I will annotate images and train a custom yolo object detection model


About this gig
I annotate your images and train a custom YOLO model that detects YOUR objects, not generic pre-trained demos.
I am an NVIDIA Inception member with a Python AI/ML team that has deployed object detection systems in manufacturing, security, restaurant, and sports analytics across 6 countries.
WHAT I DELIVER:
STEP 1 ANNOTATION & LABELING
Bounding box, polygon, or keypoint annotation
Tools: CVAT, LabelImg, Roboflow, Label Studio, YOLO format export (yaml + txt labels)
STEP 2 DATASET PREPARATION
Augmentation, train/val/test split, quality audit
STEP 3 YOLO MODEL TRAINING
YOLOv8 custom training on your dataset, GPU-accelerated on NVIDIA CUDA, mAP, precision, recall, and confusion matrix report
STEP 4 DEPLOYMENT (Premium only)
TensorRT optimization 3-5x faster inference, FastAPI inference endpoint, Python script ready to run
WHAT I HAVE BUILT:
Football player tracking 22 players simultaneously
Smoking and PPE detection on NVIDIA Jetson edge hardware
Restaurant kitchen hygiene compliance monitoring
You receive: labeled dataset, trained model weights, inference script, and training report.
Message me before ordering with your images and use case.
Get to know Poriya
AI App Development Expert, Computer Vision, OpenCV, Object Detection
- FromIndia
- Member sinceJun 2016
- Avg. response time1 hour
- Last delivery2 years
Languages
Gujarati, English, Hindi
My Portfolio
FAQ
What image formats do you accept?
JPG, PNG, BMP, TIFF and video frames from MP4. I can extract frames from your video if needed.
What if I have no labeled data yet?
That is fine. Annotation is step 1. Send raw images and describe what object you want detected.
How many images do I need for good accuracy?
Minimum 200 per class for basic detection. 500+ per class gives 85–92% mAP. 1,000+ gives 90–96%.
Can you work with medical or satellite images?
Yes. Send a sample image first and I will confirm feasibility before you order.
Can you deploy on my server instead of Jetson?
Yes. I deploy via FastAPI on AWS, Google Cloud, or any Linux server with GPU support.

