├── .idea ├── .gitignore ├── inspectionProfiles │ └── profiles_settings.xml ├── misc.xml ├── modules.xml └── yolov8.iml ├── Pvz_simulation_click.py ├── README.md ├── bus.jpg ├── cuda_test.py ├── data └── xml │ ├── 1.txt │ ├── 10.txt │ ├── 11.txt │ ├── 12.txt │ ├── 2.txt │ ├── 20.txt │ ├── 21.txt │ ├── 23.txt │ ├── 24.txt │ ├── 25.txt │ ├── 26.txt │ ├── 27.txt │ ├── 28.txt │ ├── 3.txt │ ├── 30.txt │ ├── 31.txt │ ├── 32.txt │ ├── 33.txt │ ├── 34.txt │ ├── 35.txt │ ├── 36.txt │ ├── 37.txt │ ├── 38.txt │ ├── 39.txt │ ├── 4.txt │ ├── 40.txt │ ├── 41.txt │ ├── 42.txt │ ├── 44.txt │ ├── 45.txt │ ├── 46.txt │ ├── 47.txt │ ├── 48.txt │ ├── 49.txt │ ├── 5.txt │ ├── 50.txt │ ├── 51.txt │ ├── 52.txt │ ├── 53.txt │ ├── 54.txt │ ├── 55.txt │ ├── 57.txt │ ├── 58.txt │ ├── 60.txt │ ├── 61.txt │ ├── 62.txt │ ├── 63.txt │ ├── 64.txt │ ├── 65.txt │ ├── 66.txt │ ├── 67.txt │ ├── 68.txt │ ├── 69.txt │ ├── 70.txt │ ├── 71.txt │ ├── 72.txt │ ├── 73.txt │ ├── 74.txt │ └── classes.txt ├── datasets ├── coco8 │ ├── LICENSE │ ├── README.md │ ├── images │ │ ├── train │ │ │ ├── 000000000009.jpg │ │ │ ├── 000000000025.jpg │ │ │ ├── 000000000030.jpg │ │ │ └── 000000000034.jpg │ │ └── val │ │ │ ├── 000000000036.jpg │ │ │ ├── 000000000042.jpg │ │ │ ├── 000000000049.jpg │ │ │ └── 000000000061.jpg │ └── labels │ │ ├── train.cache │ │ ├── train │ │ ├── 000000000009.txt │ │ ├── 000000000025.txt │ │ ├── 000000000030.txt │ │ └── 000000000034.txt │ │ ├── val.cache │ │ └── val │ │ ├── 000000000036.txt │ │ ├── 000000000042.txt │ │ ├── 000000000049.txt │ │ └── 000000000061.txt ├── data │ └── pvz │ │ └── test.jpg └── pvz │ ├── images │ ├── train │ │ ├── 00041.jpg │ │ ├── 00051.jpg │ │ ├── 01361.jpg │ │ ├── 01391.jpg │ │ ├── 01411.jpg │ │ ├── 01421.jpg │ │ ├── 01431.jpg │ │ ├── 01491.jpg │ │ ├── 01531.jpg │ │ ├── 01561.jpg │ │ ├── 01571.jpg │ │ ├── 01581.jpg │ │ ├── 01611.jpg │ │ ├── 01641.jpg │ │ ├── 01681.jpg │ │ ├── 01701.jpg │ │ ├── 01781.jpg │ │ ├── 01791.jpg │ │ ├── 01801.jpg │ │ ├── 01811.jpg │ │ ├── 01821.jpg │ │ ├── 01831.jpg │ │ ├── 01841.jpg │ │ ├── 01851.jpg │ │ ├── 01861.jpg │ │ ├── 01901.jpg │ │ ├── 01911.jpg │ │ ├── 01921.jpg │ │ ├── 01931.jpg │ │ ├── 01941.jpg │ │ ├── 01951.jpg │ │ ├── 01961.jpg │ │ ├── 01971.jpg │ │ ├── 01991.jpg │ │ ├── 02071.jpg │ │ ├── 02091.jpg │ │ ├── 02101.jpg │ │ ├── 02111.jpg │ │ ├── 02131.jpg │ │ ├── 02141.jpg │ │ ├── 02171.jpg │ │ ├── 02181.jpg │ │ ├── 02191.jpg │ │ ├── 02201.jpg │ │ ├── 02231.jpg │ │ ├── 02261.jpg │ │ ├── 02281.jpg │ │ ├── 02291.jpg │ │ ├── 02301.jpg │ │ ├── 02321.jpg │ │ ├── 02331.jpg │ │ ├── 02371.jpg │ │ ├── 02381.jpg │ │ ├── 02391.jpg │ │ ├── 02401.jpg │ │ ├── 02421.jpg │ │ ├── 02531.jpg │ │ ├── 02571.jpg │ │ ├── 02581.jpg │ │ ├── 02591.jpg │ │ ├── 02601.jpg │ │ ├── 02631.jpg │ │ ├── 02641.jpg │ │ ├── 02651.jpg │ │ ├── 02661.jpg │ │ ├── 02671.jpg │ │ ├── 02681.jpg │ │ ├── 02701.jpg │ │ ├── 02711.jpg │ │ ├── 02721.jpg │ │ ├── 02751.jpg │ │ ├── 02761.jpg │ │ ├── 02771.jpg │ │ ├── 02791.jpg │ │ ├── 02801.jpg │ │ ├── 02811.jpg │ │ ├── 02831.jpg │ │ ├── 02861.jpg │ │ ├── 02871.jpg │ │ ├── 02881.jpg │ │ ├── 02891.jpg │ │ ├── 02901.jpg │ │ ├── 02921.jpg │ │ ├── 02941.jpg │ │ ├── 02961.jpg │ │ ├── 03011.jpg │ │ ├── 03021.jpg │ │ ├── 03061.jpg │ │ ├── 03071.jpg │ │ ├── 03091.jpg │ │ ├── 03101.jpg │ │ ├── 03121.jpg │ │ ├── 03131.jpg │ │ ├── 03171.jpg │ │ ├── 03191.jpg │ │ ├── 03201.jpg │ │ ├── 03211.jpg │ │ ├── 03221.jpg │ │ ├── 03231.jpg │ │ ├── 03251.jpg │ │ ├── 03261.jpg │ │ ├── 03271.jpg │ │ ├── 03341.jpg │ │ ├── 03361.jpg │ │ ├── 03381.jpg │ │ ├── 03391.jpg │ │ ├── 03401.jpg │ │ ├── 03411.jpg │ │ ├── 03421.jpg │ │ ├── 03431.jpg │ │ ├── 03441.jpg │ │ ├── 03451.jpg │ │ ├── 03461.jpg │ │ ├── 03471.jpg │ │ ├── 03481.jpg │ │ ├── 03591.jpg │ │ ├── 03601.jpg │ │ ├── 03621.jpg │ │ ├── 03631.jpg │ │ ├── 03641.jpg │ │ ├── 03651.jpg │ │ ├── 03661.jpg │ │ ├── 03671.jpg │ │ ├── 03681.jpg │ │ ├── 03691.jpg │ │ ├── 03701.jpg │ │ ├── 03721.jpg │ │ ├── 03731.jpg │ │ ├── 03741.jpg │ │ ├── 03751.jpg │ │ ├── 03771.jpg │ │ ├── 03781.jpg │ │ ├── 03791.jpg │ │ ├── 03801.jpg │ │ ├── 03821.jpg │ │ ├── 03841.jpg │ │ └── 03851.jpg │ └── val │ │ ├── 00031.jpg │ │ ├── 00061.jpg │ │ ├── 01591.jpg │ │ ├── 01601.jpg │ │ ├── 01631.jpg │ │ ├── 01651.jpg │ │ ├── 01751.jpg │ │ ├── 01771.jpg │ │ ├── 01881.jpg │ │ ├── 01891.jpg │ │ ├── 02081.jpg │ │ ├── 02121.jpg │ │ ├── 02161.jpg │ │ ├── 02211.jpg │ │ ├── 02221.jpg │ │ ├── 02451.jpg │ │ ├── 02511.jpg │ │ ├── 02521.jpg │ │ ├── 02541.jpg │ │ ├── 02551.jpg │ │ ├── 02561.jpg │ │ ├── 02611.jpg │ │ ├── 02731.jpg │ │ ├── 02821.jpg │ │ ├── 02841.jpg │ │ ├── 02851.jpg │ │ ├── 02911.jpg │ │ ├── 02971.jpg │ │ ├── 03081.jpg │ │ ├── 03111.jpg │ │ ├── 03141.jpg │ │ ├── 03151.jpg │ │ ├── 03161.jpg │ │ ├── 03181.jpg │ │ ├── 03321.jpg │ │ ├── 03331.jpg │ │ ├── 03351.jpg │ │ ├── 03611.jpg │ │ ├── 03761.jpg │ │ └── 03811.jpg │ ├── labels │ ├── train.cache │ ├── train │ │ ├── 00041.txt │ │ ├── 00051.txt │ │ ├── 01361.txt │ │ ├── 01391.txt │ │ ├── 01411.txt │ │ ├── 01421.txt │ │ ├── 01431.txt │ │ ├── 01491.txt │ │ ├── 01531.txt │ │ ├── 01561.txt │ │ ├── 01571.txt │ │ ├── 01581.txt │ │ ├── 01611.txt │ │ ├── 01641.txt │ │ ├── 01681.txt │ │ ├── 01701.txt │ │ ├── 01781.txt │ │ ├── 01791.txt │ │ ├── 01801.txt │ │ ├── 01811.txt │ │ ├── 01821.txt │ │ ├── 01831.txt │ │ ├── 01841.txt │ │ ├── 01851.txt │ │ ├── 01861.txt │ │ ├── 01901.txt │ │ ├── 01911.txt │ │ ├── 01921.txt │ │ ├── 01931.txt │ │ ├── 01941.txt │ │ ├── 01951.txt │ │ ├── 01961.txt │ │ ├── 01971.txt │ │ ├── 01991.txt │ │ ├── 02071.txt │ │ ├── 02091.txt │ │ ├── 02101.txt │ │ ├── 02111.txt │ │ ├── 02131.txt │ │ ├── 02141.txt │ │ ├── 02171.txt │ │ ├── 02181.txt │ │ ├── 02191.txt │ │ ├── 02201.txt │ │ ├── 02231.txt │ │ ├── 02261.txt │ │ ├── 02281.txt │ │ ├── 02291.txt │ │ ├── 02301.txt │ │ ├── 02321.txt │ │ ├── 02331.txt │ │ ├── 02371.txt │ │ ├── 02381.txt │ │ ├── 02391.txt │ │ ├── 02401.txt │ │ ├── 02421.txt │ │ ├── 02531.txt │ │ ├── 02571.txt │ │ ├── 02581.txt │ │ ├── 02591.txt │ │ ├── 02601.txt │ │ ├── 02631.txt │ │ ├── 02641.txt │ │ ├── 02651.txt │ │ ├── 02661.txt │ │ ├── 02671.txt │ │ ├── 02681.txt │ │ ├── 02701.txt │ │ ├── 02711.txt │ │ ├── 02721.txt │ │ ├── 02751.txt │ │ ├── 02761.txt │ │ ├── 02771.txt │ │ ├── 02791.txt │ │ ├── 02801.txt │ │ ├── 02811.txt │ │ ├── 02831.txt │ │ ├── 02861.txt │ │ ├── 02871.txt │ │ ├── 02881.txt │ │ ├── 02891.txt │ │ ├── 02901.txt │ │ ├── 02921.txt │ │ ├── 02941.txt │ │ ├── 02961.txt │ │ ├── 03011.txt │ │ ├── 03021.txt │ │ ├── 03061.txt │ │ ├── 03071.txt │ │ ├── 03091.txt │ │ ├── 03101.txt │ │ ├── 03121.txt │ │ ├── 03131.txt │ │ ├── 03171.txt │ │ ├── 03191.txt │ │ ├── 03201.txt │ │ ├── 03211.txt │ │ ├── 03221.txt │ │ ├── 03231.txt │ │ ├── 03251.txt │ │ ├── 03261.txt │ │ ├── 03271.txt │ │ ├── 03341.txt │ │ ├── 03361.txt │ │ ├── 03381.txt │ │ ├── 03391.txt │ │ ├── 03401.txt │ │ ├── 03411.txt │ │ ├── 03421.txt │ │ ├── 03431.txt │ │ ├── 03441.txt │ │ ├── 03451.txt │ │ ├── 03461.txt │ │ ├── 03471.txt │ │ ├── 03481.txt │ │ ├── 03591.txt │ │ ├── 03601.txt │ │ ├── 03621.txt │ │ ├── 03631.txt │ │ ├── 03641.txt │ │ ├── 03651.txt │ │ ├── 03661.txt │ │ ├── 03671.txt │ │ ├── 03681.txt │ │ ├── 03691.txt │ │ ├── 03701.txt │ │ ├── 03721.txt │ │ ├── 03731.txt │ │ ├── 03741.txt │ │ ├── 03751.txt │ │ ├── 03771.txt │ │ ├── 03781.txt │ │ ├── 03791.txt │ │ ├── 03801.txt │ │ ├── 03821.txt │ │ ├── 03841.txt │ │ └── 03851.txt │ ├── val.cache │ └── val │ │ ├── 00031.txt │ │ ├── 00061.txt │ │ ├── 01591.txt │ │ ├── 01601.txt │ │ ├── 01631.txt │ │ ├── 01651.txt │ │ ├── 01751.txt │ │ ├── 01771.txt │ │ ├── 01881.txt │ │ ├── 01891.txt │ │ ├── 02081.txt │ │ ├── 02121.txt │ │ ├── 02161.txt │ │ ├── 02211.txt │ │ ├── 02221.txt │ │ ├── 02451.txt │ │ ├── 02511.txt │ │ ├── 02521.txt │ │ ├── 02541.txt │ │ ├── 02551.txt │ │ ├── 02561.txt │ │ ├── 02611.txt │ │ ├── 02731.txt │ │ ├── 02821.txt │ │ ├── 02841.txt │ │ ├── 02851.txt │ │ ├── 02911.txt │ │ ├── 02971.txt │ │ ├── 03081.txt │ │ ├── 03111.txt │ │ ├── 03141.txt │ │ ├── 03151.txt │ │ ├── 03161.txt │ │ ├── 03181.txt │ │ ├── 03321.txt │ │ ├── 03331.txt │ │ ├── 03351.txt │ │ ├── 03611.txt │ │ ├── 03761.txt │ │ └── 03811.txt │ └── pvztrain.yaml ├── pvz_train.py ├── requirements.txt ├── runs └── detect │ ├── predict │ └── test2.png │ ├── train │ ├── F1_curve.png │ ├── PR_curve.png │ ├── P_curve.png │ ├── R_curve.png │ ├── args.yaml │ ├── confusion_matrix.png │ ├── confusion_matrix_normalized.png │ ├── labels.jpg │ ├── labels_correlogram.jpg │ ├── results.csv │ ├── results.png │ ├── train_batch0.jpg │ ├── train_batch1.jpg │ ├── train_batch2.jpg │ ├── train_batch2880.jpg │ ├── train_batch2881.jpg │ ├── train_batch2882.jpg │ ├── val_batch0_labels.jpg │ ├── val_batch0_pred.jpg │ ├── val_batch1_labels.jpg │ ├── val_batch1_pred.jpg │ ├── val_batch2_labels.jpg │ ├── val_batch2_pred.jpg │ └── weights │ │ ├── best.pt │ │ └── last.pt │ └── train2 │ ├── F1_curve.png │ ├── PR_curve.png │ ├── P_curve.png │ ├── R_curve.png │ ├── confusion_matrix.png │ ├── confusion_matrix_normalized.png │ ├── val_batch0_labels.jpg │ ├── val_batch0_pred.jpg │ ├── val_batch1_labels.jpg │ ├── val_batch1_pred.jpg │ ├── val_batch2_labels.jpg │ └── val_batch2_pred.jpg ├── seg_train.py ├── test ├── test.jpg ├── test1.mp4 ├── test2.mp4 └── test2.png ├── test1.py ├── yolov8n-seg.pt └── yolov8n.pt /.idea/.gitignore: -------------------------------------------------------------------------------- 1 | # Default ignored files 2 | /shelf/ 3 | /workspace.xml 4 | -------------------------------------------------------------------------------- /.idea/inspectionProfiles/profiles_settings.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 6 | -------------------------------------------------------------------------------- /.idea/misc.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 6 | 7 | -------------------------------------------------------------------------------- /.idea/modules.