L Photo Classifier
Budget: €250 – €750 EUR
I need an experienced computer-vision developer to build a photo-based image classification pipeline using OpenCV. The system will ingest still photographs taken at live events and automatically tag each shot into predefined categories (for instance crowd, stage, speaker, logo, VIP, etc.).
The core requirement is accurate, fast classification of photos only; we are not dealing with video or live camera feeds right now, though I may extend in that direction later. You are free to choose the underlying framework—TensorFlow, PyTorch, scikit-learn—so long as OpenCV is used for image handling and preprocessing.
Here is what I expect:
• A well-documented training script that reads my labeled dataset, performs augmentation where helpful, and outputs a reproducible model.
• An inference module (CLI or small API) that accepts a folder of JPEG/PNG files and returns class labels with confidence scores.
• Clear instructions for environment setup plus any dependency list (Python version, library versions).
• Metrics demonstrating accuracy on a held-out test set so I can gauge performance before deployment.
If you have previous work in event photography or similar domains, that will help us move faster, but solid OpenCV and machine-vision know-how is the key. Let me know the tools you propose and the timeline you need; I’m ready to start as soon as you are.
The core requirement is accurate, fast classification of photos only; we are not dealing with video or live camera feeds right now, though I may extend in that direction later. You are free to choose the underlying framework—TensorFlow, PyTorch, scikit-learn—so long as OpenCV is used for image handling and preprocessing.
Here is what I expect:
• A well-documented training script that reads my labeled dataset, performs augmentation where helpful, and outputs a reproducible model.
• An inference module (CLI or small API) that accepts a folder of JPEG/PNG files and returns class labels with confidence scores.
• Clear instructions for environment setup plus any dependency list (Python version, library versions).
• Metrics demonstrating accuracy on a held-out test set so I can gauge performance before deployment.
If you have previous work in event photography or similar domains, that will help us move faster, but solid OpenCV and machine-vision know-how is the key. Let me know the tools you propose and the timeline you need; I’m ready to start as soon as you are.