Kinetics-600 is a large-scale 600-class video action dataset, consists of a total of 495,547 videos. We sub-sampled a food subclass in the dataset to train the model, where we follow the list of such a subclass from Weissenborn et al. (2020), namely: baking, barbequing, breading, cooking, cutting, pancake, vegetables, meat, cake, sandwich, pizza, sushi, tea, peeling, fruit, eggs, salad. We use train split for the model training and use the validation set for the evaluation. Note that we only use these classes, different from Weissenborn et al. (2020) to train the model with the whole dataset.
# download and extract train file
bash download_extract.sh train
# download and extract validation file
bash download_extract.sh val
python preprocess.py
After running all codes, one can obtain png preprocessed Kinectics-food dataset at ./train and ./val folders.
We used the downloading and extraction codes from the following repository: kinetics-dataset.