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Fiverr Pro
English
$
USD
I will do computer vision, object detection and yolo projects using opencv
About this Gig
I build custom computer vision solutions using YOLO, OpenCV, and Python trained on your specific dataset, optimized for your specific problem, and delivered as clean, ready-to-use code.
What I can build for you:
- Object detection & real-time tracking using YOLOv8
- Image classification with custom deep learning models
- Face detection & recognition systems
- Custom dataset training & annotation support
- Model evaluation with precision, recall & mAP metrics
How I work:
- You share your dataset and requirements
- I analyze, preprocess and select the best architecture
- I train, test and optimize the model until results are solid
- You receive full source code, results and documentation
Tech Stack:
- Python, OpenCV, YOLOv8, TensorFlow, PyTorch
- Google Colab, Jupyter Notebook, GitHub
- LabelImg for annotation support
Who this is for:
- Startups building vision-based products
- Researchers needing a trained model fast
- Businesses automating visual inspection or monitoring
Message me before ordering tell me what you're trying to detect, and I'll tell you exactly what's possible.
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FAQ
What do I need to provide before you start?
Please share your dataset (images or video), the objects you want to detect or classify, and a brief description of your use case. The more context you give, the better the model will perform.
Can you train YOLO on my custom dataset?
Yes, absolutely. I can train YOLOv8 on any custom dataset. If your images are not annotated yet, I can guide you through the annotation process or handle it as part of the project
My dataset is small. Can you still build a working model?
Yes. For small datasets I use transfer learning and data augmentation techniques to maximize model performance. Just share what you have and I will work with it.
What will I receive after the project is done?
You will receive the complete source code, trained model weights, a test script to run the model on new images, and documentation explaining the results including precision, recall and mAP scores
