remyxai/PoseFlorence-2
Image-Text-to-Text • 0.3B • Updated • 4 • 3
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The PoseText Dataset can be used to enhance vision-language model performance in the task of human pose estimation.
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
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}
}