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /.idea/yolov8.iml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 12 | 13 | 15 | -------------------------------------------------------------------------------- /Pvz_simulation_click.py: -------------------------------------------------------------------------------- 1 | import argparse 2 | import os 3 | import platform 4 | import sys 5 | from pathlib import Path 6 | import cv2 7 | import torch 8 | 9 | from ultralytics import YOLO 10 | 11 | import pyautogui 12 | from PIL import ImageGrab 13 | import win32gui, win32con, win32com.client 14 | import numpy as np 15 | import time 16 | 17 | 18 | def cilck_init(): 19 | hwnd = win32gui.FindWindow(None, '植物大战僵尸中文版') 20 | print(hwnd) 21 | shell = win32com.client.Dispatch("WScript.Shell") 22 | shell.SendKeys('%') 23 | win32gui.SetForegroundWindow(hwnd) 24 | window_x, window_y, right, bottom = win32gui.GetWindowRect(hwnd) 25 | box = (window_x, window_y, right, bottom) 26 | print(box) 27 | return box 28 | 29 | 30 | def run(weights='runs/detect/train/weights/best.pt', source='self_data/pvz', imgsz=640, conf_thres=0.25, 31 | iou_thres=0.45): 32 | # Load model 33 | model = YOLO(weights) 34 | 35 | # Initialize click function 36 | box = cilck_init() 37 | 38 | num_pic = 1 39 | while num_pic: 40 | # Grab screenshot 41 | background_bgr = np.array(ImageGrab.grab(box)) 42 | background = background_bgr[:, :, [2, 1, 0]] # Convert BGR to RGB 43 | img_path = 'datasets/data/pvz/test.jpg' 44 | cv2.imwrite(img_path, background) 45 | 46 | # Perform inference 47 | results = model.predict(img_path, imgsz=imgsz, conf=conf_thres, iou=iou_thres) 48 | 49 | # Process results 50 | for result in results: 51 | for det in result.boxes.data: 52 | xyxy = det[:4].cpu().numpy().astype(int) 53 | conf = det[4].cpu().numpy() 54 | cls = int(det[5].cpu().numpy()) 55 | print(xyxy, conf, cls) 56 | 57 | # Use pyautogui to click on detected coordinates 58 | pyautogui.click(box[0] + xyxy[0], box[1] + xyxy[1] + 20) 59 | 60 | # Additional processing or saving results can be added here 61 | 62 | num_pic += 1 63 | #time.sleep(1) # Add a delay to avoid excessive clicking 64 | 65 | 66 | def main(): 67 | parser = argparse.ArgumentParser() 68 | parser.add_argument('--weights', type=str, default='runs/detect/train/weights/best.pt', help='model path') 69 | parser.add_argument('--source', type=str, default='self_data/pvz', help='source') 70 | parser.add_argument('--imgsz', type=int, default=640, help='image size') 71 | parser.add_argument('--conf-thres', type=float, default=0.25, help='confidence threshold') 72 | parser.add_argument('--iou-thres', type=float, default=0.45, help='IOU threshold') 73 | opt = parser.parse_args() 74 | 75 | run(opt.weights, opt.source, opt.imgsz, opt.conf_thres, opt.iou_thres) 76 | 77 | 78 | if __name__ == "__main__": 79 | main() 80 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Yolov8-target-detection-and-simulation-click 2 | YOLOv8算法在实时视频流目标检测中的应用，训练了自己的检测模型，并以此为基础，实现《植物大战僵尸》游戏中的自动模拟点击锤僵尸功能。 3 | --- 4 | date: 星期日, 六月 9日 2024, 9:33:28 上午 5 | lastmod: 星期日, 六月 9日 2024, 12:25:06 中午 6 | --- 7 | # 环境部署 8 | ## cuda和cuDNN环境配置 9 | ### 检查自己的英伟达驱动版本 10 | 11 | ![image.png](https://s2.loli.net/2024/06/09/REqZN8ICamTzdxU.png) 12 | 13 | ### 根据对应表选择合适的cuda版本 14 | 15 | ![image.png](https://s2.loli.net/2024/06/09/n8H3NA1IxyRdMQV.png) 16 | 17 | 建议选择cuda11.8即可 18 | 19 | ### 下载并安装cuda和cuDNN 20 | https://developer.nvidia.com/cuda-toolkit-archive 21 | cuda下载链接，下载选择11.8 22 | https://developer.nvidia.com/cudnn-downloads 23 | cuDNN下载链接，需要微软开发者账户，建议直接注册一个 24 | 25 | ![image.png](https://s2.loli.net/2024/06/09/p5gSdh4j9wPkOzs.png) 26 | 27 | 如图下载本地安装包，避免网络问题 28 | 安装过程不再赘述，建议解压和安装路径都用默认且避免中文路径，选择自定义安装，不要勾选visual studio即可，是否覆盖安装显卡驱动请随意 29 | 30 | 命令行输入nvcc --version 如果返回如下信息证明安装成功 31 | 32 | ![image.png](https://s2.loli.net/2024/06/09/asZ79Trbe5Gvzl8.png) 33 | 34 | 接下来进行cuDNN配置 35 | 下载选项如图 36 | 37 | ![image.png](https://s2.loli.net/2024/06/09/pG5wQJCNiXe3cPF.png) 38 | 39 | 目前暂时没有win11专用版本，使用win10版本没影响 40 | 进入路径 41 | ```js 42 | C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8 43 | ``` 44 | 将下载下来的cuDNN压缩包内bin,include,lib文件夹复制到前面给的路径内即可 45 | ![image.png](https://s2.loli.net/2024/06/09/CDpKfOgLsmdAqy3.png) 46 | 47 | ## python虚拟环境配置 48 | conda安装使用请自行参考教程，可能碰到的问题链接 49 | https://blog.csdn.net/u010393510/article/details/130715238 50 | 51 | 首先使用conda创建环境 52 | ```js 53 | conda create -p D:\yolov8\yolo python=3.9 54 | ``` 55 | 56 | 需要注意这里的参数 -p为指定路径在D:\yolov8\路径下创建一个名为yolo的虚拟python环境，并且指定python版本为3.9，这样做的好处是python环境直接下载到当前项目内，不需要做链接，项目转接给别人也能快速上手 57 | 58 | ![image.png](https://s2.loli.net/2024/06/09/8fLyDBaGNRctiIC.png) 59 | 60 | 这里可以看到对应路径下环境已经存在，需要注意yolo文件夹下放的是虚拟环境相关文件 61 | 这里可以直接cd到D:\yolov8路径下然后conda activate D:\yolov8\yolo激活虚拟环境 62 | 63 | ![image.png](https://s2.loli.net/2024/06/09/bGDfamwO9tEUIK2.png) 64 | 65 | 但是在对于包管理以及后续脚本运行不是很方便这里我们使用pycharm来管理整个项目并导入这个已经存在的conda环境 66 | 67 | pycharm打开整个项目文件夹 68 | 添加已经存在的conda解解释器 69 | 具体操作如图 70 | ![IMAGE 2024-06-09 10:21:55.jpg](https://s2.loli.net/2024/06/09/QABxaM1oUr2LZvK.jpg) 71 | 72 | ![IMAGE 2024-06-09 10:22:12.jpg](https://s2.loli.net/2024/06/09/voRljSbhZUdk2er.jpg) 73 | 74 | ![IMAGE 2024-06-09 10:22:26.jpg](https://s2.loli.net/2024/06/09/q7QWSVw4nfErsCt.jpg) 75 | 76 | 打开pycharm自带的终端 77 | 78 | ![image.png](https://s2.loli.net/2024/06/09/6UCEaMPA7JSpTF5.png) 79 | 80 | powershell前面括号如图显示证明配置正确 81 | 82 | ## 依赖下载 83 | 首先不要进行 pip install -r requirements.txt 84 | 因为默认下载的pytorch是cpu版本，需要自己先下载对应版本的pytorch，我的设备是英伟达的显卡，所以下载cuda11.8 对应的torch 85 | https://pytorch.org/get-started/locally/ 86 | 87 | ![image.png](https://s2.loli.net/2024/06/09/25bQEU84YFhXZkW.png) 88 | 如图选择，官方就已经给出了要执行的命令，在pycharm的终端里面执行即可 89 | 这里给出一个用于测试cuda是否可用的小脚本 90 | ```python 91 | import torch 92 | 93 | # 检查CUDA是否可用 94 | print(torch.cuda.is_available()) 95 | 96 | # 如果CUDA可用，列出CUDA设备 97 | if torch.cuda.is_available(): 98 | print("CUDA is available!") 99 | print("CUDA Device Name:", torch.cuda.get_device_name(0)) 100 | else: 101 | print("CUDA is not available.") 102 | ``` 103 | 104 | ![image.png](https://s2.loli.net/2024/06/09/umzLXnC3N6xUMWk.png) 105 | 106 | 随后执行 107 | ```python 108 | pip install -r requirements.txt 109 | pip install ultralytics 110 | # ultralytics中包含了yolov8，不需要额外pip install yolo，这里的yolo下载下来居然是一个管理amp的包，会造成yolo命令冲突而失效 111 | ``` 112 | 验证yolo环境 113 | ```js 114 | yolo predict model=yolov8n.pt source='https://ultralytics.com/images/bus.jpg' 115 | ``` 116 | 在路径runs/detect/predict下可以看见一张标注出红框的图片即表示安装成功 117 | # 模型训练 118 | ## 配置文件 119 | 本项目的目的只是为了对对象进行识别，不需要对轮廓进行分割等操作，所以使用ultralytics训练好的预训练模型yolov8n.pt，首先在官网查看coco8的配置文件进行参考 120 | ```yaml 121 | # Ultralytics YOLO 🚀, AGPL-3.0 license 122 | # COCO8 dataset (first 8 images from COCO train2017) by Ultralytics 123 | # Documentation: https://docs.ultralytics.com/datasets/detect/coco8/ 124 | # Example usage: yolo train data=coco8.yaml 125 | # parent 126 | # ├── ultralytics 127 | # └── datasets 128 | # └── coco8 ← downloads here (1 MB) 129 | 130 | # Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..] 131 | path: ../datasets/coco8 # dataset root dir 132 | train: images/train # train images (relative to 'path') 4 images 133 | val: images/val # val images (relative to 'path') 4 images 134 | test: # test images (optional) 135 | 136 | # Classes 137 | names: 138 | 0: person 139 | 1: bicycle 140 | 2: car 141 | 3: motorcycle 142 | 4: airplane 143 | 5: bus 144 | 6: train 145 | 7: truck 146 | 8: boat 147 | 9: traffic light 148 | 10: fire hydrant 149 | 11: stop sign 150 | 12: parking meter 151 | 13: bench 152 | 14: bird 153 | 15: cat 154 | 16: dog 155 | 17: horse 156 | 18: sheep 157 | 19: cow 158 | 20: elephant 159 | 21: bear 160 | 22: zebra 161 | 23: giraffe 162 | 24: backpack 163 | 25: umbrella 164 | 26: handbag 165 | 27: tie 166 | 28: suitcase 167 | 29: frisbee 168 | 30: skis 169 | 31: snowboard 170 | 32: sports ball 171 | 33: kite 172 | 34: baseball bat 173 | 35: baseball glove 174 | 36: skateboard 175 | 37: surfboard 176 | 38: tennis racket 177 | 39: bottle 178 | 40: wine glass 179 | 41: cup 180 | 42: fork 181 | 43: knife 182 | 44: spoon 183 | 45: bowl 184 | 46: banana 185 | 47: apple 186 | 48: sandwich 187 | 49: orange 188 | 50: broccoli 189 | 51: carrot 190 | 52: hot dog 191 | 53: pizza 192 | 54: donut 193 | 55: cake 194 | 56: chair 195 | 57: couch 196 | 58: potted plant 197 | 59: bed 198 | 60: dining table 199 | 61: toilet 200 | 62: tv 201 | 63: laptop 202 | 64: mouse 203 | 65: remote 204 | 66: keyboard 205 | 67: cell phone 206 | 68: microwave 207 | 69: oven 208 | 70: toaster 209 | 71: sink 210 | 72: refrigerator 211 | 73: book 212 | 74: clock 213 | 75: vase 214 | 76: scissors 215 | 77: teddy bear 216 | 78: hair drier 217 | 79: toothbrush 218 | 219 | # Download script/URL (optional) 220 | download: https://ultralytics.com/assets/coco8.zip 221 | ``` 222 | 大致结构如下 223 | ```yaml 224 | 225 | path: ../datasets/coco8 # dataset root dir 训练的数据集在的根目录 226 | train: images/train # train images (relative to 'path') 4 images 训练图片 227 | val: images/val # val images (relative to 'path') 4 images 验证图片 228 | test: # test images (optional) 测试图片 229 | 230 | # Classes 人工标注的框的种类 231 | names: 232 | 0: person 233 | 1: bicycle 234 | 2: car 235 | 3: motorcycle 236 | ``` 237 | 进行修改 238 | ```yaml 239 | path: D:\yolov8\datasets\pvz # dataset root dir 240 | train: images # train images (relative to 'path') 128 images 241 | val: images # val images (relative to 'path') 128 images 242 | 243 | names: 244 | 0: common 245 | 1: hat 246 | 2: cat 247 | 3: iron 248 | 4: sun 249 | ``` 250 | 这里对于僵尸头上带的物品，及僵尸头本身，和阳光进行了标注 251 | 保存为pvztrain.html这里我是直接放在了D:\yolov8\datasets\pvz下面 252 | ## 文件路径 253 | ``` 254 | datasets 255 | |--coco8 256 | |__pvz 257 | |--images 258 | |--labels 259 | |__pvztrain.yaml 260 | ``` 261 | 这里需要注意的是images和labels下面还有train和val（验证）对应数据和文件夹 262 | 263 | ![image.png](https://s2.loli.net/2024/06/09/QwqbcDp9EFTCsmH.png) 264 | 265 | ## 数据标注 266 | 先把图片分成train和val两部分塞入images下两个对应文件夹，再批量重命名为序号.jpg 267 | 然后使用labelimg进行标注，具体操作不在多说，自行参考网上教程，需要注意的是保存的文件夹设置为labels下对应文件夹，格式选择yolo格式，只需要矩形框标注即可。 