf8") as f:json.dump(record, f, indent=2)end = time.time()print(f"consuming time {end - start:.1f} sec")print(f"{len(record['success'])} images downloaded.")print(f"{len(record['timeout'])} urls failed due to request timeout.")print(f"{len(record['expired'])} urls failed due to url expiration.")if len(record['success']) == len(image2url):os.remove(record_path)print('All images have been downloaded!')else:print('Please run this file again to download failed image!')if __name__ == "__main__":main()

V3Det转Yolo

V3Det的标注文件和COCO是一致的！

import json
import os
import shutil
from pathlib import Path
import numpy as np
from tqdm import tqdmdef make_folders(path='../out/'):# Create foldersif os.path.exists(path):shutil.rmtree(path)  # delete output folderos.makedirs(path)  # make new output folderos.makedirs(path + os.sep + 'labels')  # make new labels folderos.makedirs(path + os.sep + 'images')  # make new labels folderreturn pathdef convert_coco_json(json_dir='./image_1024/V3Det___V3Det/raw/v3det_2023_v1_val.json',out_dir=None):# fn_images = 'out/images/%s/' % Path(json_file).stem.replace('instances_', '')  # folder nameos.makedirs(out_dir,exist_ok=True)# os.makedirs(fn_images,exist_ok=True)with open(json_dir) as f:data = json.load(f)print(out_dir)# Create image dictimages = {'%g' % x['id']: x for x in data['images']}# Write labels filefor x in tqdm(data['annotations'], desc='Annotations %s' % json_dir):if x['iscrowd']:continueimg = images['%g' % x['image_id']]h, w, f = img['height'], img['width'], img['file_name']file_path='coco/'+out_dir.split('/')[-2]+"/"+f# The Labelbox bounding box format is [top left x, top left y, width, height]box = np.array(x['bbox'], dtype=np.float64)box[:2] += box[2:] / 2  # xy top-left corner to centerbox[[0, 2]] /= w  # normalize xbox[[1, 3]] /= h  # normalize yif (box[2] > 0.) and (box[3] > 0.):  # if w > 0 and h > 0with open(out_dir + Path(f).stem + '.txt', 'a') as file:file.write('%g %.6f %.6f %.6f %.6f\n' % (x['category_id'] - 1, *box))convert_coco_json(json_dir='./image_1024/V3Det___V3Det/raw/v3det_2023_v1_val.json',out_dir='out/labels/val/')
convert_coco_json(json_dir='./image_1024/V3Det___V3Det/raw/v3det_2023_v1_train.json',out_dir='out/labels/train/')

复制图片到指定目录

将图片放到和Label同级的images文件夹

import glob
import os
import shutilimage_paths = glob.glob('V3Det/images/*/*.jpg')dir_imagepath = {}for image_path in image_paths:image_key = image_path.replace('\\', '/').split('/')[-1].split('.')[0]dir_imagepath[image_key] = image_pathos.makedirs('out/images/train',exist_ok=True)
os.makedirs('out/images/val',exist_ok=True)def txt_2_image(txt_dir='out/labels/train/', out_path='out/images/train'):txt_paths = glob.glob(txt_dir + '*.txt')for txt in txt_paths:txt_key = txt.replace('\\', '/').split('/')[-1].split('.')[0]if txt_key in dir_imagepath:image_path = dir_imagepath[txt_key]shutil.copy(image_path, out_path)else:os.remove(txt)txt_2_image(txt_dir='out/labels/train/', out_path='out/images/train')
txt_2_image(txt_dir='out/labels/val/', out_path='out/images/val')

生成类别

找到类别文件，生成YoloV5或V8的类别格式，如下图：
在这里插入图片描述
代码如下：

with open('image_1024/V3Det___V3Det/raw/category_name_13204_v3det_2023_v1.txt','r') as files:list_class=files.readlines()for i, c in enumerate(list_class):print(str(i)+": "+c.replace('\n',''))