AI / ML pipeline
Custom Vision Model
A repeatable path from labeled images to a specialized visual-detection model and inference API.
01Labels→02Dataset→03Training→04Inference
Context
A custom detection task requires more than model training: consistent data structure, reproducible preprocessing and a clear path from experiment to usable inference.
How it works
Validated and structured the supplied annotations, built preprocessing and augmentation, configured TensorFlow training and model export, and separated inference for integration with photo processing.
What it enables
The result is a repeatable ML loop where dataset preparation, training, validation and inference share the same conventions, so a new model iteration does not require rebuilding the process by hand.