268 | 本项目提供标注好的数据集并且已经放在了对应位置可以直接使用 269 | 270 | ## 开始训练 271 | 参考一下官网提供的示例脚本 272 | ![image.png](https://s2.loli.net/2024/06/09/8UF5EHgA361xoaZ.png) 273 | 274 | 我们的数据集并不大只有不到200张图片，所以不需要特意设置onnx格式提高速度并降低精度，同样对于使用模型检测一张图片也不需要，后续通过另外的脚本直接截取视频流进行检测 275 | ```python 276 | from ultralytics import YOLO 277 | 278 | def main(): 279 | # Load model 280 | model = YOLO("yolov8n.pt") 281 | 282 | # Train 283 | model.train(data="datasets/pvz/pvztrain.yaml", epochs=250,patience=150) 284 | 285 | # Validate 286 | model.val() 287 | 288 | if __name__ == "__main__": 289 | main() 290 | #这里设置轮数为250轮以提高精度，但其实100轮后提升效果就已经区别不大，设置patience=150，即在150轮后检测如果已经无提升则直接结束训练 291 | ``` 292 | 执行这个脚本，会在run路径下生成对应文件和模型 293 | 294 | ![image.png](https://s2.loli.net/2024/06/09/FsQENkwr1fK7dDM.png) 295 | 296 | 如图，train下面就是模型本身，train2下面就是对于这个模型进行的各种数学评估的图片 297 | # 测试效果 298 | 这里对于测试模型效果，因为训练过程中就能看到拟合程度已经很高，所以直接下载了一个敲僵尸的游戏视频进行目标检测 299 | ```python 300 | from ultralytics import YOLO 301 | import cv2 302 | import numpy as np 303 | 304 | # 加载YOLOv8模型 305 | model = YOLO('runs/detect/train/weights/best.pt') 306 | 307 | # 打开视频文件 308 | cap = cv2.VideoCapture('test/test2.mp4') 309 | 310 | # 循环遍历视频帧 311 | while cap.isOpened(): 312 | # 从视频读取一帧 313 | success, frame = cap.read() 314 | if not success: 315 | break 316 | 317 | # 在帧上运行YOLOv8检测 318 | results = model.predict(frame) 319 | 320 | # 检查是否有检测结果 321 | if results: 322 | # 获取框和类别信息 323 | boxes = results[0].boxes.xyxy.cpu().numpy() # 修改为获取xyxy格式的边界框，并转换为numpy数组 324 | classes = results[0].boxes.cls.cpu().numpy() # 获取类别索引，并转换为numpy数组 325 | 326 | # 在帧上展示结果 327 | annotated_frame = results[0].plot() # 绘制检测结果 328 | 329 | # 展示带注释的帧 330 | annotated_frame = cv2.resize(annotated_frame, (640, 480)) 331 | cv2.imshow('YOLOv8 Detection', annotated_frame) 332 | else: 333 | # 如果没有检测结果，直接展示原始帧 334 | cv2.imshow('YOLOv8 Detection', frame) 335 | 336 | # 如果按下'q'则退出循环 337 | if cv2.waitKey(1) & 0xFF == ord('q'): 338 | break 339 | 340 | # 释放视频捕获对象并关闭显示窗口 341 | cap.release() 342 | cv2.destroyAllWindows() 343 | ``` 344 | 345 | ![image.png](https://s2.loli.net/2024/06/09/5qwlXti8JkSYIHB.png) 346 | 347 | 随意截取一帧，能看到识别精度很高 348 | 349 | ![image.png](https://s2.loli.net/2024/06/09/gyMLbUh2eBcJDoK.png) 350 | 351 | 对于复杂情况，抗干扰能力也很强 352 | # 模拟点击 353 | 对于模拟点击的部分，直接使用的pyautogui库模拟的点击，使用win32gui来抓取的窗口 354 | 详细代码如下 355 | ```python 356 | import argparse 357 | import os 358 | import platform 359 | import sys 360 | from pathlib import Path 361 | import cv2 362 | import torch 363 | 364 | from ultralytics import YOLO 365 | 366 | import pyautogui 367 | from PIL import ImageGrab 368 | import win32gui, win32con, win32com.client 369 | import numpy as np 370 | import time 371 | 372 | 373 | def cilck_init(): 374 | hwnd = win32gui.FindWindow(None, '植物大战僵尸中文版') 375 | print(hwnd) 376 | shell = win32com.client.Dispatch("WScript.Shell") 377 | shell.SendKeys('%') 378 | win32gui.SetForegroundWindow(hwnd) 379 | window_x, window_y, right, bottom = win32gui.GetWindowRect(hwnd) 380 | box = (window_x, window_y, right, bottom) 381 | print(box) 382 | return box 383 | 384 | 385 | def run(weights='runs/detect/train/weights/best.pt', source='self_data/pvz', imgsz=640, conf_thres=0.25, 386 | iou_thres=0.45): 387 | # Load model 388 | model = YOLO(weights) 389 | 390 | # Initialize click function 391 | box = cilck_init() 392 | 393 | num_pic = 1 394 | while num_pic: 395 | # Grab screenshot 396 | background_bgr = np.array(ImageGrab.grab(box)) 397 | background = background_bgr[:, :, [2, 1, 0]] # Convert BGR to RGB 398 | img_path = 'datasets/data/pvz/test.jpg' 399 | cv2.imwrite(img_path, background) 400 | 401 | # Perform inference 402 | results = model.predict(img_path, imgsz=imgsz, conf=conf_thres, iou=iou_thres) 403 | 404 | # Process results 405 | for result in results: 406 | for det in result.boxes.data: 407 | xyxy = det[:4].cpu().numpy().astype(int) 408 | conf = det[4].cpu().numpy() 409 | cls = int(det[5].cpu().numpy()) 410 | print(xyxy, conf, cls) 411 | 412 | # Use pyautogui to click on detected coordinates 413 | pyautogui.click(box[0] + xyxy[0], box[1] + xyxy[1] + 20) 414 | 415 | # Additional processing or saving results can be added here 416 | 417 | num_pic += 1 418 | #time.sleep(1) # Add a delay to avoid excessive clicking 419 | 420 | 421 | def main(): 422 | parser = argparse.ArgumentParser() 423 | parser.add_argument('--weights', type=str, default='runs/detect/train/weights/best.pt', help='model path') 424 | parser.add_argument('--source', type=str, default='self_data/pvz', help='source') 425 | parser.add_argument('--imgsz', type=int, default=640, help='image size') 426 | parser.add_argument('--conf-thres', type=float, default=0.25, help='confidence threshold') 427 | parser.add_argument('--iou-thres', type=float, default=0.45, help='IOU threshold') 428 | opt = parser.parse_args() 429 | 430 | run(opt.weights, opt.source, opt.imgsz, opt.conf_thres, opt.iou_thres) 431 | 432 | 433 | if __name__ == "__main__": 434 | main() 435 | 436 | ``` 437 | 438 | # 成果展示 439 | 440 | http://storage.live.com/items/6D2785503C1134C!259:/录屏2024-06-08 20.12.01.mp4 441 | -------------------------------------------------------------------------------- /bus.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/bus.jpg -------------------------------------------------------------------------------- /cuda_test.py: -------------------------------------------------------------------------------- 1 | import torch 2 | 3 | # 检查CUDA是否可用 4 | print(torch.cuda.is_available()) 5 | 6 | # 如果CUDA可用，列出CUDA设备 7 | if torch.cuda.is_available(): 8 | print("CUDA is available!") 9 | print("CUDA Device Name:", torch.cuda.get_device_name(0)) 10 | else: 11 | print("CUDA is not available.") -------------------------------------------------------------------------------- /data/xml/1.txt: -------------------------------------------------------------------------------- 1 | 0 0.556886 0.573529 0.886228 0.852941 2 | -------------------------------------------------------------------------------- /data/xml/10.txt: -------------------------------------------------------------------------------- 1 | 0 0.472727 0.500000 0.909091 0.931034 2 | -------------------------------------------------------------------------------- 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0.511364 0.979592 0.977273 2 | -------------------------------------------------------------------------------- /data/xml/27.txt: -------------------------------------------------------------------------------- 1 | 0 0.462264 0.510417 0.886792 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/28.txt: -------------------------------------------------------------------------------- 1 | 0 0.509091 0.577465 0.418182 0.760563 2 | -------------------------------------------------------------------------------- /data/xml/3.txt: -------------------------------------------------------------------------------- 1 | 0 0.500000 0.548780 0.808219 0.878049 2 | -------------------------------------------------------------------------------- /data/xml/30.txt: -------------------------------------------------------------------------------- 1 | 0 0.471698 0.490385 0.905660 0.903846 2 | -------------------------------------------------------------------------------- /data/xml/31.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.551471 0.981132 0.897059 2 | -------------------------------------------------------------------------------- /data/xml/32.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.522059 0.981132 0.926471 2 | -------------------------------------------------------------------------------- /data/xml/33.txt: -------------------------------------------------------------------------------- 1 | 0 0.518868 0.529412 0.962264 0.941176 2 | -------------------------------------------------------------------------------- /data/xml/34.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.522059 0.981132 0.955882 2 | -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | 0 0.516393 0.510417 0.967213 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/4.txt: -------------------------------------------------------------------------------- 1 | 0 0.440000 0.546296 0.840000 0.907407 2 | -------------------------------------------------------------------------------- /data/xml/40.txt: -------------------------------------------------------------------------------- 1 | 0 0.475410 0.510417 0.885246 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/41.txt: -------------------------------------------------------------------------------- 1 | 0 0.452830 0.500000 0.867925 0.958333 2 | -------------------------------------------------------------------------------- /data/xml/42.txt: -------------------------------------------------------------------------------- 1 | 0 0.513889 0.564103 0.972222 0.871795 2 | -------------------------------------------------------------------------------- /data/xml/44.txt: -------------------------------------------------------------------------------- 1 | 0 0.483333 0.518519 0.900000 0.962963 2 | -------------------------------------------------------------------------------- /data/xml/45.txt: -------------------------------------------------------------------------------- 1 | 0 0.508333 0.509259 0.983333 0.981481 2 | -------------------------------------------------------------------------------- /data/xml/46.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.520833 0.943396 0.958333 2 | -------------------------------------------------------------------------------- /data/xml/47.txt: -------------------------------------------------------------------------------- 1 | 0 0.508929 0.539216 0.982143 0.921569 2 | -------------------------------------------------------------------------------- /data/xml/48.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.510417 0.981132 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/49.txt: -------------------------------------------------------------------------------- 1 | 0 0.490566 0.520833 0.943396 0.958333 2 | -------------------------------------------------------------------------------- /data/xml/5.txt: -------------------------------------------------------------------------------- 1 | 0 0.491803 0.431818 0.885246 0.772727 2 | -------------------------------------------------------------------------------- /data/xml/50.txt: -------------------------------------------------------------------------------- 1 | 0 0.518868 0.541667 0.962264 0.916667 2 | -------------------------------------------------------------------------------- /data/xml/51.txt: -------------------------------------------------------------------------------- 1 | 0 0.518868 0.510417 0.962264 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/52.txt: -------------------------------------------------------------------------------- 1 | 0 0.518868 0.509091 0.962264 0.981818 2 | -------------------------------------------------------------------------------- /data/xml/53.txt: -------------------------------------------------------------------------------- 1 | 0 0.509434 0.510417 0.981132 0.979167 2 | -------------------------------------------------------------------------------- /data/xml/54.txt: -------------------------------------------------------------------------------- 1 | 0 0.507143 0.540323 0.928571 0.919355 2 | -------------------------------------------------------------------------------- /data/xml/55.txt: -------------------------------------------------------------------------------- 1 | 0 0.482143 0.523810 0.892857 0.825397 2 | -------------------------------------------------------------------------------- /data/xml/57.txt: -------------------------------------------------------------------------------- 1 | 0 0.508929 0.579365 0.982143 0.841270 2 | -------------------------------------------------------------------------------- /data/xml/58.txt: -------------------------------------------------------------------------------- 1 | 0 0.535714 0.587302 0.928571 0.825397 2 | -------------------------------------------------------------------------------- /data/xml/60.txt: -------------------------------------------------------------------------------- 