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I will provide an ai solution for computer vision projects using yolo and tensorflow
About this Gig
Welcome! I'm Hassan, a computer vision specialist creating advanced AI models for image recognition, object detection, and video analysis. Whether you're a business, startup, developer, or individual, I solve your visual intelligence needs with precision and professionalism.
You dont have to reinvent the wheel. I build state-of-the-art computer vision systems tailored to your needs (using TensorFlow/PyTorch, YOLO, OpenCV, etc.). These plug and play AI solutions let your team automate image/video workflows, cut manual effort, and unlock business value.
What You'll Get:
- Image Classification: CNNs, Transfer Learning (ResNet, EfficientNet) for binary & multi-class tasks.
- Object Detection: YOLOv8/v7/v5, Faster R-CNN, real-time video & live camera support.
- Model Deployment: Streamlit/Web app integration, Fast API.
- Performance Tracking: Accuracy, F1, precision/recall metrics, detailed reports.
Why Choose Me:
- Production-ready code with clean documentation
- Fast turnaround, transparent communication
- Full confidentiality & seamless integration into your stack
I deliver reliable, production-ready vision models with clean code, clear communication, and full confidence.
APIs:
Other
Expertise:
Image processing
•
Classification
•
Object detection
Programming language:
Python
•
Colab
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
Excel
•
Colab
•
PyTorch
Frameworks:
Scikit-learn
•
SimpleCV
•
Keras
•
PyTorch
•
Panda
My Portfolio
FAQ
Can you work with a custom or niche dataset?
Yes, I specialize in training models on custom datasets. Just make sure the data is properly labeled and organized. If you’re unsure, feel free to message me before ordering.
What frameworks do you use?
I mainly use Python-based frameworks including TensorFlow, Keras, and OpenCV. The models are built from scratch for your use case.
Do you use transfer learning for faster or better results?
Yes, whenever appropriate. I use pre-trained models like ResNet, MobileNet, EfficientNet, or YOLO as a base and fine-tune them on your dataset. This approach speeds up training and boosts accuracy, especially when the dataset is small.
What if my dataset is too small to train from scratch?
No problem. I’ll apply transfer learning to adapt a pre-trained model to your specific dataset. This is ideal for small or specialized image sets and still achieves high accuracy.
