I will build a yolo object detection system using python
AI Engineer , Python , Machine Learning , Automation
About this Gig
I will build a custom YOLO object detection system using Python for your computer vision project.
I can work with images, videos, CCTV footage, and real-time camera streams. My services include dataset preparation, preprocessing, YOLO model training, object detection, testing, evaluation, and optimization.
I can help detect and identify custom objects based on your requirements. I work with Python, YOLO, Ultralytics, OpenCV, and other suitable computer vision tools.
Depending on your selected package, you will receive trained model files, clean source code, testing results, documentation, and API integration when included.
Before placing an order, please send your dataset, target objects, expected output, and project requirements. I will review your requirements and confirm the appropriate package before starting.
Programming language:
Python
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SQL
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Colab
Tools:
Jupyter Notebook
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OpenCV
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TensorFlow
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Excel
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PyTorch
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Other
Frameworks:
Scikit-learn
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SimpleCV
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PyTorch
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Panda
My Portfolio
Other Data Science & ML Services I Offer
FAQ
What can you detect with YOLO?
I can build YOLO models to detect custom objects based on your dataset and project requirements, including objects in images, videos, CCTV footage, and camera streams.
Can you train YOLO on my custom dataset?
Yes. You can provide your dataset and target object information. I can prepare the data and train a suitable YOLO model according to the selected package.
Can you work with CCTV or video footage?
Yes. I can develop object detection solutions for images, recorded videos, CCTV footage, and real-time camera streams.
Do you provide the trained model and source code?
Yes. Trained model files and source code are provided according to the selected package.
Can you integrate YOLO with an API?
Yes. API integration is available in the Premium package when required.
What do you need before starting?
Please provide your dataset, target objects, expected output, project requirements, and any reference examples or existing code.

