Omkar2118/datasets huggingface dataset:
MC1296
Full name: Meter_Challenge

a dataset of reading pointer meter

Introducing paper: Read Pointer Meters in complex environments based on a Human-like Alignment and Recognition Algorithm
Evosuite SF110 Benchmark

The SF100 corpus of classes is a statistically representative sample of 100 Java projects from SourceForge, which is a popular open source repository (more than 300,000 projects with more than two million registered users). Because SourceForge is home to many old and stale projects, we have extended SF100 with the 10 most popular projects, resulting in a revised corpus of classes, SF110.
ContactArt

**ContactArt** is a dataset for learning hand-object interaction priors for hand and articulated object pose estimation. The dataset is created using visual teleoperation, where the human operator can directly play within a physical simulator to manipulate the articulated objects.  All the object models are from Partnet dataset for the convenience of scaling up. ContactArt can provide accurate annotation, rich hand-object interaction, and contact information.

Source: [ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation](https://arxiv.org/pdf/2305.01618.pdf)

Image Source: [ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation](https://arxiv.org/pdf/2305.01618.pdf)

Introducing paper: ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation
Pick-a-Pic

**Pick-a-Pic** dataset was created by logging user interactions with the Pick-a-Pic web application for text-to image generation. Overall, the Pick-a-Pic dataset contains over 500,000 examples and 35,000 distinct prompts. Each example contains a prompt, two generated images, and a label for which image is preferred, or if there is a tie when no image is significantly preferred over the other.

Source: [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/pdf/2305.01569v1.pdf)

Image Source: [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/pdf/2305.01569v1.pdf)
Stain Transfer in Histopathology

The dataset contains 256x256 tiles extracted from Whole Slide Images (WSI) of mouse liver tissue stained with H&E and Masson's Trichrome. WSIs were acquired with a Zeiss AxioScan scanner with a 20× objective at a resolution of 0.221 µm/pix and subsequently subsampled with a factor of 1:2, which resulted in a 0.442 µm/pixel resolution.
Stain Transfer

The dataset contains 256x256 tiles extracted from Whole Slide Images (WSI) of mouse liver tissue stained with H&E and Masson's Trichrome. WSIs were acquired with a Zeiss AxioScan scanner with a 20× objective at a resolution of 0.221 µm/pix and subsequently subsampled with a factor of 1:2, which resulted in a 0.442 µm/pixel resolution. 

The dataset can be used for training and evaluation of image to image translation methods for stain transfer in histopathology.

Introducing paper: A comparative evaluation of image-to-image translation methods for stain transfer in histopathology
WebUI

The WebUI dataset contains 400K web UIs captured over a period of 3 months and cost about $500 to crawl. We grouped web pages together by their domain name, then generated training (70%), validation (10%), and testing (20%) splits. This ensured that similar pages from the same website must appear in the same split. We created four versions of the training dataset. Three of these splits were generated by randomly sampling a subset of the training split: Web-7k, Web-70k, Web-350k. We chose 70k as a baseline size, since it is approximately the size of existing UI datasets. We also generated an additional split (Web-7k-Resampled) to provide a small, higher quality split for experimentation. Web-7k-Resampled was generated using a class-balancing sampling technique, and we removed screens with possible visual defects (e.g., very small, occluded, or invisible elements). The validation and test split was always kept the same.

Introducing paper: WebUI: A Dataset for Enhancing Visual UI Understanding with Web Semantics