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# Automatic pedestrian detection and monitoring system based on Deep Learning
[中文文档](https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/blob/master/README_zh.md)<br>
Monitoring plays an important role in security and inspections, but it is also a very tedious task. The emergence of deep learning has liberated humans from this task to some extent. This project builds a simple and effective monitoring system based on the goal detection of deep learning, which can automate the flow statistics and pedestrian detection.
**This system is based on the Apache2.0 protocol open source, please strictly abide by the open source agreement.**
# 0x00 Introduction
The system consists of the following three sub-projects: <br>
- 1.Pedestrian detection system based on TensorFlow platform
- 2.Push flow system based on Android platform
- 3.JavaWeb-based display system
The overall framework is shown below:
<img src="https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/raw/master/img/framework.png" width="400" height="300">
# 0x01 Server Deployment
## 1.Server configuration requirements
| Configuration | Basic requirements |
| ---------- | ------- |
| OS | Ubuntu 16.04 x64 |
| CPU | Main frequency 2.0GHz or more |
| RAM | 8G or more |
| GPU | NVIDIA GTX1080 or more |
| Network | The server IP address needs to be the public IP address. |
## 2.Pedestrian detection system based on TensorFlow platform
The system relies on the following:
| Dependency | Installation method |
| ---------- | ------ |
| Python3.5 | Skip |
| pip | Skip |
| TensorFlow-1.11.0-GPU | Skip |
| Python version - OpenCV | Skip |
| requests | pip3 install requests |
| frozen_inference_graph.pb | [Download Link](https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/releases/download/v1.0/frozen_inference_graph.pb) |
| Nginx with RTMP | [Installation Process](https://www.jianshu.com/p/b4ee6956d1ea) |
How to run the system:
- Copy the `.pb` model file obtained after training the model in the `python`directory;
- Modify the `RTMP_HOST` variable in the `main.py`file and run`main.py`;
## 3.Push flow system based on Android platform
How to run the system:
- Import the project in the 'android' directory in an integrated development environment such as IDEA or AndroidStudio,and modify the static variavles in 'MainActivity.java';
## 4.Display system based on SSM (SpringMVC+Spring+Mybatis) Internet lightweight framework
The system relies on the following
| Dependency | Installation method |
| ---------- | ------ |
| JDK-1.8.0 | Skip |
| Apache-Tomcat-9.0.12 | Skip |
| Maven | Skip |
| Mysql | Need to configure remote access rights |
How to run the system:
- The system is developed based on the IDEA integrated development environment. The dependencies in the SSM framework are all based on Maven configuration. Import the project under the `web` directory in Idea, export the `war` package, and put the `war` package on the server `tomcat/webapps` directory, run `./startup.sh` to start the `tomcat` container
# 0x02 Project Display
<img src="https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/raw/master/img/example2.jpg" width="600" height="300">
<img src="https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/raw/master/img/example1.png" width="700" height="400">
<img src="https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/raw/master/img/example3.jpg" width="700" height="400">
- Added visual view of human flow statistics for large data volumes;
<img src="https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/raw/master/img/example4.png" width="700" height="600">
- Show the full effect of the pedestrian detection project,[Display link](https://pan.baidu.com/s/1X7BX5QSbqZFx2Y6XElW4ZA);
# 0x03 About
- How to support the author: Click on **star** button in the upper right corner is the maximum support of the author;
- If you have questions or discuss the pedestrian detection algorithm model, please [submit an issue](https://github.com/zhangpengpengpeng/PedestrianDetectionSystem/issues/new),thanks;
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基于Python+TensorFlow的自动化行人检测(人体检测)和监控(视频监控)系统源码+数据集+详细文档(高分毕业设计)
共252个文件
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jar:41个
xml:34个
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【资源说明】 基于Python+TensorFlow的自动化行人检测(人体检测)和监控(视频监控)系统。源码+数据集+详细文档(高分毕业设计).zip基于Python+TensorFlow的自动化行人检测(人体检测)和监控(视频监控)系统。源码+数据集+详细文档(高分毕业设计).zip基于Python+TensorFlow的自动化行人检测(人体检测)和监控(视频监控)系统。源码+数据集+详细文档(高分毕业设计).zip 【备注】 1、该资源内项目代码都经过测试运行成功,功能ok的情况下才上传的,请放心下载使用! 2、本项目适合计算机相关专业(如软件工程、计科、人工智能、通信工程、自动化、电子信息等)的在校学生、老师或者企业员工下载使用,也可作为毕设项目、课程设计、作业、项目初期立项演示等,当然也适合小白学习进阶。 3、如果基础还行,可以在此代码基础上进行修改,以实现其他功能,也可直接用于毕设、课设、作业等。 欢迎下载,沟通交流,互相学习,共同进步!
