10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Generate standardized figure legends for scientific charts and graphs. Trigger when user uploads/requesting legend for research figures, academic papers, or data charts. Supports bar charts, line graphs, scatter plots, box plots, heatmaps, and microscopy images. This tool generates text legends only, not visualizations.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install aipoch-ai/figure-legend-genInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Generate publication-quality figure legends for scientific research charts and images.
| Chart Type | Description |
|---|---|
| Bar Chart | Compare values across categories |
| Line Graph | Show trends over time or continuous data |
| Scatter Plot | Display relationships between variables |
| Box Plot | Show distribution and outliers |
| Heatmap | Display matrix data intensity |
| Microscopy | Fluorescence/confocal images |
| Flow Cytometry | FACS plots and histograms |
| Western Blot | Protein expression bands |
python scripts/main.py --input <image_path> --type <chart_type> [--output <output_path>]
| Parameter | Required | Description |
|---|---|---|
--input |
Yes | Path to chart image |
--type |
Yes | Chart type (bar/line/scatter/box/heatmap/microscopy/flow/western) |
--output |
No | Output path for legend text (default: stdout) |
--format |
No | Output format (text/markdown/latex), default: markdown |
--language |
No | Language (en/zh), default: en |
# Generate legend for bar chart
python scripts/main.py --input figure1.png --type bar
# Save to file
python scripts/main.py --input plot.jpg --type line --output legend.md
# Chinese output
python scripts/main.py --image.png --type scatter --language zh
Generated legends follow academic standards:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Figure Legend Generator Generate publication-quality figure legends for scientific research charts and images. ## Supported Chart Types | Chart Type | Description | |------------|-------------| | Bar Chart | Compare values across categories | | Line Graph | Show trends over time or continuous data | | Scatter Plot | Display relationships between variables | | Box Plot | Show distribution and outliers | | Heatmap | Display matrix data intensity | | Microscopy | Fluorescence/confocal images | | Flow Cytometry | FACS plots and histograms | | Western Blot | Protein expression bands | ## Usage ```bash python scripts/main.py --input <image_path> --type <chart_type> [--output <output_path>] ``` ### Parameters | Parameter | Required | Description | |-----------|----------|-------------| | `--input` | Yes | Path to chart image | | `--type` | Yes | Chart type (bar/line/scatter/box/heatmap/microscopy/flow/western) | | `--output` | No | Output path for legend text (default: stdout) | | `--format` | No | Output format (text/markdown/latex), default: markdown | | `--language` | No | Language (en/zh), default: en | ### Examples ```bash # Generate legend for bar chart python scripts/main.py --input figure1.png --type bar # Save to file python scripts/main.py --input plot.jpg --type line --output legend.md # Chinese output python scripts/main.py --image.png --type scatter --language zh ``` ## Legend Structure Generated legends follow academic standards: 1. **Figure Number** - Sequential numbering 2. **Brief Title** - Concise description 3. **Main Description** - What the figure shows 4. **Data Details** - Key statistics/measurements 5. **Methodology** - Brief experimental context 6. **Statistics** - P-values, significance markers 7. **Scale Bars** - For microscopy images ## Technical Notes - **Difficulty**: Low - **Dependencies**: PIL, pytesseract (optional OCR) - **Processing**: Vision analysis for chart type detection - **Output**: Structured markdown by default...
generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
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