food-recognition-challenge-mmdetection-baseline
Problem Statement
The goal of this challenge is to train models which can look at images of food items and detect the individual food items present in them. We provide a novel dataset of food images collected using the MyFoodRepo project where numerous volunteer Swiss users provide images of their daily food intake. The images have been hand labelled by a group of experts to map the individual food items to an ontology of Swiss Food items.
This is an evolving dataset, where we will release more data as the dataset grows in size.
Baseline
MMdetection is an open source object detection toolbox based on PyTorch, with a large Model Zoo with many customised models that can be plugged and tested in with just a single config file modification. PYou can read more about it at: mmdetection github
Code
This repo contains the source code used to train my best submission for Round 4. The submission was a two-model ensemble of DetectoRS and HTC x101.
Best of Luck
Miscelaneous Resources
Credits
- Parts of the documentation for this baseline was taken from : https://github.com/AIcrowd/food-recognition-challenge-starter-kit
- and the baseline is built using MMDetection: https://github.com/open-mmlab/mmdetection/