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基于Python+TensorFlow的自动化行人检测(人体检测)和监控(视频监控)系统源码+数据集+详细文档(高分毕业设计) (252个子文件)
gradlew.bat 2KB
UserController.class 5KB
UserController.class 5KB
RootConfig.class 4KB
RootConfig.class 4KB
ChannelController.class 3KB
ChannelController.class 3KB
TrafficController.class 3KB
TrafficController.class 3KB
LoginFilter.class 2KB
LoginFilter.class 2KB
WebConfig.class 2KB
WebConfig.class 2KB
DateServiceImpl.class 2KB
DateServiceImpl.class 2KB
UserServiceImpl.class 2KB
UserServiceImpl.class 2KB
SessionListener.class 2KB
SessionListener.class 2KB
User.class 1KB
User.class 1KB
Date.class 1009B
Date.class 1009B
WebAppInitializer.class 886B
WebAppInitializer.class 886B
DateMapper.class 672B
DateMapper.class 672B
UserMapper.class 561B
UserMapper.class 561B
DateService.class 340B
DateService.class 340B
UserService.class 288B
UserService.class 288B
bootstrap.css 143KB
bootstrap.css 143KB
bootstrap.min.css 141KB
bootstrap.min.css 141KB
bootstrap-theme.css 26KB
bootstrap-theme.css 26KB
bootstrap-theme.min.css 23KB
bootstrap-theme.min.css 23KB
pricing.css 418B
pricing.css 418B
.gitignore 97B
.gitignore 7B
build.gradle 2KB
build.gradle 868B
settings.gradle 15B
gradlew 5KB
PeopleDetection.iml 80B
javaee-api-7.0.jar 1.84MB
aspectjweaver-1.8.10.jar 1.84MB
mybatis-3.4.1.jar 1.51MB
jackson-databind-2.8.7.jar 1.18MB
spring-context-4.3.5.RELEASE.jar 1.08MB
spring-core-4.3.5.RELEASE.jar 1.06MB
mysql-connector-java-5.1.41.jar 970KB
spring-webmvc-4.3.5.RELEASE.jar 893KB
spring-web-4.3.5.RELEASE.jar 797KB
spring-beans-4.3.5.RELEASE.jar 744KB
hibernate-validator-5.2.4.Final.jar 688KB
mchange-commons-java-0.2.11.jar 592KB
javax.mail-1.5.0.jar 510KB
mybatis-generator-core-1.3.2.jar 504KB
c3p0-0.9.5.2.jar 486KB
log4j-1.2.17.jar 478KB
spring-jdbc-4.3.5.RELEASE.jar 417KB
jstl-1.2.jar 405KB
spring-aop-4.3.5.RELEASE.jar 371KB
jackson-core-2.8.7.jar 276KB
spring-tx-4.3.5.RELEASE.jar 261KB
spring-expression-4.3.5.RELEASE.jar 257KB
spring-context-support-4.3.5.RELEASE.jar 183KB
commons-io-2.2.jar 170KB
commons-collections-2.1.jar 161KB
aspectjrt-1.8.9.jar 115KB
commons-pool-1.6.jar 109KB
xml-apis-1.0.b2.jar 107KB
commons-dbcp-1.2.jar 100KB
javax.servlet-api-3.1.0.jar 94KB
commons-fileupload-1.3.1.jar 67KB
jboss-logging-3.2.1.Final.jar 65KB
jackson-annotations-2.9.0.jar 65KB
validation-api-1.1.0.Final.jar 62KB
activation-1.1.jar 62KB
classmate-1.1.0.jar 61KB
commons-logging-1.2.jar 60KB
gradle-wrapper.jar 52KB
mybatis-spring-1.3.1.jar 52KB
javax.servlet.jsp-api-2.3.1.jar 52KB
aopalliance-1.0.jar 4KB
RecordActivity.java 18KB
UserController.java 5KB
RootConfig.java 3KB
MainActivity.java 2KB
ChannelController.java 2KB
WelcomeActivity.java 2KB
TrafficController.java 2KB
UserServiceImpl.java 2KB
LoginFilter.java 2KB
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