I will build a custom real time ai cctv tracking and alert system with opencv
Turn your CCTV and sports footage into real time AI tracking camera analytics
Sobre este Serviço
Do you need your CCTV system to automatically understand what is happening instead of simply recording video? I build custom real time AI tracking and alert systems that process live camera feeds, detect relevant objects, follow their movement, and trigger useful events based on your requirements.
This service is suitable for sports venues, training facilities, sports tech products, research projects, and custom video intelligence applications where real-time computer vision is required.
What I will do:
- Connect and process your supported CCTV, IP camera, RTSP, or video source.
- Build real time object detection for your required targets.
- Implement multi object tracking and identity continuity.
- Configure zones, lines, regions, or custom detection rules.
- Create event triggered alerts based on your project requirements.
- Add OpenCV based visualization, logging, analytics, or data export.
- Optimize and document the pipeline for your target hardware and workflow.
I can tailor the system around your latency, resolution, camera, hardware, Message me with your camera setup and use case.
Linguagem de programação:
Python
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R
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MATLAB
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SQL
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Colab
Frameworks:
Scikit-learn
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DeepPy
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Google ML Kit
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SimpleCV
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keras
Perguntas frequentes
Does this work with RTSP and IP camera streams?
Yes, compatible RTSP and IP camera feeds can be integrated into the system. Before development, I would need the stream specifications and details about your camera resolution, frame rate, network environment, and target hardware.
Can the system send alerts when a specific event happens?
Yes. Custom event rules can be implemented when the requested event can be reliably detected from the video. The alert mechanism can be designed around your workflow and technical requirements.
Can you optimize the AI system for real time performance?
Yes. I can consider model size, resolution, frame rate, tracking method, hardware, and processing architecture to reduce latency and improve practical real time performance. The achievable performance depends on the model complexity and your hardware.
