Link to dataset - https://dphi-live.s3.eu-west-1.amazonaws.com/dataset/Human+Action+Recognition-20220526T101201Z-001.zip

The dataset features 15 different classes of Human Activities. The dataset contains about 12k+ labelled images including the validation images. Each image has only one human activity category and are saved in separate folders of the labelled classes

From the above link you will be able to download a zip file named ‘Human_Activities.zip’. After you extract this zip file, you will get four files:

Train - contains all the images that are to be used for training your model. In this folder you will find 15 folders namely - 'calling', ’clapping’, ’cycling’, ’dancing’, ‘drinking’, ‘eating’, ‘fighting’, ‘hugging’, ‘laughing’, ‘listening_to_music’, ‘running’, ‘sitting’, ‘sleeping’, texting’, ‘using_laptop’ which contain the images of the respective human activities.
Test - contains 5400 images of Human Activities. For these images you are required to make predictions as the respective class names -'calling', ’clapping’, ’cycling’, ’dancing’, ‘drinking’, ‘eating’, ‘fighting’, ‘hugging’, ‘laughing’, ‘listening_to_music’, ‘running’, ‘sitting’, ‘sleeping’, texting’, ‘using_laptop’.
Testing_set.csv - this is the order of the predictions for each image that is to be submitted on the platform. Make sure the predictions you download are with their image’s filename in the same order as given in this file.
sample_submission: This is a csv file that contains the sample submission for the data sprint.

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Etc.

Note that the header name should be ‘label’ else it will throw an evaluation error.

Notebook submission: You should submit a CSV file with a header row and the sample submission can be found below:

filename	label
Image_1.jpg	cycling
Image_2.jpg	cycling
Image_3.jpg	cycling
Image_4.jpg	cycling
Image_5.jpg	cycling

Steps to follow to submit your notebook:

Data Sprint 76 - Human Activity Recognition

Challenge Starts

Registration Ends

Challenge Ends