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image/webp

Dataset Card for the PoseText Dataset

The PoseText Dataset can be used to enhance vision-language model performance in the task of human pose estimation.

Dataset Details

Dataset Description

Parsing body keypoints from the Voxel51/MPII_Human_Pose_Dataset, parsing into a text-based format used in Molmo

import re
import numpy as np

def extract_points(molmo_output, image_w, image_h):
    all_points = []
    for match in re.finditer(r'x\d*="\s*([0-9]+(?:\.[0-9]+)?)"\s+y\d*="\s*([0-9]+(?:\.[0-9]+)?)"', molmo_output):
        try:
            point = [float(match.group(i)) for i in range(1, 3)]
        except ValueError:
            pass
        else:
            point = np.array(point)
            if np.max(point) > 100:
                # Treat as an invalid output
                continue
            point /= 100.0
            point = point * np.array([image_w, image_h])
            all_points.append(point)
    return all_points
  • Curated by: [remyx.ai]
  • Language(s) (NLP): [en]

Citation

If you found this resource useful, please consider citing:

@misc{posetext2024,
  title={PoseText},
  author={Terry Rodriguez and Salma Mayorquin},
  organization={Remyx AI},
  year={2024},
  month={September},
  note = {Dataset},
  url = {https://huggingface.co/datasets/salma-remyx/PoseText}
}
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