metadata

language:
  - en
pretty_name: Recon2025AHONT1
tags:
  - audio-to-3d
  - 3d-reconstruction
license: other
task_categories:
  - text-to-3d
  - image-to-3d
size_categories:
  - n<1K
modalities:
  - images
  - text
annotations_creators:
  - no-annotation
source_datasets:
  - original

https://huggingface.co/datasets/ajsbsd/recon2025AHONT1

📂 Data Source

colorbar [ERROR]: CPT has no z-slices! [Session pygmt-session (9)]: Error returned from GMT API: GMT_CPT_READ_ERROR (8) [Session pygmt-session (9)]: Error returned from GMT API: GMT_CPT_READ_ERROR (8) The original aircraft reconnaissance data comes from the National Hurricane Center's archive.

View source TXT files

Recon2025AHONT1 Dataset

This dataset contains multimodal data for 3D reconstruction experiments, potentially linked to models like Hunyuan3D.

📥 Install Required Tools

To work with Hugging Face datasets in Python:

pip install datasets
pip install pillow soundfile numpy
pip install pillow soundfile huggingface_hub

Visual Example

import pygmt
import pandas as pd

# Sample DataFrame
data = {
    "longitude": [-90.47, -90.45, -90.44, -90.42, -90.40, -90.38, -90.36],
    "latitude": [28.27, 28.29, 28.31, 28.33, 28.35, 28.37, 28.39],
    "temp": [-18.5, -18.5, -18.5, -18.5, -18.5, -18.5, -18.2]  # One different value
}

df = pd.DataFrame(data)

fig = pygmt.Figure()

# Set region based on data
minlon, maxlon = df["longitude"].min() - 1, df["longitude"].max() + 1
minlat, maxlat = df["latitude"].min() - 1, df["latitude"].max() + 1

# Create basemap
fig.basemap(region=[minlon, maxlon, minlat, maxlat], projection="M15c", frame=True)
fig.coast(shorelines="1/0.5p", land="lightgray", water="white")

# Define CPT based on temperature range
pygmt.makecpt(cmap="hot", series=[df["temp"].min(), df["temp"].max()])

# Plot colored points
fig.plot(
    x=df["longitude"],
    y=df["latitude"],
    style="c0.5c",
    cmap=True,
    fill=df["temp"],
    pen="black"
)

# Add colorbar
fig.colorbar(frame='af+l"Temperature (°C)"')

fig.show()