yolov5 deepsort 行人 车辆 跟踪 检测 计数

Overview

yolov5 deepsort 行人 车辆 跟踪 检测 计数

  • 实现了 出/入 分别计数。
  • 默认是 南/北 方向检测,若要检测不同位置和方向,可在 main.py 文件第13行和21行,修改2个polygon的点。
  • 默认检测类别:行人、自行车、小汽车、摩托车、公交车、卡车。
  • 检测类别可在 detector.py 文件第60行修改。

视频

bilibili

bilibili

运行环境

  • python 3.6+,pip 20+
  • pytorch
  • pip install -r requirements.txt

如何运行

  1. 下载代码

    $ git clone https://github.com/dyh/unbox_yolov5_deepsort_counting.git
    

    因此repo包含weights及mp4等文件,若 git clone 速度慢,可直接下载zip文件:https://github.com/dyh/unbox_yolov5_deepsort_counting/archive/main.zip

  2. 进入目录

    $ cd unbox_yolov5_deepsort_counting
    
  3. 创建 python 虚拟环境

    $ python3 -m venv venv
    
  4. 激活虚拟环境

    $ source venv/bin/activate
    
  5. 升级pip

    $ python -m pip install --upgrade pip
    
  6. 安装pytorch

    根据你的操作系统、安装工具以及CUDA版本,在 https://pytorch.org/get-started/locally/ 找到对应的安装命令。我的环境是 ubuntu 18.04.5、pip、CUDA 11.0。

    $ pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio===0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
    
  7. 安装软件包

    $ pip install -r requirements.txt
    
  8. 在 main.py 文件中第66行,设置要检测的视频文件路径,默认为 './video/test.mp4'

    140MB的测试视频可以在这里下载:https://pan.baidu.com/s/1geqjht-no0iyzQ88JQopwA 密码: i6cs

    capture = cv2.VideoCapture('./video/test.mp4')
    
  9. 运行程序

    python main.py
    

引用

Comments
  • 怎麽使用自己的訓練好的模型?

    怎麽使用自己的訓練好的模型?

    我有訓練自己的模型,4個模型都有做訓練,但當我放入自己的模型且在models中添加了關於這個模型的yaml檔案后,在更改了detector.py中self.weights的路徑后出現錯誤 AttributeError: Can't get attribute 'C3' on <module 'models.common' from 'C:\Users\User\Desktop\yolov5\unbox_yolov5_deepsort_counting\models\common.py'> 請問這個要如何解決?

    opened by manmo-hut 8
  • qt5

    qt5

    This application failed to start because no Qt platform plugin could be initialized. Reinstalling the application may fix this problem.

    Available platform plugins are: xcb.

    opened by jiangyuanlin01 1
  • opencv

    opencv

    cv2.error: OpenCV(4.5.1) /tmp/pip-req-build-s8zh4qlk/opencv/modules/highgui/src/window.cpp:651: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvShowImage'

    opened by jiangyuanlin01 1
  • mac电脑无法运行,有谁运行成功的吗?

    mac电脑无法运行,有谁运行成功的吗?

    我在colab上可以,mac pro电脑无法运行,有谁运行成功的吗?

    (unbox_yolov5_deepsort_counting-main) ➜ unbox_yolov5_deepsort_counting-main python main.py Fatal Python error: Segmentation fault

    Thread 0x000000010825e600 (most recent call first): File "<[1] 19053 segmentation fault python main.py

    opened by ziqiflow 0
  • loade()少一个参数

    loade()少一个参数

    self.update(yaml.load(fo.read()))
    

    TypeError: load() missing 1 required positional argument: 'Loader'

    修改为: self.update(yaml.load(fo.read(),Loader=yaml.SafeLoader))

    opened by z-z-zhao 1
Owner
Unbox AI
null
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~

YOLOv5-Lite:lighter, faster and easier to deploy Perform a series of ablation experiments on yolov5 to make it lighter (smaller Flops, lower memory, a

pogg 1.5k Jan 5, 2023
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-Captured Scenarios

