ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network
ISIA Food-500 consists of
399,726 food items.Each item includes the food name,food images.
There are totally
500 kinds of food dishes.
The dataset and code can be downloaded from the following link:
This is a PyTorch implementation of the ACMMM2020 paper "ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network" (Weiqing Min, Linhu Liu, Zhiling Wang,Zhengdong Luo, Xiaoming Wei, Xiaolin Wei and Shuqiang Jiang).
- python 2.7
- pytorch 0.4+
1.Download ten compressed packages(from ISIA_Food500.z01 to ISIA_Food500.z10) to obtain the complete dataset. You can also download metadata_ISIAFood_500.zip to obtain the statistical data of the dataset.
2.The category list is:
e.g: Duck_soup_noodles/Duck_soup_noodles_0045.jpg 197
Train the model
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' is the category list of train and 'DIR_TEST_IMAGES' is the category list of test. 'WEIGHT_PATH' is the pretrained model on food dataset. 'IMAGE_PATH' is the path of the image folder. During training, the checkpoint file will be saved.
If you are interested in our work and want to cite it, please acknowledge the following paper: