Omkar2118/datasets huggingface dataset:
SchizzoSQUAD

The “Mental Health” forum was used, a forum dedicated to people suffering from schizophrenia and different mental disorders. Relevant posts of active users, who regularly participate, were extrapolated providing a new method of obtaining low-bias content and without privacy issues. This corpus i then processed to offer a SQUAD (Standford Question Answering Dataset) version in order to train a ML QA model.

The structure is a Json with different keys with the following structure:

{
  "data": [
    {
      "paragraphs": [
        {
          "qas": [
            {
              "question": "What is the patient afraid of?",
              "id": 304425,
              "answers": [
                {
                  "answer_id": 305544,
                  "document_id": 501182,
                  "question_id": 304425,
                  "text": "I’m afraid of people except for my family and a few close friends",
                  "answer_start": 29769,
                  "answer_category": null
                }
              ],
              "is_impossible": false
            }
          ],
          "context": "\t\" I don’t understand why people send aid to other countries and go on missions when our own country people are suffering and have nothing, in the us at least.\"\n\t\"7-21-19 Said \\\"What is she afraid of? Afraid of family!?,
          "document_id": 501182
        }
      ]
    }

Introducing paper: Question-Answering Model for Schizophrenia Symptoms and Their Impact on Daily Life using Mental Health Forums Data
EPIC-STATES

EPIC-STATES builds upon the raw data in the EPIC-KITCHENS dataset and consists of 10 object state categories: open, close, in-hand, out-of-hand, whole, cut, raw, cooked, peeled, unpeeled. EPIC-STATES consists of 14,346 object bounding boxes from the EPIC-KITCHENS dataset (2018 version), each labeled with 10 binary labels corresponding to the 10 state classes.

Introducing paper: Human Hands as Probes for Interactive Object Understanding
EPIC-ROI

EPIC-ROI builds on top of the EPIC-KITCHENS dataset, and consists of 103 diverse images with pixel-level annotations for regions where human hands frequently touch in everyday interaction. Specifically, image regions that afford any of the most frequent actions: take, open, close, press, dry, turn, peel are considered as positives. We manually watched video for multiple participants to define a) object categories, and b) specific regions within each category where participants interacted while conducting any of the 7 selected actions. These 103 images were sampled from across 9 different kitchens (7 to 15 images with minimal overlap, from each kitchen). EPIC-ROI is only used for evaluation, and contains 32 val images and 71 test images. Images from the same kitchen are in the same split. The Regions-of-Interaction task is to score each pixel in the image with the probability of a hand interacting with it. Performance is measured using average precision.

Introducing paper: Human Hands as Probes for Interactive Object Understanding