I will train a custom yolo model for object detection, tracking and counting

K
kuminai
K
kuminai
Luong D

About this gig

Need a model that reliably detects your objects on real images, not only in a notebook? I train custom YOLO models (Ultralytics YOLOv8/YOLO11: detection, segmentation or pose) on your dataset.


Need tracking or counting too? I add object tracking (ByteTrack/BoT-SORT), line-crossing counts and zone alerts on video.


What I have built:

  • Real-time fall detection from RTSP cameras (YOLO Pose, tracking, ONNX, FastAPI, Docker). 83% F1 on a 100-video benchmark, Top 10 at AI20K (Vingroup x VinUni).
  • PPE safety detection: cleaned a 7,000-image multi-source dataset and compared 10+ YOLO methods. mAP50 improved from 0.674 to 0.753 on an 808-image test set.

What you get:

  • Trained weights (.pt, plus ONNX in Premium)
  • mAP50, mAP50-95, precision, recall, per-class results and confusion matrix
  • A Python inference script for images, video or webcam
  • A short report on what works, what fails and how to improve it
  • A clean README so you can retrain later

Process: send your dataset (YOLO, COCO, VOC or Roboflow), I check it for label problems and leakage, train, evaluate on a held-out test set, and deliver.


Data not labeled yet? Message me first.

Get to know Luong D

Luong D

AI Engineer for Computer Vision and LLM Apps

  • FromVietnam
  • Member sinceJul 2021
  • Avg. response time1 hour
  • Languages

    English, Vietnamese
I build AI systems that work in the real world. My recent projects include SYL GuardianCam, a real-time fall detection system (YOLO Pose, FastAPI, Docker) with 83% F1 that placed Top 10 at AI20K, and a Medical GraphRAG system that reduces LLM hallucinations. I can train custom YOLO models, clean datasets, build RAG chatbots and AI agents, and deploy them with FastAPI and Docker. Every delivery includes clean code, a README and clear metrics.