TPH-YOLOv5 This repo is the implementation of "TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-Captured

cv516Buaa 439 Dec 22, 2022
Multi-task yolov5 with detection and segmentation based on yolov5

YOLOv5DS Multi-task yolov5 with detection and segmentation based on yolov5(branch v6.0) decoupled head anchor free segmentation head README中文 Ablation

null 150 Dec 30, 2022
Yolov5-lite - Minimal PyTorch implementation of YOLOv5

Yolov5-Lite: Minimal YOLOv5 + Deep Sort Overview This repo is a shortened versio

Kadir Nar 57 Nov 28, 2022
Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

Object tracking implemented with YOLOv4, DeepSort, and TensorFlow. YOLOv4 is a state of the art algorithm that uses deep convolutional neural networks to perform object detections. We can take the output of YOLOv4 feed these object detections into Deep SORT (Simple Online and Realtime Tracking with a Deep Association Metric) in order to create a highly accurate object tracker.

The AI Guy 1.1k Dec 29, 2022
using yolox+deepsort for object-tracker

YOLOX_deepsort_tracker yolox+deepsort实现目标跟踪 最新的yolox尝尝鲜~~(yolox正处在频繁更新阶段,因此直接链接yolox仓库作为子模块) Install Clone the repository recursively: git clone --rec

null 245 Dec 26, 2022
Vehicles Counting using YOLOv4 + DeepSORT + Flask + Ngrok

A project for counting vehicles using YOLOv4 + DeepSORT + Flask + Ngrok

Duong Tran Thanh 37 Dec 16, 2022
StrongSORT: Make DeepSORT Great Again

StrongSORT StrongSORT: Make DeepSORT Great Again StrongSORT: Make DeepSORT Great Again Yunhao Du, Yang Song, Bo Yang, Yanyun Zhao arxiv 2202.13514 Abs

null 369 Jan 4, 2023
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Yolov5 running on TorchServe (GPU compatible) ! This is a dockerfile to run TorchServe for Yolo v5 object detection model. (TorchServe (PyTorch librar

null 82 Nov 29, 2022
YOLOv5 in PyTorch > ONNX > CoreML > TFLite

This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and evolution on anonymized client datasets. All code and models are under active development, and are subject to modification or deletion without notice.

Ultralytics 34.1k Dec 31, 2022
null 202 Jan 6, 2023
Drone detection using YOLOv5

This drone detection system uses YOLOv5 which is a family of object detection architectures and we have trained the model on Drone Dataset. Overview I

Tushar Sarkar 27 Dec 20, 2022
joint detection and semantic segmentation, based on ultralytics/yolov5,

Multi YOLO V5——Detection and Semantic Segmentation Overeview This is my undergraduate graduation project which based on ultralytics YOLO V5 tag v5.0.

null 477 Jan 6, 2023
This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes.

Polygon-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes. Section I. Description The codes a

xinzelee 226 Jan 5, 2023
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset

YOLOv5 ?? is a family of object detection architectures and models pretrained on the COCO dataset, and represents Ultralytics open-source research int

阿才 73 Dec 16, 2022
A graphical Semi-automatic annotation tool based on labelImg and Yolov5

??YOLOV5 semi-automatic annotation tool (Based on labelImg)

EricFang 247 Jan 5, 2023
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~

pogg 1.5k Jan 5, 2023
This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes.

Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are

xinzelee 90 Dec 13, 2022
Add gui for YoloV5 using PyQt5

<<<<<<< HEAD 更新2021.08.16 **添加图片和视频保存功能: 1.图片和视频按照当前系统时间进行命名 2.各自检测结果存放入output文件夹 3.摄像头检测的默认设备序号更改为0,减少调试报错 温馨提示: 1.项目放置在全英文路径下,防止项目报错 2.默认使用cpu进行检测,自

Ruihao Wang 65 Dec 27, 2022