CoolFace
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desktop

UI-MOPD /Uni-GUI-Desktop-1 Uni-GUI-Desktop-1 A large-scale desktop GUI agent trajectory dataset, used as part of the training data for UI-MOPD (Multi-platform On-Policy Distillation for Continual GUI Agent Learning). Dataset Statistics Metric Value Trajectories 2,685 Total Steps ~36K Platform Desktop (1920x1080) Applications 10 categories Coordinate System Normalized to [0, 999] Applications App Description chrome Web browsing tasks gimp… See the full description on the dataset page: https://huggingface.co/datasets/UI-MOPD/Uni-GUI-Desktop-1.imagerobotics10K<n<100K1 likes4.4k downloads3mo agoHugging FaceRoboCOIN /Cobot_Magic_desktop_organizationgated Cobot_Magic_desktop_organization 📋 Overview This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot. Robot Type: agilex_cobot_decoupled_magic | Codebase Version: v2.1 End-Effector Type: two_finger_gripper 🏠 Scene Types This dataset covers the following scene types: home office 🤖 Atomic Actions This dataset includes the following atomic actions: grasp pick place 📊 Dataset Statistics Metric… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/Cobot_Magic_desktop_organization.tabularrobotics1M<n<10M0 likes2k downloads9mo agoHugging FaceRoboCOIN /RMC-AIDA-L_desktop_organizationgated RMC-AIDA-L_desktop_organization 📋 Overview This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot. Robot Type: realman_rmc_aidal | Codebase Version: v2.1 End-Effector Type: two_finger_gripper 🏠 Scene Types This dataset covers the following scene types: home 🤖 Atomic Actions This dataset includes the following atomic actions: grasp pick place 📊 Dataset Statistics Metric… See the full description on the dataset page: https://huggingface.co/datasets/RoboCOIN/RMC-AIDA-L_desktop_organization.tabularrobotics1M<n<10M0 likes1.8k downloads9mo agoHugging Faceshowlab /ShowUI-desktopGithub | arXiv | HF Paper | Spaces | Datasets | Quick Start ShowUI-desktop-8K is a UI-grounding dataset focused on PC-based grounding, with screenshots and annotations originally sourced from OmniAct. We utilize GPT-4o to augment the original annotations, enriching them with diverse attributes such as appearance, spatial relationships, and intended functionality. You can use our rewrite strategy code to augment your own data. If you find our work helpful, please consider citing our paper.… See the full description on the dataset page: https://huggingface.co/datasets/showlab/ShowUI-desktop.image1K<n<10K37 likes1.7k downloads2y agoHugging FaceVoxel51 /ShowUI_desktop Desktop Dataset from ShowUI This is a FiftyOne dataset with 7496 samples. Installation If you haven't already, install FiftyOne: pip install -U fiftyone Usage import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub # Load the dataset # Note: other available arguments include 'max_samples', etc dataset = load_from_hub("Voxel51/ShowUI_desktop") # Launch the App session = fo.launch_app(dataset) Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/ShowUI_desktop.imageimage-classification1K<n<10K4 likes1.5k downloads1y agoHugging Facedixantp /desktop-accessibility-screenshot-json-dumpsimagen<1K1 likes1k downloads1y agoHugging Face