I will build a custom yolo object detection computer vision model


Over deze dienst
Need a custom object detection model for your images ?
I will build and train a YOLO-based computer vision model tailored to your dataset and project requirements.
I can help you with:
- Object detection using YOLO
- Custom model training and fine-tuning
- Dataset preparation and validation
- Image and video inference
- Model performance evaluation
- Precision, recall, mAP and other relevant metrics
- Python inference code
- OpenCV integration
- Trained model files
- Clear documentation depending on the selected package
I work with Python, YOLO, Ultralytics, PyTorch and OpenCV to develop clean and structured computer vision solutions.
My experience includes developing an industrial AI inspection system combining object detection, anomaly detection, image classification and explainable AI.
IMPORTANT:
The client should provide a labeled dataset for model training. If your images are not annotated yet, please contact me before ordering so we can discuss annotation requirements separately.
Model performance depends on dataset size, image quality, annotation quality and task complexity, so I do not promise unrealistic accuracy levels.
Please contact me before ordering if your project involves a la
Maak kennis met Ines Abdellaoui
Content Writer, Software Engineer, French English Arabic Translator
- Afkomstig uitItalië
- Lid sindsaug 2026
- Gem. reactietijdBinnen 2 dagen
Talen
Arabisch, Engels, Frans
Veelgestelde vragen
Do I need to provide an annotated dataset?
Yes. For model training, you should provide a labeled dataset. If your images are not annotated yet, please contact me before ordering so we can discuss annotation as an additional service.
Which YOLO versions can you work with?
I mainly work with modern Ultralytics YOLO models such as YOLOv8 and can select the most suitable model according to your dataset, hardware, and project requirements.
Can you guarantee a specific accuracy?
No realistic computer vision project can guarantee a fixed accuracy before evaluating the dataset. Performance depends on dataset size, image quality, annotation quality, class balance, and task complexity.
What will I receive after the project is completed?
Depending on your package, you may receive the trained model, Python inference code, evaluation results, performance metrics, sample predictions, and documentation.
What information should I send before placing an order?
Please send a short description of your project, the number of object classes, dataset size, sample images, annotation format, expected output, and any deployment or performance requirements.