1 | 0 0.500000 0.500000 0.964286 0.746032 2 | -------------------------------------------------------------------------------- /data/xml/61.txt: -------------------------------------------------------------------------------- 1 | 0 0.505814 0.558824 0.872093 0.882353 2 | -------------------------------------------------------------------------------- /data/xml/62.txt: -------------------------------------------------------------------------------- 1 | 0 0.366197 0.570513 0.704225 0.756410 2 | -------------------------------------------------------------------------------- /data/xml/63.txt: -------------------------------------------------------------------------------- 1 | 0 0.500000 0.564516 0.960784 0.870968 2 | -------------------------------------------------------------------------------- /data/xml/64.txt: -------------------------------------------------------------------------------- 1 | 0 0.508772 0.541667 0.982456 0.916667 2 | -------------------------------------------------------------------------------- /data/xml/65.txt: -------------------------------------------------------------------------------- 1 | 0 0.507042 0.528986 0.985915 0.942029 2 | -------------------------------------------------------------------------------- /data/xml/66.txt: -------------------------------------------------------------------------------- 1 | 0 0.517544 0.526316 0.964912 0.947368 2 | -------------------------------------------------------------------------------- /data/xml/67.txt: -------------------------------------------------------------------------------- 1 | 0 0.500000 0.509434 0.959184 0.943396 2 | -------------------------------------------------------------------------------- /data/xml/68.txt: -------------------------------------------------------------------------------- 1 | 0 0.507812 0.549180 0.796875 0.901639 2 | -------------------------------------------------------------------------------- /data/xml/69.txt: -------------------------------------------------------------------------------- 1 | 0 0.453125 0.532787 0.875000 0.934426 2 | -------------------------------------------------------------------------------- /data/xml/70.txt: -------------------------------------------------------------------------------- 1 | 0 0.486842 0.535714 0.921053 0.928571 2 | -------------------------------------------------------------------------------- /data/xml/71.txt: -------------------------------------------------------------------------------- 1 | 0 0.531250 0.549180 0.937500 0.901639 2 | -------------------------------------------------------------------------------- /data/xml/72.txt: -------------------------------------------------------------------------------- 1 | 0 0.445312 0.549180 0.828125 0.901639 2 | -------------------------------------------------------------------------------- /data/xml/73.txt: -------------------------------------------------------------------------------- 1 | 0 0.528986 0.531746 0.942029 0.936508 2 | -------------------------------------------------------------------------------- /data/xml/74.txt: -------------------------------------------------------------------------------- 1 | 0 0.523256 0.547368 0.860465 0.905263 2 | -------------------------------------------------------------------------------- /data/xml/classes.txt: -------------------------------------------------------------------------------- 1 | head 2 | -------------------------------------------------------------------------------- /datasets/coco8/LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to 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But first, please read 674 | . -------------------------------------------------------------------------------- /datasets/coco8/README.md: -------------------------------------------------------------------------------- 1 | # Ultralytics COCO8 Dataset 2 | 3 | Ultralytics COCO8 is a small, but versatile object detection dataset composed of the first 8 images of the COCO train 4 | 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, 5 | or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet 6 | diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets. 7 | 8 | This dataset is intended for use with Ultralytics YOLOv8. 9 | 10 | Docs: https://docs.ultralytics.com 11 | Community: https://community.ultralytics.com 12 | GitHub: https://github.com/ultralytics/ultralytics -------------------------------------------------------------------------------- /datasets/coco8/images/train/000000000009.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/datasets/coco8/images/train/000000000009.jpg -------------------------------------------------------------------------------- /datasets/coco8/images/train/000000000025.jpg: -------------------------------------------------------------------------------- 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/datasets/coco8/labels/train/000000000009.txt: -------------------------------------------------------------------------------- 1 | 45 0.479492 0.688771 0.955609 0.5955 2 | 45 0.736516 0.247188 0.498875 0.476417 3 | 50 0.637063 0.732938 0.494125 0.510583 4 | 45 0.339438 0.418896 0.678875 0.7815 5 | 49 0.646836 0.132552 0.118047 0.0969375 6 | 49 0.773148 0.129802 0.0907344 0.0972292 7 | 49 0.668297 0.226906 0.131281 0.146896 8 | 49 0.642859 0.0792187 0.148063 0.148062 9 | -------------------------------------------------------------------------------- /datasets/coco8/labels/train/000000000025.txt: -------------------------------------------------------------------------------- 1 | 23 0.770336 0.489695 0.335891 0.697559 2 | 23 0.185977 0.901608 0.206297 0.129554 3 | -------------------------------------------------------------------------------- /datasets/coco8/labels/train/000000000030.txt: -------------------------------------------------------------------------------- 1 | 58 0.519219 0.451121 0.39825 0.75729 2 | 75 0.501188 0.592138 0.26 0.456192 3 | -------------------------------------------------------------------------------- /datasets/coco8/labels/train/000000000034.txt: -------------------------------------------------------------------------------- 1 | 22 0.346211 0.493259 0.689422 0.892118 2 | -------------------------------------------------------------------------------- /datasets/coco8/labels/val.cache: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/datasets/coco8/labels/val.cache -------------------------------------------------------------------------------- /datasets/coco8/labels/val/000000000036.txt: -------------------------------------------------------------------------------- 1 | 25 0.475759 0.414523 0.951518 0.672422 2 | 0 0.671279 0.617945 0.645759 0.726859 3 | -------------------------------------------------------------------------------- /datasets/coco8/labels/val/000000000042.txt: -------------------------------------------------------------------------------- 1 | 16 0.606687 0.341381 0.544156 0.51 2 | -------------------------------------------------------------------------------- /datasets/coco8/labels/val/000000000049.txt: -------------------------------------------------------------------------------- 1 | 17 0.597835 0.63755 0.342283 0.36886 2 | 17 0.324291 0.64808 0.219711 0.3164 3 | 0 0.620039 0.5939 0.172415 0.14608 4 | 0 0.385525 0.58557 0.14937 0.12586 5 | 0 0.328898 0.70199 0.0313386 0.06714 6 | 58 0.622546 0.89961 0.185932 0.09446 7 | 0 0.760577 0.69423 0.0285564 0.05486 8 | 0 0.510709 0.69215 0.0187927 0.04682 9 | 0 0.929554 0.67602 0.0388451 0.01844 10 | -------------------------------------------------------------------------------- /datasets/coco8/labels/val/000000000061.txt: -------------------------------------------------------------------------------- 1 | 0 0.445688 0.480615 0.075125 0.117295 2 | 0 0.640086 0.471742 0.0508281 0.0814344 3 | 20 0.643211 0.558852 0.129828 0.097623 4 | 20 0.459703 0.592121 0.22175 0.159242 5 | 0 0.435383 0.45832 0.0534531 0.111025 6 | -------------------------------------------------------------------------------- /datasets/data/pvz/test.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/datasets/data/pvz/test.jpg -------------------------------------------------------------------------------- /datasets/pvz/images/train/00041.jpg: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | 0 0.657568 0.164062 0.047146 0.065625 2 | 0 0.722705 0.319531 0.048387 0.054688 3 | 2 0.349256 0.621875 0.065757 0.087500 4 | 3 0.797146 0.159375 0.055831 0.093750 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02671.txt: -------------------------------------------------------------------------------- 1 | 0 0.637097 0.171094 0.043424 0.060937 2 | 2 0.612283 0.155469 0.048387 0.101562 3 | 0 0.296526 0.635156 0.052109 0.067187 4 | 0 0.566998 0.637500 0.052109 0.062500 5 | 3 0.779777 0.153906 0.055831 0.095312 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02681.txt: -------------------------------------------------------------------------------- 1 | 2 0.579404 0.153125 0.054591 0.103125 2 | 0 0.632754 0.164844 0.047146 0.048438 3 | 3 0.760546 0.160938 0.059553 0.093750 4 | 0 0.531638 0.637500 0.053350 0.059375 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02701.txt: -------------------------------------------------------------------------------- 1 | 3 0.875931 0.778906 0.064516 0.089063 2 | 3 0.742556 0.156250 0.053350 0.093750 3 | 2 0.500000 0.145313 0.057072 0.106250 4 | 2 0.325682 0.305469 0.045906 0.104688 5 | 0 0.599876 0.165625 0.050868 0.068750 6 | 0 0.498759 0.634375 0.044665 0.068750 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02711.txt: -------------------------------------------------------------------------------- 1 | 0 0.571960 0.170313 0.054591 0.068750 2 | 2 0.449132 0.152344 0.047146 0.107813 3 | 2 0.668114 0.462500 0.053350 0.096875 4 | 2 0.768610 0.616406 0.065757 0.095312 5 | 2 0.757444 0.775000 0.058313 0.103125 6 | 3 0.856079 0.775000 0.062035 0.096875 7 | 3 0.736973 0.156250 0.064516 0.087500 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02721.txt: -------------------------------------------------------------------------------- 1 | 2 0.419355 0.149219 0.052109 0.101562 2 | 2 0.637097 0.458594 0.068238 0.095312 3 | 2 0.732630 0.617188 0.053350 0.106250 4 | 2 0.725806 0.784375 0.057072 0.100000 5 | 3 0.847395 0.770312 0.064516 0.096875 6 | 3 0.707816 0.153125 0.060794 0.090625 7 | 0 0.575062 0.169531 0.048387 0.064062 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02751.txt: -------------------------------------------------------------------------------- 1 | 0 0.521712 0.166406 0.053350 0.067187 2 | 0 0.500620 0.469531 0.055831 0.060937 3 | 2 0.465261 0.144531 