⚡Real-Time Person Re-ID in Multi-Camera Surveillance Systems⚡

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Introduction

This project leverages a combination of cutting-edge technologies, including Apache Kafka and Apache Spark, along with straightforward Deep Learning Models like YOLOv5 (for Human Detection) and ResNet (for Person Re-identification). The primary objective is to tackle the challenge of Person Re-identification in real-time within a given scenario.

In the context of a building equipped with multiple cameras, the aim is to detect individuals across these camera feeds and assign unique IDs to each person. Notably, a person may initially appear in one camera and subsequently reappear in another. The overarching objective is to seamlessly identify the same individual across these cameras by associating them with a consistent ID—a task commonly referred to as Person Re-identification.

Project overview

This project presents a real-time Person Re-identification System using Deep Learning techniques. The system is designed to (1) process video streams, (2) detect persons in the video and (3) identify them based on their features.

The project is structured around several key components:

• The Producer.py and Consumer.py scripts handle the ingestion and consumption of data.
• The realtime_reid module contains the core functionality of the system, including person detection (person_detector.py), feature extraction (feature_extraction.py), and person identification (classifier.py).
• The streaming module includes services for video production (kafka_services/video_producer.py) and data processing (spark_services/spark_processing.py).
• The project is configured via a settings.json file (TODO) and dependencies are managed through a requirements.txt file.

Prerequisites

• Python 3.11
• Apache Spark (>= 3.5.0)
• Apache Kafka (>= 3.6.0)

Note:

• I tested this on python=3.12 (November 2023) but it didn't work. You can test it on the latest version, if it still doesn't work, I recommend using python=3.11.

Getting Started

• Install Apache Spark and Apache Kafka (Remember to test if it works).

• Clone this repository

• Create a Python environment and install the necessary packages

conda create -n human_reid python=3.11
conda activate human_reid
pip install -r requirements.txt

• There are 2 models needed for this project:
  • A YOLOv5 model (yolov5s.pt) for Human Detection. The model will be automatically downloaded when you run the code for the first time, or if you want to use your own yolov5 model, you can put it in the checkpoints/ folder.
  • A ResNet50 model (resnet50_model.pt) for Person Re-identification (Feature Extraction specifically). This model is required, put it in the checkpoints/ folder.

Usage

• Run Zookeeper

/path/to/your/kafka/bin/zookeeper-server-start.sh /path/to/your/kafka/config/zookeeper.properties

• Run Kafka

/path/to/your/kafka/bin/kafka-server-start.sh /path/to/your/kafka/config/server.properties

• Run the Consumer. You can run python Consumer.py --help to see the arguments.

python Consumer.py --topic topic_name --topic-2 topic_name_2 --reid y

• Run Producers to publish recorded footage from our cameras on these topics (run each producer separately).

python Producer.py --topic topic_name --camera /path/to/your/video.mp4

python Producer.py --topic topic_name_2 --camera /path/to/your/video.mp4

• A cv2 window will pop up if the producer is running successfully (2 windows if run 2 topics).

Contribution

This repo is continuously fixed and updated over time, feel free to fix some issues/bugs, all are welcome here!

About Us

We are a Group of Students majoring in Data Science at University of Information Technology (UIT), VNU-HCM of Vietnam.