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| import type { TaskDataCustom } from "../Types"; | |
| const taskData: TaskDataCustom = { | |
| datasets: [ | |
| { | |
| description: "A widely used dataset containing questions (with answers) about images.", | |
| id: "Graphcore/vqa", | |
| }, | |
| { | |
| description: "A dataset to benchmark visual reasoning based on text in images.", | |
| id: "textvqa", | |
| }, | |
| ], | |
| demo: { | |
| inputs: [ | |
| { | |
| filename: "elephant.jpeg", | |
| type: "img", | |
| }, | |
| { | |
| label: "Question", | |
| content: "What is in this image?", | |
| type: "text", | |
| }, | |
| ], | |
| outputs: [ | |
| { | |
| type: "chart", | |
| data: [ | |
| { | |
| label: "elephant", | |
| score: 0.97, | |
| }, | |
| { | |
| label: "elephants", | |
| score: 0.06, | |
| }, | |
| { | |
| label: "animal", | |
| score: 0.003, | |
| }, | |
| ], | |
| }, | |
| ], | |
| }, | |
| isPlaceholder: false, | |
| metrics: [ | |
| { | |
| description: "", | |
| id: "accuracy", | |
| }, | |
| { | |
| description: | |
| "Measures how much a predicted answer differs from the ground truth based on the difference in their semantic meaning.", | |
| id: "wu-palmer similarity", | |
| }, | |
| ], | |
| models: [ | |
| { | |
| description: "A visual question answering model trained to convert charts and plots to text.", | |
| id: "google/deplot", | |
| }, | |
| { | |
| description: | |
| "A visual question answering model trained for mathematical reasoning and chart derendering from images.", | |
| id: "google/matcha-base ", | |
| }, | |
| { | |
| description: "A strong visual question answering that answers questions from book covers.", | |
| id: "google/pix2struct-ocrvqa-large", | |
| }, | |
| ], | |
| spaces: [ | |
| { | |
| description: "An application that can answer questions based on images.", | |
| id: "nielsr/vilt-vqa", | |
| }, | |
| { | |
| description: "An application that can caption images and answer questions about a given image. ", | |
| id: "Salesforce/BLIP", | |
| }, | |
| { | |
| description: "An application that can caption images and answer questions about a given image. ", | |
| id: "vumichien/Img2Prompt", | |
| }, | |
| ], | |
| summary: | |
| "Visual Question Answering is the task of answering open-ended questions based on an image. They output natural language responses to natural language questions.", | |
| widgetModels: ["dandelin/vilt-b32-finetuned-vqa"], | |
| youtubeId: "", | |
| }; | |
| export default taskData; | |