I will build a CV pipeline for object detection or image classification using pytorch

Need a computer vision model that actually works in your environment not just a notebook demo?

I build end-to-end computer vision pipelines using PyTorch, OpenCV, and state-of-the-art architectures like YOLO, ResNet, VGG16, and Vision Transformers. Whether you need to detect objects in real-time, classify images, segment regions, or extract text I deliver a clean, deployable solution.

What I can build:

• Object detection (YOLOv8/v11, Faster R-CNN)
• Image classification (ResNet50, VGG16, EfficientNet)
• Image segmentation (semantic & instance)
• OCR and document text extraction
• Medical imaging analysis
• Custom dataset training + fine-tuning
• FastAPI inference endpoint for your model

Popular use cases: Defect detection in manufacturing, medical image diagnosis, face/object recognition, retail shelf monitoring, document digitization, security camera analytics.

Why me? I've built and deployed a Brain Tumor Detection system using VGG16 and ResNet50 with a FastAPI backend and Docker container a real, end-to-end medical imaging project. Message me with your dataset and use case before ordering.