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.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install aipoch-ai/figure-legend-gen打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
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:
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# 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
Productivity system based on Maya calendar with 13 natural tones for project management and personal development
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