Training a Computer Vision Model for Commercial Bakeries with Primarily Synthetic Images

2024-09-30 · Thomas H. Schmitt, Maximilian Bundscherer, Tobias Bocklet

In the food industry, reprocessing returned product is a vital step to increase resource efficiency. [SBB23] presented an AI application that automates the tracking of returned bread buns. We extend their work by creating an expanded dataset comprising 2432 images and a wider range of baked goods. To increase model robustness, we use generative models pix2pix and CycleGAN to create synthetic images. We train state-of-the-art object detection model YOLOv9 and YOLOv8 on our detection task. Our overall best-performing model achieved an average precision AP@0.5 of 90.3% on our test set.

📄 PDF Abstract BibTeX arXiv:2409.20122

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object-detection Object Detection

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