0.064516 0.095312 4 | 2 0.663772 0.617969 0.064516 0.089063 5 | 2 0.627792 0.767969 0.066998 0.082812 6 | 3 0.800248 0.781250 0.062035 0.090625 7 | 3 0.671836 0.160938 0.055831 0.093750 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02761.txt: -------------------------------------------------------------------------------- 1 | 3 0.355459 0.306250 0.060794 0.084375 2 | 3 0.662531 0.154688 0.059553 0.093750 3 | 3 0.792184 0.773438 0.058313 0.096875 4 | 0 0.457196 0.480469 0.050868 0.064062 5 | 0 0.512407 0.171875 0.052109 0.068750 6 | 2 0.637717 0.614844 0.062035 0.092188 7 | 2 0.597395 0.775000 0.068238 0.081250 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02771.txt: -------------------------------------------------------------------------------- 1 | 3 0.297767 0.311719 0.057072 0.092188 2 | 3 0.640819 0.155469 0.055831 0.085938 3 | 3 0.777916 0.775781 0.062035 0.089063 4 | 0 0.497519 0.168750 0.052109 0.071875 5 | 0 0.775434 0.507031 0.052109 0.064062 6 | 2 0.607320 0.617969 0.063275 0.110937 7 | 2 0.552730 0.779687 0.060794 0.090625 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02791.txt: -------------------------------------------------------------------------------- 1 | 0 0.452854 0.318750 0.054591 0.068750 2 | 3 0.621588 0.155469 0.059553 0.089063 3 | 2 0.540943 0.620313 0.062035 0.103125 4 | 2 0.478288 0.778125 0.055831 0.100000 5 | 0 0.741935 0.474219 0.049628 0.060937 6 | 3 0.754342 0.773438 0.066998 0.081250 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02801.txt: -------------------------------------------------------------------------------- 1 | 3 0.611663 0.157812 0.059553 0.090625 2 | 3 0.732010 0.784375 0.059553 0.100000 3 | 0 0.725186 0.477344 0.058313 0.064062 4 | 0 0.361042 0.642188 0.052109 0.065625 5 | 2 0.528536 0.621094 0.057072 0.079687 6 | 2 0.441067 0.772656 0.060794 0.095312 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02811.txt: -------------------------------------------------------------------------------- 1 | 3 0.594913 0.152344 0.060794 0.101562 2 | 3 0.727667 0.770312 0.060794 0.096875 3 | 0 0.712779 0.481250 0.055831 0.059375 4 | 2 0.513027 0.617969 0.065757 0.085938 5 | 2 0.411290 0.774219 0.063275 0.085938 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02831.txt: -------------------------------------------------------------------------------- 1 | 3 0.570099 0.153906 0.063275 0.098437 2 | 3 0.697891 0.777344 0.065757 0.092188 3 | 0 0.364144 0.482031 0.050868 0.060937 4 | 0 0.673077 0.477344 0.048387 0.057813 5 | 2 0.830025 0.775781 0.052109 0.095312 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02861.txt: -------------------------------------------------------------------------------- 1 | 3 0.528536 0.153125 0.066998 0.087500 2 | 3 0.665633 0.773438 0.053350 0.084375 3 | 0 0.573201 0.475781 0.057072 0.060937 4 | 0 0.632754 0.477344 0.049628 0.070312 5 | 2 0.365385 0.622656 0.055831 0.101562 6 | 2 0.759305 0.772656 0.062035 0.092188 7 | 0 0.863524 0.791406 0.049628 0.070312 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02871.txt: -------------------------------------------------------------------------------- 1 | 0 0.530397 0.478906 0.050868 0.060937 2 | 0 0.603598 0.477344 0.048387 0.060937 3 | 0 0.835608 0.790625 0.050868 0.062500 4 | 2 0.336849 0.614844 0.058313 0.101562 5 | 2 0.736973 0.775000 0.057072 0.096875 6 | 3 0.632754 0.779687 0.054591 0.093750 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02881.txt: -------------------------------------------------------------------------------- 1 | 0 0.504963 0.478906 0.049628 0.064062 2 | 0 0.597395 0.475781 0.050868 0.067187 3 | 0 0.328164 0.639844 0.063275 0.064062 4 | 0 0.802109 0.798438 0.043424 0.062500 5 | 3 0.633995 0.774219 0.054591 0.089063 6 | 2 0.705955 0.776563 0.049628 0.096875 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02891.txt: -------------------------------------------------------------------------------- 1 | 0 0.460298 0.483594 0.049628 0.064062 2 | 0 0.582506 0.479687 0.048387 0.065625 3 | 0 0.768610 0.792969 0.050868 0.060937 4 | 2 0.763648 0.303906 0.058313 0.082812 5 | 2 0.691067 0.778906 0.057072 0.089063 6 | 3 0.625310 0.775000 0.057072 0.081250 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02901.txt: -------------------------------------------------------------------------------- 1 | 2 0.704715 0.308594 0.052109 0.095312 2 | 2 0.673697 0.772656 0.064516 0.089063 3 | 0 0.566377 0.476562 0.050868 0.065625 4 | 0 0.748139 0.791406 0.049628 0.064062 5 | 0 0.860422 0.799219 0.048387 0.060937 6 | 3 0.601117 0.777344 0.063275 0.092188 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02921.txt: -------------------------------------------------------------------------------- 1 | 0 0.699752 0.786719 0.054591 0.064062 2 | 0 0.826303 0.788281 0.052109 0.070312 3 | 0 0.769851 0.169531 0.048387 0.064062 4 | 2 0.612283 0.308594 0.053350 0.107813 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02941.txt: -------------------------------------------------------------------------------- 1 | 0 0.737593 0.164844 0.053350 0.067187 2 | 0 0.638958 0.782031 0.049628 0.064062 3 | 0 0.788462 0.784375 0.048387 0.065625 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/02961.txt: -------------------------------------------------------------------------------- 1 | 0 0.580645 0.792969 0.054591 0.070312 2 | 0 0.740695 0.797656 0.049628 0.064062 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03011.txt: -------------------------------------------------------------------------------- 1 | 0 0.569479 0.513281 0.047146 0.064062 2 | 0 0.771712 0.355469 0.054591 0.067187 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03021.txt: -------------------------------------------------------------------------------- 1 | 0 0.717742 0.317969 0.050868 0.070312 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03061.txt: -------------------------------------------------------------------------------- 1 | 0 0.561414 0.478906 0.048387 0.057813 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03071.txt: -------------------------------------------------------------------------------- 1 | 2 0.751241 0.465625 0.050868 0.096875 2 | 2 0.868486 0.778906 0.052109 0.101562 3 | 2 0.561414 0.610156 0.055831 0.110937 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03091.txt: -------------------------------------------------------------------------------- 1 | 2 0.339330 0.464062 0.058313 0.093750 2 | 2 0.830645 0.778125 0.048387 0.106250 3 | 0 0.645161 0.482031 0.049628 0.064062 4 | 0 0.768610 0.185156 0.048387 0.067187 5 | 0 0.421836 0.632031 0.049628 0.067187 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03101.txt: -------------------------------------------------------------------------------- 1 | 0 0.591811 0.477344 0.047146 0.067187 2 | 0 0.752481 0.157812 0.050868 0.068750 3 | 2 0.826923 0.771875 0.055831 0.103125 4 | 2 0.380273 0.784375 0.053350 0.087500 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03121.txt: -------------------------------------------------------------------------------- 1 | 0 0.708437 0.165625 0.052109 0.065625 2 | 0 0.857320 0.164844 0.047146 0.067187 3 | 2 0.790323 0.774219 0.057072 0.101562 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03131.txt: -------------------------------------------------------------------------------- 1 | 0 0.746278 0.325781 0.048387 0.064062 2 | 0 0.831886 0.167187 0.050868 0.062500 3 | 2 0.765509 0.779687 0.057072 0.106250 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03171.txt: -------------------------------------------------------------------------------- 1 | 0 0.368486 0.535156 0.047146 0.067187 2 | 0 0.666253 0.535156 0.049628 0.064062 3 | 0 0.490074 0.634375 0.049628 0.068750 4 | 2 0.714640 0.782031 0.076923 0.089063 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03191.txt: -------------------------------------------------------------------------------- 1 | 0 0.578784 0.471094 0.053350 0.070312 2 | 3 0.761787 0.155469 0.054591 0.092188 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03201.txt: -------------------------------------------------------------------------------- 1 | 3 0.739454 0.151562 0.064516 0.087500 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03211.txt: -------------------------------------------------------------------------------- 1 | 3 0.726427 0.150781 0.063275 0.089063 2 | 0 0.846154 0.156250 0.054591 0.053125 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03221.txt: -------------------------------------------------------------------------------- 1 | 0 0.772953 0.160938 0.052109 0.059375 2 | 3 0.706576 0.157031 0.068238 0.089063 3 | 0 0.725186 0.790625 0.045906 0.065625 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03231.txt: -------------------------------------------------------------------------------- 1 | 0 0.567618 0.811719 0.050868 0.067187 2 | 0 0.665012 0.792969 0.047146 0.060937 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03251.txt: -------------------------------------------------------------------------------- 1 | 0 0.765509 0.482031 0.052109 0.060937 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03261.txt: -------------------------------------------------------------------------------- 1 | 0 0.745037 0.472656 0.048387 0.064062 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03271.txt: -------------------------------------------------------------------------------- 1 | 0 0.568859 0.171094 0.045906 0.067187 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03341.txt: -------------------------------------------------------------------------------- 1 | 2 0.697270 0.461719 0.069479 0.089063 2 | 0 0.613524 0.477344 0.048387 0.064062 3 | 0 0.568859 0.793750 0.053350 0.062500 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03361.txt: -------------------------------------------------------------------------------- 1 | 0 0.658809 0.325781 0.052109 0.070312 2 | 0 0.550868 0.480469 0.047146 0.067187 3 | 0 0.547767 0.786719 0.048387 0.064062 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03381.txt: -------------------------------------------------------------------------------- 1 | 0 0.869727 0.221875 0.057072 0.071875 2 | 2 0.728288 0.305469 0.057072 0.098437 3 | 0 0.521092 0.633594 0.052109 0.067187 4 | 2 0.486973 0.782031 0.053350 0.101562 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03391.txt: -------------------------------------------------------------------------------- 1 | 0 0.825062 0.172656 0.047146 0.060937 2 | 0 0.436104 0.791406 0.055831 0.064062 3 | 2 0.698511 0.306250 0.071960 0.096875 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03401.txt: -------------------------------------------------------------------------------- 1 | 0 0.550868 0.475000 0.057072 0.071875 2 | 0 0.377792 0.789062 0.043424 0.065625 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03411.txt: -------------------------------------------------------------------------------- 1 | 0 0.565757 0.493750 0.052109 0.075000 2 | 0 0.566998 0.799219 0.054591 0.054688 3 | 0 0.319479 0.786719 0.055831 0.073438 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03421.txt: -------------------------------------------------------------------------------- 1 | 0 0.530397 0.475000 0.045906 0.062500 2 | 0 0.537221 0.791406 0.052109 0.070312 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03431.txt: -------------------------------------------------------------------------------- 1 | 2 0.372208 0.464062 0.071960 0.096875 2 | 0 0.501861 0.792188 0.053350 0.071875 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03441.txt: -------------------------------------------------------------------------------- 1 | 0 0.338710 0.478906 0.057072 0.067187 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03451.txt: -------------------------------------------------------------------------------- 1 | 0 0.312655 0.477344 0.052109 0.064062 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03461.txt: -------------------------------------------------------------------------------- 1 | 4 0.332506 0.434375 0.081886 0.100000 2 | 4 0.290323 0.477344 0.084367 0.107813 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03471.txt: -------------------------------------------------------------------------------- 1 | 4 0.209057 0.364063 0.088089 0.100000 2 | 4 0.316998 0.471875 0.075682 0.103125 3 | 4 0.283499 0.580469 0.075682 0.085938 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03481.txt: -------------------------------------------------------------------------------- 1 | 4 0.157568 0.325781 0.076923 0.079687 2 | 4 0.107320 0.180469 0.063275 0.085938 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03591.txt: -------------------------------------------------------------------------------- 1 | 2 0.371588 0.310156 0.053350 0.101562 2 | 2 0.568238 0.157031 0.049628 0.095312 3 | 2 0.475806 0.309375 0.060794 0.087500 4 | 2 0.672457 0.310156 0.057072 0.095312 5 | 2 0.764268 0.306250 0.057072 0.100000 6 | 2 0.364144 0.619531 0.058313 0.104688 7 | 2 0.369107 0.781250 0.053350 0.100000 8 | 2 0.568859 0.618750 0.065757 0.096875 9 | 2 0.471464 0.767969 0.054591 0.101562 10 | 2 0.766129 0.617188 0.060794 0.090625 11 | 2 0.872208 0.774219 0.069479 0.095312 12 | 3 0.367246 0.458594 0.057072 0.085938 13 | 3 0.567618 0.786719 0.060794 0.092188 14 | 3 0.568238 0.468750 0.064516 0.087500 15 | 3 0.665012 0.462500 0.059553 0.090625 16 | 3 0.767370 0.466406 0.060794 0.079687 17 | 3 0.866005 0.620313 0.057072 0.087500 18 | 3 0.767990 0.774219 0.066998 0.089063 19 | 3 0.759305 0.156250 0.062035 0.090625 20 | 3 0.866625 0.156250 0.063275 0.087500 21 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03601.txt: -------------------------------------------------------------------------------- 1 | 2 0.328784 0.308594 0.076923 0.107813 2 | 2 0.566377 0.153125 0.065757 0.090625 3 | 2 0.636476 0.301563 0.059553 0.109375 4 | 2 0.719603 0.302344 0.057072 0.104688 5 | 2 0.733871 0.614062 0.058313 0.106250 6 | 2 0.313896 0.625000 0.062035 0.096875 7 | 2 0.311414 0.775781 0.054591 0.107813 8 | 2 0.426179 0.772656 0.065757 0.095312 9 | 2 0.510546 0.625000 0.058313 0.100000 10 | 2 0.835608 0.775000 0.060794 0.100000 11 | 3 0.545285 0.779687 0.055831 0.093750 12 | 3 0.705955 0.782031 0.057072 0.092188 13 | 3 0.537841 0.464844 0.060794 0.095312 14 | 3 0.335608 0.466406 0.060794 0.092188 15 | 3 0.725186 0.154688 0.058313 0.100000 16 | 3 0.853598 0.148438 0.059553 0.100000 17 | 3 0.761166 0.467187 0.060794 0.090625 18 | 3 0.806452 0.621875 0.062035 0.106250 19 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03621.txt: -------------------------------------------------------------------------------- 1 | 2 0.531638 0.142187 0.065757 0.087500 2 | 3 0.632134 0.155469 0.060794 0.085938 3 | 3 0.820099 0.150000 0.064516 0.090625 4 | 3 0.504342 0.471094 0.060794 0.092188 5 | 3 0.598015 0.472656 0.057072 0.098437 6 | 3 0.718983 0.471875 0.058313 0.100000 7 | 3 0.508065 0.783594 0.060794 0.092188 8 | 3 0.629653 0.776563 0.068238 0.087500 9 | 3 0.732010 0.617188 0.059553 0.084375 10 | 0 0.427419 0.320312 0.045906 0.065625 11 | 2 0.220844 0.619531 0.062035 0.098437 12 | 2 0.228288 0.771875 0.057072 0.103125 13 | 2 0.340571 0.775000 0.065757 0.100000 14 | 2 0.406948 0.625000 0.062035 0.109375 15 | 2 0.607940 0.310156 0.054591 0.104688 16 | 2 0.640819 0.304688 0.050868 0.103125 17 | 2 0.673077 0.620313 0.053350 0.106250 18 | 2 0.771712 0.778125 0.064516 0.090625 19 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03631.txt: -------------------------------------------------------------------------------- 1 | 2 0.499380 0.152344 0.050868 0.095312 2 | 2 0.607320 0.304688 0.055831 0.100000 3 | 2 0.377792 0.618750 0.063275 0.084375 4 | 2 0.187345 0.778125 0.049628 0.090625 5 | 2 0.286600 0.774219 0.057072 0.101562 6 | 2 0.745658 0.768750 0.064516 0.090625 7 | 3 0.812035 0.153906 0.063275 0.089063 8 | 3 0.606079 0.160938 0.053350 0.093750 9 | 3 0.592432 0.460938 0.063275 0.081250 10 | 3 0.718983 0.468750 0.058313 0.084375 11 | 3 0.491935 0.464062 0.060794 0.093750 12 | 3 0.498139 0.779687 0.060794 0.090625 13 | 3 0.576303 0.780469 0.058313 0.095312 14 | 0 0.413151 0.317188 0.057072 0.065625 15 | 0 0.179280 0.632812 0.058313 0.068750 16 | 3 0.676799 0.625781 0.050868 0.095312 17 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03641.txt: -------------------------------------------------------------------------------- 1 | 2 0.497519 0.150000 0.069479 0.084375 2 | 2 0.315136 0.621094 0.059553 0.101562 3 | 2 0.254342 0.775000 0.052109 0.093750 4 | 2 0.710918 0.775000 0.069479 0.084375 5 | 2 0.570099 0.306250 0.058313 0.103125 6 | 0 0.396402 0.325781 0.055831 0.073438 7 | 3 0.464640 0.475000 0.063275 0.096875 8 | 3 0.703474 0.470313 0.059553 0.090625 9 | 3 0.559553 0.466406 0.062035 0.089063 10 | 3 0.794665 0.150000 0.058313 0.096875 11 | 3 0.568238 0.158594 0.059553 0.092188 12 | 3 0.644541 0.623437 0.055831 0.100000 13 | 3 0.468362 0.786719 0.055831 0.092188 14 | 3 0.542804 0.770312 0.058313 0.087500 15 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03651.txt: -------------------------------------------------------------------------------- 1 | 3 0.529156 0.153125 0.055831 0.090625 2 | 3 0.774194 0.150781 0.054591 0.095312 3 | 3 0.696650 0.471875 0.063275 0.084375 4 | 3 0.539702 0.467969 0.062035 0.092188 5 | 3 0.452854 0.468750 0.062035 0.090625 6 | 3 0.462779 0.779687 0.062035 0.090625 7 | 2 0.280397 0.616406 0.059553 0.095312 8 | 2 0.469603 0.147656 0.058313 0.101562 9 | 2 0.510546 0.307031 0.050868 0.107813 10 | 0 0.386476 0.314063 0.053350 0.059375 11 | 3 0.593052 0.622656 0.057072 0.082812 12 | 2 0.673697 0.775000 0.057072 0.093750 13 | 2 0.557072 0.309375 0.044665 0.090625 14 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03661.txt: -------------------------------------------------------------------------------- 1 | 2 0.454094 0.153906 0.054591 0.089063 2 | 2 0.483251 0.309375 0.045906 0.096875 3 | 2 0.536600 0.300000 0.043424 0.103125 4 | 2 0.647022 0.782031 0.060794 0.095312 5 | 0 0.366625 0.328125 0.053350 0.075000 6 | 3 0.763648 0.150781 0.060794 0.095312 7 | 3 0.498759 0.153125 0.052109 0.087500 8 | 3 0.439206 0.467969 0.054591 0.085938 9 | 3 0.527916 0.458594 0.060794 0.085938 10 | 3 0.674938 0.462500 0.059553 0.084375 11 | 3 0.547146 0.621094 0.057072 0.085938 12 | 3 0.444789 0.785156 0.055831 0.095312 13 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03671.txt: -------------------------------------------------------------------------------- 1 | 2 0.437965 0.149219 0.059553 0.098437 2 | 2 0.447270 0.304688 0.055831 0.106250 3 | 2 0.507444 0.311719 0.044665 0.110937 4 | 2 0.619107 0.772656 0.064516 0.101562 5 | 3 0.424318 0.778906 0.052109 0.089063 6 | 3 0.400124 0.774219 0.060794 0.092188 7 | 3 0.656328 0.472656 0.059553 0.092188 8 | 3 0.751861 0.150000 0.062035 0.087500 9 | 3 0.402605 0.471875 0.058313 0.090625 10 | 3 0.502481 0.472656 0.062035 0.095312 11 | 3 0.513027 0.616406 0.060794 0.092188 12 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03681.txt: -------------------------------------------------------------------------------- 1 | 3 0.418734 0.156250 0.048387 0.087500 2 | 3 0.731390 0.151562 0.058313 0.090625 3 | 3 0.655087 0.467969 0.057072 0.092188 4 | 3 0.397643 0.467969 0.055831 0.089063 5 | 3 0.483871 0.465625 0.057072 0.090625 6 | 3 0.448511 0.631250 0.058313 0.090625 7 | 3 0.350496 0.776563 0.055831 0.096875 8 | 3 0.410670 0.780469 0.052109 0.092188 9 | 2 0.389578 0.305469 0.054591 0.107813 10 | 2 0.496278 0.307812 0.054591 0.106250 11 | 2 0.510546 0.614062 0.050868 0.100000 12 | 2 0.583127 0.776563 0.062035 0.093750 13 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03691.txt: -------------------------------------------------------------------------------- 1 | 3 0.393300 0.164844 0.081886 0.085938 2 | 3 0.722705 0.144531 0.058313 0.092188 3 | 3 0.640819 0.470313 0.058313 0.100000 4 | 3 0.374690 0.471094 0.057072 0.085938 5 | 3 0.467122 0.460156 0.055831 0.095312 6 | 3 0.422457 0.616406 0.058313 0.079687 7 | 3 0.316377 0.772656 0.069479 0.085938 8 | 3 0.387717 0.778906 0.058313 0.092188 9 | 2 0.364144 0.312500 0.050868 0.096875 10 | 2 0.479529 0.306250 0.050868 0.103125 11 | 2 0.488834 0.624219 0.054591 0.107813 12 | 2 0.549628 0.772656 0.064516 0.095312 13 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03701.txt: -------------------------------------------------------------------------------- 1 | 0 0.335608 0.164844 0.055831 0.060937 2 | 0 0.317618 0.321094 0.052109 0.067187 3 | 2 0.441067 0.308594 0.048387 0.101562 4 | 2 0.448511 0.625781 0.053350 0.098437 5 | 2 0.519231 0.778906 0.065757 0.092188 6 | 3 0.438586 0.467187 0.060794 0.093750 7 | 3 0.633995 0.467187 0.054591 0.090625 8 | 3 0.699752 0.155469 0.052109 0.092188 9 | 3 0.262407 0.778906 0.055831 0.092188 10 | 3 0.373449 0.782031 0.059553 0.095312 11 | 3 0.361663 0.627344 0.063275 0.092188 12 | 3 0.355459 0.467969 0.058313 0.095312 13 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03721.txt: -------------------------------------------------------------------------------- 1 | 0 0.251241 0.170313 0.053350 0.065625 2 | 0 0.232630 0.329688 0.048387 0.062500 3 | 3 0.320720 0.471094 0.058313 0.092188 4 | 3 0.403226 0.462500 0.052109 0.090625 5 | 3 0.289702 0.617188 