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I will do object detection and recognition project
Machine Learning Engineer
I am a dedicated Machine Learning Engineer specializing in Computer Vision (CV) and Deep Learning (DL) solutions. On Fiverr, I bridge the gap between raw data and powerful, scalable AI applications, e...
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I specialize in leveraging the power of YOLO (You Only Look Once) for your complex computer vision projects.
I offer expert, cutting-edge YOLO solutions for precise object detection, segmentation, and tracking. From custom model training tailored to your unique data to seamless deployment and integration, I provide highly accurate and exceptionally efficient solutions according to your specific needs.
Unlock advanced computer vision capabilities and rapid, real-time performance with my professional YOLO projects.
API:
Microsoft Computer Vision AI
Lenguaje de programación:
Python
•
Colab
Herramientas:
Jupyter Notebook
•
opencv
•
TensorFlow
•
CVAT
•
Colab
•
PyTorch
Marcos:
Scikit-learn
•
keras
•
PyTorch
•
Panda
Mi porfolio
FAQ
What data do I need to provide?
You need to provide the dataset (images or video frames) containing the objects you want to detect. Crucially, this data must be annotated with bounding boxes (and masks, if segmentation is required) in a standard format (e.g., YOLO format, COCO format, or Pascal VOC format).
What if my data is not annotated?
Data annotation is a time-consuming but necessary step. If your data is not yet labeled, I can provide this service as a Gig Extra. Please message me before ordering to discuss the size of your dataset and get a custom quote for annotation, as this affects the project timeline.
Which YOLO version do you use?
I primarily use the most modern and efficient versions, such as YOLO11 and YOLO12, to ensure high accuracy and real-time performance. However, I can also work with older versions (like YOLOv10 or YOLOv8) if your deployment environment requires it.
What are the key deliverables of the project?
The trained model weights (e.g., .pt file). The Python source code necessary for running inference (predictions) on new images/videos. A detailed performance report including metrics like mAP (mean Average Precision), Precision, and Recall. Clear documentation on how to run and use the model.
