← Back to Projects Real-Time YOLO Object Detection Pipeline
Develop real-time object detection pipelines with YOLOv8 and deployment-ready inference optimization.
Categories
CVML
Tech Used
YOLOv8PyTorchOpenCVfine-tuningUltralyticsTensorRTONNXCUDANumPyFastAPIFlaskDocker
Problem
Video applications need object detection that remains accurate while meeting latency and deployment constraints.
Approach
- Trained YOLOv8 detection models with augmentation and iterative evaluation
- Optimized inference using ONNX, TensorRT, and CUDA-oriented deployment paths
- Served predictions through API-based workflows and containerized packaging
Results
- Production-oriented object detection setup for real-time use cases
- Deployment-friendly model artifacts and serving pattern
Demo Videos