0.060794 0.084375 6 | 3 0.336228 0.782031 0.062035 0.095312 7 | 3 0.594293 0.472656 0.054591 0.092188 8 | 3 0.669975 0.156250 0.057072 0.093750 9 | 2 0.419975 0.308594 0.053350 0.104688 10 | 2 0.412531 0.621094 0.068238 0.082812 11 | 2 0.462779 0.775000 0.066998 0.081250 12 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03731.txt: -------------------------------------------------------------------------------- 1 | 0 0.225186 0.169531 0.053350 0.067187 2 | 3 0.304591 0.466406 0.055831 0.098437 3 | 3 0.235732 0.626563 0.062035 0.090625 4 | 3 0.375310 0.467187 0.060794 0.090625 5 | 3 0.595533 0.465625 0.059553 0.093750 6 | 3 0.666253 0.145313 0.066998 0.090625 7 | 2 0.390819 0.307031 0.057072 0.110937 8 | 2 0.387097 0.618750 0.064516 0.084375 9 | 2 0.424318 0.775781 0.062035 0.092188 10 | 3 0.314516 0.786719 0.060794 0.092188 11 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03741.txt: -------------------------------------------------------------------------------- 1 | 2 0.379032 0.304688 0.053350 0.096875 2 | 2 0.352357 0.615625 0.054591 0.103125 3 | 2 0.393921 0.781250 0.065757 0.100000 4 | 3 0.639578 0.153125 0.060794 0.100000 5 | 3 0.578164 0.471875 0.059553 0.090625 6 | 3 0.367246 0.461719 0.062035 0.089063 7 | 3 0.275434 0.472656 0.054591 0.092188 8 | 3 0.196650 0.613281 0.063275 0.098437 9 | 3 0.293424 0.778125 0.060794 0.087500 10 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03751.txt: -------------------------------------------------------------------------------- 1 | 3 0.632754 0.149219 0.057072 0.085938 2 | 3 0.568859 0.472656 0.060794 0.095312 3 | 3 0.269851 0.466406 0.053350 0.089063 4 | 3 0.339330 0.465625 0.053350 0.090625 5 | 3 0.279777 0.782813 0.055831 0.093750 6 | 0 0.156948 0.634375 0.048387 0.075000 7 | 2 0.354839 0.307031 0.052109 0.101562 8 | 2 0.327543 0.617969 0.064516 0.098437 9 | 2 0.368486 0.777344 0.066998 0.085938 10 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03771.txt: -------------------------------------------------------------------------------- 1 | 3 0.602357 0.140625 0.065757 0.084375 2 | 3 0.528536 0.471875 0.057072 0.090625 3 | 3 0.218983 0.467187 0.063275 0.090625 4 | 3 0.303970 0.461719 0.059553 0.101562 5 | 2 0.261166 0.625781 0.058313 0.104688 6 | 2 0.297767 0.770312 0.069479 0.087500 7 | 2 0.320099 0.307031 0.057072 0.104688 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03781.txt: -------------------------------------------------------------------------------- 1 | 2 0.301489 0.307031 0.059553 0.110937 2 | 2 0.228288 0.617969 0.054591 0.098437 3 | 3 0.209057 0.464844 0.055831 0.092188 4 | 3 0.279156 0.467969 0.059553 0.092188 5 | 3 0.530397 0.470313 0.063275 0.096875 6 | 3 0.574442 0.157031 0.057072 0.089063 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03791.txt: -------------------------------------------------------------------------------- 1 | 3 0.571960 0.150000 0.064516 0.087500 2 | 3 0.517990 0.471094 0.058313 0.098437 3 | 3 0.186725 0.473438 0.050868 0.096875 4 | 3 0.265509 0.461719 0.064516 0.085938 5 | 2 0.284119 0.307031 0.059553 0.101562 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03801.txt: -------------------------------------------------------------------------------- 1 | 3 0.254963 0.310937 0.053350 0.106250 2 | 3 0.245658 0.464062 0.062035 0.084375 3 | 3 0.505583 0.471875 0.063275 0.096875 4 | 3 0.547146 0.157812 0.064516 0.090625 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03821.txt: -------------------------------------------------------------------------------- 1 | 2 0.228908 0.305469 0.053350 0.104688 2 | 3 0.468362 0.468750 0.063275 0.087500 3 | 3 0.509926 0.155469 0.057072 0.092188 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03841.txt: -------------------------------------------------------------------------------- 1 | 3 0.489454 0.157812 0.055831 0.093750 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/train/03851.txt: -------------------------------------------------------------------------------- 1 | 3 0.477667 0.149219 0.059553 0.095312 2 | 4 0.409429 0.423438 0.071960 0.096875 3 | 4 0.468983 0.425000 0.074442 0.100000 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val.cache: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/datasets/pvz/labels/val.cache -------------------------------------------------------------------------------- /datasets/pvz/labels/val/00031.txt: -------------------------------------------------------------------------------- 1 | 2 0.563275 0.155469 0.057072 0.098437 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/00061.txt: -------------------------------------------------------------------------------- 1 | 0 0.532258 0.792969 0.049628 0.057813 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01591.txt: -------------------------------------------------------------------------------- 1 | 2 0.558313 0.146875 0.054591 0.103125 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01601.txt: -------------------------------------------------------------------------------- 1 | 2 0.537841 0.150781 0.058313 0.110937 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01631.txt: -------------------------------------------------------------------------------- 1 | 2 0.558933 0.622656 0.055831 0.110937 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01651.txt: -------------------------------------------------------------------------------- 1 | 0 0.767990 0.359375 0.052109 0.062500 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01751.txt: -------------------------------------------------------------------------------- 1 | 0 0.758685 0.171875 0.050868 0.071875 2 | 0 0.560794 0.634375 0.049628 0.065625 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01771.txt: -------------------------------------------------------------------------------- 1 | 0 0.550248 0.799219 0.050868 0.070312 2 | 4 0.766129 0.306250 0.090571 0.103125 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01881.txt: -------------------------------------------------------------------------------- 1 | 0 0.734491 0.326562 0.047146 0.062500 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/01891.txt: -------------------------------------------------------------------------------- 1 | 0 0.725806 0.322656 0.047146 0.067187 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02081.txt: -------------------------------------------------------------------------------- 1 | 0 0.748759 0.790625 0.050868 0.068750 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02121.txt: -------------------------------------------------------------------------------- 1 | 0 0.684864 0.792969 0.057072 0.057813 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02161.txt: -------------------------------------------------------------------------------- 1 | 2 0.880273 0.768750 0.065757 0.087500 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02211.txt: -------------------------------------------------------------------------------- 1 | 0 0.341811 0.323437 0.050868 0.065625 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02221.txt: -------------------------------------------------------------------------------- 1 | 0 0.304591 0.317969 0.050868 0.073438 2 | 0 0.769851 0.559375 0.055831 0.062500 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02451.txt: -------------------------------------------------------------------------------- 1 | 0 0.331266 0.785937 0.052109 0.059375 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02511.txt: -------------------------------------------------------------------------------- 1 | 0 0.365385 0.378906 0.048387 0.067187 2 | 0 0.872208 0.217969 0.047146 0.067187 3 | 0 0.767990 0.378125 0.049628 0.065625 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02521.txt: -------------------------------------------------------------------------------- 1 | 0 0.333127 0.321094 0.055831 0.064062 2 | 0 0.863524 0.170313 0.049628 0.062500 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02541.txt: -------------------------------------------------------------------------------- 1 | 0 0.297146 0.317188 0.045906 0.059375 2 | 0 0.669975 0.330469 0.047146 0.064062 3 | 0 0.823821 0.170313 0.047146 0.062500 4 | 0 0.769231 0.791406 0.047146 0.064062 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02551.txt: -------------------------------------------------------------------------------- 1 | 0 0.653846 0.321875 0.054591 0.062500 2 | 0 0.817618 0.166406 0.049628 0.064062 3 | 0 0.737593 0.793750 0.050868 0.068750 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02561.txt: -------------------------------------------------------------------------------- 1 | 2 0.356700 0.310156 0.058313 0.089063 2 | 2 0.369727 0.461719 0.064516 0.085938 3 | 0 0.709677 0.791406 0.052109 0.064062 4 | 0 0.797146 0.170313 0.048387 0.068750 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02611.txt: -------------------------------------------------------------------------------- 1 | 0 0.729529 0.166406 0.054591 0.064062 2 | 0 0.639578 0.789844 0.050868 0.067187 3 | 2 0.634615 0.302344 0.053350 0.101562 4 | 2 0.727047 0.306250 0.057072 0.084375 5 | 3 0.857320 0.160156 0.062035 0.089063 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02731.txt: -------------------------------------------------------------------------------- 1 | 0 0.377171 0.165625 0.047146 0.068750 2 | 0 0.554591 0.171875 0.044665 0.059375 3 | 0 0.468362 0.385937 0.045906 0.062500 4 | 3 0.698511 0.158594 0.062035 0.098437 5 | 3 0.825682 0.778906 0.058313 0.092188 6 | 2 0.706576 0.622656 0.053350 0.098437 7 | 2 0.694169 0.774219 0.055831 0.107813 8 | 2 0.591811 0.464062 0.062035 0.093750 9 | 2 0.529156 0.157812 0.048387 0.106250 10 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02821.txt: -------------------------------------------------------------------------------- 1 | 3 0.562655 0.159375 0.060794 0.096875 2 | 3 0.703474 0.778906 0.059553 0.092188 3 | 0 0.694169 0.477344 0.045906 0.060937 4 | 2 0.476427 0.616406 0.057072 0.095312 5 | 0 0.363524 0.787500 0.052109 0.071875 6 | 2 0.862903 0.772656 0.068238 0.098437 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02841.txt: -------------------------------------------------------------------------------- 1 | 3 0.544665 0.156250 0.057072 0.090625 2 | 3 0.689206 0.768750 0.065757 0.081250 3 | 0 0.662531 0.476562 0.039702 0.059375 4 | 0 0.633995 0.467187 0.052109 0.056250 5 | 2 0.800248 0.780469 0.059553 0.092188 6 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02851.txt: -------------------------------------------------------------------------------- 1 | 3 0.547767 0.157031 0.058313 0.092188 