force
Datasets
All datasets matching “force”PPTAgent-parsed_dataZenodo10K
PPTAgent/Zenodo10K
This is the dataset used in PPTAgent, crawled from zenodo.
To the best of our knowledge, it is the largest presentation dataset currently available, comprising over 10,000 PowerPoint (.pptx) files, all distributed under a clear and compliant license.
For more information, please visit our github repo.
dirname = f"zenodo-pptx/pptx/{task['license']}/{task['created'][:4]}/"
basename = f"{task['checksum'][4:]}-{task['filename']}"
filepath = dirname + basename
try:… See the full description on the dataset page: https://huggingface.co/datasets/Forceless/Zenodo10K.ForceBody_ano
ForceBody
ForceBody pairs the SKEL parametric body model with measured ground reaction forces and inverse-dynamics joint torques across 10,386 motion trials (26.9 hours of motion at 100 Hz) from 140 subjects. A subset of 8,652 trials additionally ships per-frame, per-joint Monte Carlo uncertainty sigma_tau for every torque label.
Each trial is stored as a single NumPy .npz file readable with numpy.load. No nimblephysics, OpenSim, or AddBiomechanics tooling is needed to consume the… See the full description on the dataset page: https://huggingface.co/datasets/ForceBody/ForceBody_ano.supreme_court_opinions_corpus_pdfwebAug24gelsight-force-estimation
Dataset Details
This dataset contains paired tactile and force data, intended for use in predicting 3-axis normal and shear forces applied to the sensor's elastomer. We used three different indenter shapes to collect force-labeled data: hemisphere, sharp, and flat. To measure force ground truths, we employed the ATI nano17 force/torque sensor. The protocol consisted of applying a random normal load (up to 3N) followed by a shear load, achieved by sliding the probe 2mm on the… See the full description on the dataset page: https://huggingface.co/datasets/facebook/gelsight-force-estimation.digit-force-estimation
Dataset Details
This dataset contains paired tactile and force data, intended for use in predicting 3-axis normal and shear forces applied to the sensor's elastomer. We used three different indenter shapes to collect force-labeled data: hemisphere, sharp, and flat. To measure force ground truths, we employed the ATI nano17 force/torque sensor. The protocol consisted of applying a random normal load (up to 5N) followed by a shear load, achieved by sliding the probe 2mm on the… See the full description on the dataset page: https://huggingface.co/datasets/facebook/digit-force-estimation.