image-generation

name

image-generation

description

Use this skill when generating images programmatically with Python. This includes creating charts, diagrams, mind maps, flowcharts, infographics, data visualizations, annotated images, posters, and any visual output that requires code-based rendering. Trigger when user asks to "generate an image", "create a diagram", "draw a chart", "make a mind map", "visualize data", or requests any PNG/JPG/SVG output created via code. Also use when matplotlib, PIL/Pillow, or similar graphics libraries are needed.

Image Generation Guide

Generate images programmatically using Python. This guide covers matplotlib for diagrams/charts and PIL for image manipulation.

Environment Setup

pip install matplotlib pillow numpy --break-system-packages

Chinese Font Configuration (Critical)

Chinese text renders as boxes without proper fonts. Always configure before plotting:

import matplotlib.pyplot as plt

# Check available CJK fonts
import matplotlib.font_manager as fm
cjk_fonts = [f.name for f in fm.fontManager.ttflist 
             if 'CJK' in f.name or 'Noto' in f.name or 'WenQuanYi' in f.name]
print(cjk_fonts)

# Configure (use first available)
plt.rcParams['font.sans-serif'] = ['Noto Sans CJK SC', 'WenQuanYi Zen Hei', 'DejaVu Sans']
plt.rcParams['axes.unicode_minus'] = False  # Fix minus sign display

If no CJK fonts available, install: apt-get install -y fonts-noto-cjk fonts-wqy-zenhei

Quick Start

Basic Chart

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(figsize=(10, 6), dpi=150)
x = np.linspace(0, 10, 100)
ax.plot(x, np.sin(x), label='sin(x)')
ax.plot(x, np.cos(x), label='cos(x)')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.legend()
ax.set_title('Trigonometric Functions')
plt.savefig('chart.png', bbox_inches='tight', facecolor='white')
plt.close()

Basic Diagram (No Axes)

fig, ax = plt.subplots(figsize=(12, 8), dpi=150)
ax.set_xlim(0, 12)
ax.set_ylim(0, 8)
ax.set_aspect('equal')
ax.axis('off')  # Hide axes for diagrams

# Draw shapes
from matplotlib.patches import FancyBboxPatch, Circle, Arrow
box = FancyBboxPatch((1, 3), 3, 2, boxstyle="round,pad=0.1", 
                      facecolor='#3498DB', edgecolor='white', linewidth=2)
ax.add_patch(box)
ax.text(2.5, 4, 'Node A', ha='center', va='center', color='white', fontsize=12)

plt.savefig('diagram.png', bbox_inches='tight', facecolor='white')
plt.close()

Core Patterns

1. Mind Map / Tree Diagram

Use radial or hierarchical layout with FancyBboxPatch for nodes:

def draw_node(ax, x, y, text, color, width=2.5, height=0.8, fontsize=10):
    """Draw a rounded rectangle node with centered text."""
    from matplotlib.patches import FancyBboxPatch
    box = FancyBboxPatch((x - width/2, y - height/2), width, height,
                         boxstyle="round,pad=0.05,rounding_size=0.2",
                         facecolor=color, edgecolor='white', linewidth=2)
    ax.add_patch(box)
    ax.text(x, y, text, ha='center', va='center', fontsize=fontsize, 
            color='white', weight='bold')

def draw_connection(ax, start, end, color='#555'):
    """Draw a line between two points."""
    ax.plot([start[0], end[0]], [start[1], end[1]], 
            color=color, linewidth=2, zorder=0)

See scripts/mindmap_template.py for complete example.

2. Flowchart

Use different shapes for different node types:

Shape	Meaning	Code
Rectangle	Process	FancyBboxPatch with boxstyle="round"
Diamond	Decision	RegularPolygon with numVertices=4, orientation=np.pi/4
Parallelogram	Input/Output	Custom Polygon
Oval	Start/End	Ellipse

Use FancyArrowPatch for arrows with arrowstyle='->'.

3. Data Visualization

# Bar chart
ax.bar(categories, values, color=['#E74C3C', '#3498DB', '#2ECC71'])

# Pie chart
ax.pie(sizes, labels=labels, autopct='%1.1f%%', colors=colors)

# Heatmap
im = ax.imshow(data, cmap='viridis')
plt.colorbar(im)

# Scatter with size/color encoding
ax.scatter(x, y, s=sizes, c=colors, alpha=0.6)

4. Annotated Images (PIL + matplotlib)

from PIL import Image
import matplotlib.pyplot as plt

# Load and display image
img = Image.open('photo.jpg')
fig, ax = plt.subplots()
ax.imshow(img)

# Add annotations
ax.annotate('Important!', xy=(100, 150), xytext=(200, 100),
            arrowprops=dict(arrowstyle='->', color='red'),
            fontsize=12, color='red')
ax.add_patch(plt.Rectangle((50, 50), 100, 80, fill=False, edgecolor='red', linewidth=2))

ax.axis('off')
plt.savefig('annotated.png', bbox_inches='tight')

Color Palettes

Professional color schemes:

# Modern flat colors
COLORS = {
    'red': '#E74C3C',
    'blue': '#3498DB', 
    'green': '#2ECC71',
    'orange': '#F39C12',
    'purple': '#9B59B6',
    'teal': '#1ABC9C',
    'dark': '#2C3E50',
    'gray': '#95A5A6'
}

# Categorical palette (up to 10 items)
CATEGORICAL = ['#E74C3C', '#3498DB', '#2ECC71', '#F39C12', '#9B59B6',
               '#1ABC9C', '#E67E22', '#16A085', '#8E44AD', '#2980B9']

# Sequential palette (for gradients)
# Use matplotlib colormaps: 'viridis', 'plasma', 'Blues', 'Reds'

Common Issues & Solutions

Issue: Chinese characters show as boxes

Solution: Configure CJK fonts before any plotting (see Environment Setup)

Issue: Image has extra whitespace

Solution: Use bbox_inches='tight' in savefig()

Issue: Low resolution output

Solution: Increase dpi (150-300 for print quality)

Issue: Transparent background needed

Solution: savefig('out.png', transparent=True)

Issue: Elements overlap

Solution: Adjust figsize, use plt.tight_layout(), or manually position

Issue: Subscript/superscript characters missing

Solution: Avoid Unicode subscripts (₀₁₂). Use LaTeX: $H_2O$, $x^2$

Output Guidelines

1. Always use dpi=150 minimum (300 for print)
2. Use facecolor='white' for consistent background
3. Call plt.close() after saving to free memory
4. Save to /mnt/user-data/outputs/ for user access
5. Prefer PNG for diagrams, JPG for photos

File Structure

scripts/
├── mindmap_template.py    # Mind map with radial layout
├── flowchart_template.py  # Flowchart with decision nodes
└── chart_templates.py     # Common chart types

references/
├── MATPLOTLIB_SHAPES.md   # All available shapes and patches
└── COLOR_REFERENCE.md     # Extended color palettes

Next Steps

• For complex mind maps: See scripts/mindmap_template.py
• For flowcharts: See scripts/flowchart_template.py
• For shape reference: See references/MATPLOTLIB_SHAPES.md
• For extended colors: See references/COLOR_REFERENCE.md