2 | 2 0.370968 0.625781 0.057072 0.101562 3 | 0 0.609181 0.471094 0.047146 0.054688 4 | 0 0.647643 0.476562 0.057072 0.059375 5 | 3 0.666873 0.783594 0.055831 0.092188 6 | 2 0.784739 0.776563 0.060794 0.090625 7 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02911.txt: -------------------------------------------------------------------------------- 1 | 2 0.669355 0.306250 0.063275 0.084375 2 | 0 0.716501 0.790625 0.048387 0.068750 3 | 0 0.844293 0.785937 0.050868 0.059375 4 | 3 0.596154 0.767188 0.050868 0.090625 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/02971.txt: -------------------------------------------------------------------------------- 1 | 0 0.726427 0.783594 0.043424 0.067187 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03081.txt: -------------------------------------------------------------------------------- 1 | 2 0.375310 0.460938 0.060794 0.093750 2 | 2 0.707196 0.461719 0.049628 0.098437 3 | 2 0.855459 0.772656 0.055831 0.114062 4 | 0 0.490695 0.633594 0.053350 0.067187 5 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03111.txt: -------------------------------------------------------------------------------- 1 | 0 0.730769 0.163281 0.052109 0.060937 2 | 0 0.552109 0.481250 0.049628 0.065625 3 | 2 0.803350 0.780469 0.053350 0.107813 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03141.txt: -------------------------------------------------------------------------------- 1 | 0 0.698511 0.317969 0.049628 0.064062 2 | 2 0.759305 0.769531 0.052109 0.110937 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03151.txt: -------------------------------------------------------------------------------- 1 | 2 0.576923 0.701562 0.054591 0.115625 2 | 2 0.739454 0.776563 0.054591 0.093750 3 | 0 0.666253 0.480469 0.042184 0.057813 4 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03161.txt: -------------------------------------------------------------------------------- 1 | 2 0.548387 0.624219 0.057072 0.104688 2 | 2 0.723945 0.769531 0.045906 0.107813 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03181.txt: -------------------------------------------------------------------------------- 1 | 0 0.337469 0.477344 0.049628 0.067187 2 | 0 0.624690 0.475781 0.045906 0.064062 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03321.txt: -------------------------------------------------------------------------------- 1 | 0 0.761787 0.794531 0.044665 0.064062 2 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03331.txt: -------------------------------------------------------------------------------- 1 | 2 0.736973 0.467969 0.052109 0.104688 2 | 2 0.658809 0.464844 0.062035 0.089063 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03351.txt: -------------------------------------------------------------------------------- 1 | 0 0.563275 0.798438 0.052109 0.075000 2 | 0 0.583747 0.480469 0.048387 0.057813 3 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03611.txt: -------------------------------------------------------------------------------- 1 | 2 0.536600 0.153906 0.055831 0.104688 2 | 2 0.630273 0.303906 0.047146 0.104688 3 | 2 0.683623 0.304688 0.054591 0.115625 4 | 2 0.263027 0.616406 0.052109 0.101562 5 | 2 0.276675 0.771875 0.057072 0.096875 6 | 2 0.377171 0.778906 0.057072 0.104688 7 | 2 0.470223 0.615625 0.062035 0.100000 8 | 2 0.701613 0.621875 0.058313 0.096875 9 | 2 0.801489 0.776563 0.066998 0.096875 10 | 3 0.531017 0.783594 0.049628 0.092188 11 | 3 0.673077 0.777344 0.055831 0.092188 12 | 3 0.687965 0.151562 0.055831 0.093750 13 | 3 0.826923 0.153125 0.063275 0.090625 14 | 3 0.531017 0.470313 0.062035 0.096875 15 | 3 0.626551 0.463281 0.057072 0.082812 16 | 3 0.736352 0.460156 0.060794 0.085938 17 | 3 0.767370 0.621094 0.055831 0.098437 18 | 0 0.431141 0.323437 0.048387 0.065625 19 | 3 0.303350 0.460938 0.060794 0.093750 20 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03761.txt: -------------------------------------------------------------------------------- 1 | 2 0.337469 0.302344 0.054591 0.101562 2 | 2 0.295285 0.619531 0.054591 0.107813 3 | 2 0.333127 0.774219 0.065757 0.095312 4 | 3 0.246898 0.475000 0.057072 0.096875 5 | 3 0.312035 0.468750 0.058313 0.090625 6 | 3 0.606700 0.160156 0.059553 0.089063 7 | 3 0.551489 0.463281 0.058313 0.092188 8 | -------------------------------------------------------------------------------- /datasets/pvz/labels/val/03811.txt: -------------------------------------------------------------------------------- 1 | 2 0.245037 0.303125 0.055831 0.103125 2 | 3 0.539082 0.144531 0.060794 0.085938 3 | 3 0.489454 0.466406 0.060794 0.089063 4 | 3 0.149504 0.470313 0.058313 0.096875 5 | -------------------------------------------------------------------------------- /datasets/pvz/pvztrain.yaml: -------------------------------------------------------------------------------- 1 | path: D:\yolov8\datasets\pvz # dataset root dir 2 | train: images # train images (relative to 'path') 128 images 3 | val: images # val images (relative to 'path') 128 images 4 | 5 | names: 6 | 0: common 7 | 1: hat 8 | 2: cat 9 | 3: iron 10 | 4: sun -------------------------------------------------------------------------------- /pvz_train.py: -------------------------------------------------------------------------------- 1 | from ultralytics import YOLO 2 | 3 | def main(): 4 | # Load model 5 | model = YOLO("yolov8n.pt") 6 | 7 | # Train 8 | model.train(data="datasets/pvz/pvztrain.yaml", epochs=250,patience=150) 9 | 10 | # Validate 11 | model.val() 12 | 13 | if __name__ == "__main__": 14 | main() 15 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | 2 | matplotlib>=3.2.2 3 | numpy>=1.22.2 # pinned by Snyk to avoid a vulnerability 4 | opencv-python>=4.6.0 5 | pillow>=7.1.2 6 | pyyaml>=5.3.1 7 | requests>=2.23.0 8 | scipy>=1.4.1 9 | torch>=1.7.0 10 | torchvision>=0.8.1 11 | tqdm>=4.64.0 12 | # tensorboard>=2.13.0 13 | # dvclive>=2.12.0 14 | # clearml 15 | pandas>=1.1.4 16 | seaborn>=0.11.0 17 | 18 | # coremltools>=6.0,<=6.2 # CoreML export 19 | # onnx>=1.12.0 # ONNX export 20 | # onnxsim>=0.4.1 # ONNX simplifier 21 | # nvidia-pyindex # TensorRT export 22 | # nvidia-tensorrt # TensorRT export 23 | # scikit-learn==0.19.2 # CoreML quantization 24 | # tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos) 25 | # tflite-support 26 | # tensorflowjs>=3.9.0 # TF.js export 27 | # openvino-dev>=2023.0 # OpenVINO export 28 | psutil # system utilization 29 | py-cpuinfo # display CPU info 30 | # thop>=0.1.1 # FLOPs computation 31 | # ipython # interactive notebook 32 | # albumentations>=1.0.3 # training augmentations 33 | # pycocotools>=2.0.6 # COCO mAP 34 | # roboflow 35 | -------------------------------------------------------------------------------- /runs/detect/predict/test2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/runs/detect/predict/test2.png -------------------------------------------------------------------------------- /runs/detect/train/F1_curve.png: 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25 | cos_lr: false 26 | close_mosaic: 10 27 | resume: false 28 | amp: true 29 | fraction: 1.0 30 | profile: false 31 | freeze: null 32 | multi_scale: false 33 | overlap_mask: true 34 | mask_ratio: 4 35 | dropout: 0.0 36 | val: true 37 | split: val 38 | save_json: false 39 | save_hybrid: false 40 | conf: null 41 | iou: 0.7 42 | max_det: 300 43 | half: false 44 | dnn: false 45 | plots: true 46 | source: null 47 | vid_stride: 1 48 | stream_buffer: false 49 | visualize: false 50 | augment: false 51 | agnostic_nms: false 52 | classes: null 53 | retina_masks: false 54 | embed: null 55 | show: false 56 | save_frames: false 57 | save_txt: false 58 | save_conf: false 59 | save_crop: false 60 | show_labels: true 61 | show_conf: true 62 | show_boxes: true 63 | line_width: null 64 | format: torchscript 65 | keras: false 66 | optimize: false 67 | int8: false 68 | dynamic: false 69 | simplify: false 70 | opset: null 71 | workspace: 4 72 | nms: false 73 | lr0: 0.01 74 | lrf: 0.01 75 | momentum: 0.937 76 | weight_decay: 0.0005 77 | warmup_epochs: 3.0 78 | warmup_momentum: 0.8 79 | warmup_bias_lr: 0.1 80 | box: 7.5 81 | cls: 0.5 82 | dfl: 1.5 83 | pose: 12.0 84 | kobj: 1.0 85 | label_smoothing: 0.0 86 | nbs: 64 87 | hsv_h: 0.015 88 | hsv_s: 0.7 89 | hsv_v: 0.4 90 | degrees: 0.0 91 | translate: 0.1 92 | scale: 0.5 93 | shear: 0.0 94 | perspective: 0.0 95 | flipud: 0.0 96 | fliplr: 0.5 97 | bgr: 0.0 98 | mosaic: 1.0 99 | mixup: 0.0 100 | copy_paste: 0.0 101 | auto_augment: randaugment 102 | erasing: 0.4 103 | crop_fraction: 1.0 104 | cfg: null 105 | tracker: botsort.yaml 106 | save_dir: runs\detect\train 107 | -------------------------------------------------------------------------------- /runs/detect/train/confusion_matrix.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/runs/detect/train/confusion_matrix.png 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epochs=100, batch=4) 12 | 13 | # 评估模型在验证集上的性能 14 | results = model.val() 15 | 16 | # 使用模型对图片进行目标检测 17 | results = model('test/test.jpg') 18 | 19 | # 将模型导出为ONNX格式 20 | success = model.export(format='onnx') -------------------------------------------------------------------------------- /test/test.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/test/test.jpg -------------------------------------------------------------------------------- /test/test1.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/pan0624/Yolov8-target-detection-and-simulation-click/a6e1d91bc4cb632351f1c35a8e104156cbc3de13/test/test1.mp4 -------------------------------------------------------------------------------- /test/test2.mp4: 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success, frame = cap.read() 15 | if not success: 16 | break 17 | 18 | # 在帧上运行YOLOv8检测 19 | results = model.predict(frame) 20 | 21 | # 检查是否有检测结果 22 | if results: 23 | # 获取框和类别信息 24 | boxes = results[0].boxes.xyxy.cpu().numpy() # 修改为获取xyxy格式的边界框，并转换为numpy数组 25 | classes = results[0].boxes.cls.cpu().numpy() # 获取类别索引，并转换为numpy数组 26 | 27 | # 在帧上展示结果 28 | annotated_frame = results[0].plot() # 绘制检测结果 29 | 30 | # 展示带注释的帧 31 | annotated_frame = cv2.resize(annotated_frame, (640, 480)) 32 | cv2.imshow('YOLOv8 Detection', annotated_frame) 33 | else: 34 | # 如果没有检测结果，直接展示原始帧 35 | cv2.imshow('YOLOv8 Detection', frame) 36 | 37 | # 如果按下'q'则退出循环 38 | if cv2.waitKey(1) & 0xFF == ord('q'): 39 | break 40 | 41 | # 释放视频捕获对象并关闭显示窗口 42 | cap.release() 43 | cv2.destroyAllWindows() -------------------------------------------------------------------------------- /yolov8n-seg.pt: -------------------------------------------------------------------------------- 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