labeling
Datasets
All datasets matching “labeling”INRIA-Aerial-Image-Labeling
Inria Aerial Image Labeling Dataset
Description
The Inria Aerial Image Labeling Dataset is a building semantic segmentation dataset proposed in "Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark," Maggiori et al.. It consists of 360 high-resolution (0.3m) RGB images, each with a size of 5000x5000 pixels. These images are extracted from various international GIS services, such as the USGS National Map.
Project page:… See the full description on the dataset page: https://huggingface.co/datasets/blanchon/INRIA-Aerial-Image-Labeling.INRIA-Aerial-Image-Labeling
Inria Aerial Image Labeling Dataset
Description
The Inria Aerial Image Labeling Dataset is a building semantic segmentation dataset proposed in "Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark," Maggiori et al.. It consists of 360 high-resolution (0.3m) RGB images, each with a size of 5000x5000 pixels. These images are extracted from various international GIS services, such as the USGS National Map.
Project page:… See the full description on the dataset page: https://huggingface.co/datasets/usmanhf/INRIA-Aerial-Image-Labeling.pick_and_place_failure_labelingThis dataset was created using LeRobot.
Pick and Place Failure Labeling
This dataset is a failure-only, frame-labeled subset derived from KGB0/pick_and_place_annotation_image.
It keeps complete episodes that contain at least one failure label and adds frame-level failure annotation columns for failure detection and recovery experiments.
Generated at: 2026-06-16T02:22:18+00:00Target repo: KGB0/pick_and_place_failure_labeling
Dataset Structure
meta/info.json:
{… See the full description on the dataset page: https://huggingface.co/datasets/KGB0/pick_and_place_failure_labeling.gta5-cityscapes-labelingmetagaming-labeling-v2
camgeodesic/metagaming-labeling-v2
Auto-generated by dataset-builder.
Each config below is a separate dataset produced from a versioned YAML build
config. Load with:
from datasets import load_dataset
ds = load_dataset("camgeodesic/metagaming-labeling-v2", "<config_name>", revision="<commit-sha>")
Pin revision= to the specific commit SHA you want; without it, you get the
current HEAD of the dataset repo, which may change when the builder re-pushes.
What this repo is… See the full description on the dataset page: https://huggingface.co/datasets/camgeodesic/metagaming-labeling-v2.cs2-v3-prompt-labeling-project
CS2 V3 Prompt Labeling Project
这是 CS2 第一人称视频打标 Prompt、批处理脚本、样例结果和 Sonnet/Gemini 对比网页的可迁移项目。仓库按“拿到另一台电脑即可继续处理”的方式整理；原始数据集、模型权重、API 请求体和凭据不在仓库中。
固定标注约定
输入视频：81 帧、16 FPS，帧 0 是 conditioning frame。
内容窗口固定为 [1,17)、[17,33)、[33,49)、[49,65)、[65,81)，每个窗口 16 帧、约 1 秒。
每个 chunk 只写一个高层 Move 和一个高层 Camera；跨 chunk 的同一个动作复用同一个 Action ID。
当前生产输出默认只保留顶层 english_json，chunk 证据使用完整的 16 帧 MP4（不使用四联图）。
Prompt 要求按观看者屏幕的左/右描述，并按 chunk 内时间顺序组织详细视觉叙述；HUD/overlay 不写入结果。
目录… See the full description on the dataset page: https://huggingface.co/datasets/mikusama99/cs2-v3-prompt-labeling-project.