Multi-Stream, Multi-Model ANPR System Development
Budget: ₹600 – ₹1,500 INR
ANPR Integration Using YOLO & EfficientNet (Multi-Model, Multi-Video Support)
Project Description:
I’m working on an Automatic Number Plate Recognition (ANPR) system and need an experienced developer to help with model integration and optimization.
Key Requirements:
I already have 5 trained models (based on YOLO and EfficientNet).
The task is to combine these models into a single, unified pipeline.
The integrated system must:
Process at least 5 video streams simultaneously
Avoid skipping any vehicles or number plates
Run efficiently with minimal CPU/GPU load
Preferred Skills:
Strong experience with YOLO (v5/v8) and EfficientNet
Python (preferred) or any language suitable for deployment
Knowledge of multithreading/multiprocessing and real-time video processing
Previous work with ANPR, object detection, or computer vision
Deliverables:
Fully working, integrated ANPR solution
Code and setup instructions
Test run with 5 sample videos
Only apply if you have prior experience in YOLO-based object detection and real-time video processing.
Project Description:
I’m working on an Automatic Number Plate Recognition (ANPR) system and need an experienced developer to help with model integration and optimization.
Key Requirements:
I already have 5 trained models (based on YOLO and EfficientNet).
The task is to combine these models into a single, unified pipeline.
The integrated system must:
Process at least 5 video streams simultaneously
Avoid skipping any vehicles or number plates
Run efficiently with minimal CPU/GPU load
Preferred Skills:
Strong experience with YOLO (v5/v8) and EfficientNet
Python (preferred) or any language suitable for deployment
Knowledge of multithreading/multiprocessing and real-time video processing
Previous work with ANPR, object detection, or computer vision
Deliverables:
Fully working, integrated ANPR solution
Code and setup instructions
Test run with 5 sample videos
Only apply if you have prior experience in YOLO-based object detection and real-time video processing.