📄 Image10k – Category-Specific Metadata Tables - Images10k - an open, large, human-annotated dataset for biological and artificial visual processing

1🙂 Human Faces – Metadata Overview¶

This section displays metadata for all images in the human_face category. Each row includes the file name, source website, license type, author, and a direct link to the original image. The data was curated to ensure proper attribution and licensing.

⚠️ Note: The table below shows a preview of the dataset (first 30 rows). You can access the full metadata and all related files here:
📂 Browse metadata folder on Google Drive

Source

import pandas as pd
from IPython.display import HTML, display

def show_with_scroll(df):
    html = df.to_html(index=False, escape=False)
    return HTML(f'''
    <div style="height: 400px; overflow: auto; border: 1px solid #ccc;">
        {html}
    </div>
    ''')

# Load Excel metadata
df_faces = pd.read_excel("../image10k-dataset/human_face.xlsx")

# Preview: just the first 30 rows
df_preview = df_faces.head(30).copy()

# Optional: shorten long text columns like 'metadata'
if 'metadata' in df_preview.columns:
    df_preview['metadata'] = df_preview['metadata'].astype(str).str.slice(0, 150) + '...'

# Display with scroll
display(show_with_scroll(df_preview))

2🧍 Human Body Parts – Metadata Overview¶

This section displays metadata for images in the human_body_parts category. Each entry includes the filename, license type, source platform, and author information. These images typically depict limbs, torsos, or other anatomical segments, and were annotated with careful attention to attribution and copyright compliance.

⚠️ Note: The table below shows a preview of the dataset (first 30 rows). You can access the full metadata and all related files here:
📂 Browse metadata folder on Google Drive

Source

import pandas as pd
from IPython.display import HTML, display

# Simple function to show DataFrame with a vertical scrollbar
def show_with_scroll(df):
    html = df.to_html(index=False, escape=False)
    return HTML(f'''
    <div style="height: 400px; overflow: auto; border: 1px solid #ccc;">
        {html}
    </div>
    ''')

# Load the Excel metadata
df_body = pd.read_excel("../image10k-dataset/human_body_parts.xlsx")

# Preview: show only first 30 rows
df_preview = df_body.head(30).copy()

# Optional: shorten long 'metadata' text for cleaner preview
if 'metadata' in df_preview.columns:
    df_preview['metadata'] = df_preview['metadata'].astype(str).str.slice(0, 150) + '...'

# Display the table
display(show_with_scroll(df_preview))

3🐾 Animal Images – Metadata Overview¶

This section contains the metadata for all images in the animal category. Each row corresponds to one image and includes the file name, source website, license type, author and a direct link to the image.

⚠️ Note: The table below shows a preview of the dataset (first 30 rows). You can access the full metadata and all related files here:
📂 Browse metadata folder on Google Drive

Source

import pandas as pd
from IPython.display import HTML, display

# Function to show a scrollable DataFrame preview
def show_with_scroll(df):
    html = df.to_html(index=False, escape=False)
    return HTML(f'''
    <div style="height: 400px; overflow: auto; border: 1px solid #ccc;">
        {html}
    </div>
    ''')

# Load metadata
df_animals = pd.read_excel("../image10k-dataset/animal.xlsx")

# Preview: show only first 30 rows
df_preview = df_animals.head(30).copy()

# Truncate long 'metadata' values
if 'metadata' in df_preview.columns:
    df_preview['metadata'] = df_preview['metadata'].astype(str).str.slice(0, 150) + '...'

# Display preview with scroll
display(show_with_scroll(df_preview))

4🧩 Objects – Metadata Overview¶

This section contains metadata for all images in the object category. These images represent a wide variety of man-made and natural objects, each annotated with information such as source, author, license type, and file extension. The data was curated to ensure proper attribution and licensing.

⚠️ Note: The table below shows a preview of the dataset (first 30 rows). You can access the full metadata and all related files here:
📂 Browse metadata folder on Google Drive

Source

import pandas as pd
from IPython.display import HTML, display

# Function to show a scrollable DataFrame preview
def show_with_scroll(df):
    html = df.to_html(index=False, escape=False)
    return HTML(f'''
    <div style="height: 400px; overflow: auto; border: 1px solid #ccc;">
        {html}
    </div>
    ''')

# Load metadata
df_objects = pd.read_excel("../image10k-dataset/object.xlsx")

# Preview: show only first 30 rows
df_preview = df_objects.head(30).copy()

# Truncate long 'metadata' text
if 'metadata' in df_preview.columns:
    df_preview['metadata'] = df_preview['metadata'].astype(str).str.slice(0, 150) + '...'

# Display preview with scroll
display(show_with_scroll(df_preview))

Images10k - an open, large, human-annotated dataset for biological and artificial visual processing

🧱 Objects

Images10k - an open, large, human-annotated dataset for biological and artificial visual processing

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