ISIA Food-200 consists of 197,323 food items.Each item includes the food name,food images,main ingredients.There are totally 200 kinds of food dishes and 398 ingredients.

[image.rar] [metadata.rar] [readme.txt]

http://123.57.42.89/FoodComputing-Dataset/FoodComputing-ISIA200.html

This is a PyTorch implementation of the ACMMM2019 paper "Ingredient-Guided Cascaded Multi-Attention Network for Food Recognition" (Weiqing Min, Linhu Liu, Zhengdong Luo, Shuqiang Jiang).

• python 2.7
• pytorch 0.4+

1.Download the ETH Food-101 or ISIA Food-200 datasets, you may obtain images which contain ingredient and category list. You can also try other food datasets. 2.The category list is : name_of_image.jpg label_num\n

e.g for ETH Food-101:

apple_pie/1057749.jpg 0
apple_pie/1057810.jpg 0
baby_back_ribs/1148389.jpg 1
baby_back_ribs/1153312.jpg 1

3.The ingredient list is : name_of_image.jpg ingredient_label1 ingredient_label2 ...\n

e.g for ETH Food-101:

apple_pie/1005649.jpg 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
beef_carpaccio/608583.jpg 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

If you want to train the model, just run 'python train_model.py'. You may need to change the configurations in train_model.py. The parameter 'DIR_TRAIN_IMAGES_INGREDIENT' is the ingredient list of train and 'DIR_TEST_IMAGES_INGREDIENT' is the ingredient list of test. 'DIR_TRAIN_IMAGES' is the category list of train and 'DIR_TEST_IMAGES' is the category list of test. 'vgg_multilabel_finetune' is the vgg pretrained model on food dataset,such as WikiFood-200. 'IMAGE_PATH' is the path of the image folder. 'NUM_INGREDIENT' is the ingredient number of food dataset. What's more, in 'IGCMAN_module.py', you may change the parameter 'food101_multilable_class'(the ingredient number of food dataset) and 'food101_category'(the category number of food dataset).

If you are interested in our work and want to cite it, please acknowledge the following paper:

@InProceedings{Min-IG-CMAN-MM2019,
 author = {Min, Weiqing and Liu, Linhu and Luo, Zhengdong and Jiang, Shuqiang},
 title = {Ingredient-Guided Cascaded Multi-Attention Network for Food Recognition},
 booktitle = {Proceedings of the 27th ACM International Conference on Multimedia},
 year = {2019},
 pages = {1331--1339},
 numpages = {9},
}