- name
- dpi-upscaler-checker
- description
- Check image DPI and intelligently upscale low-resolution images using
- version
- 1.0.0
- category
- Visual
- tags
- author
- AIPOCH
- license
- MIT
- status
- Draft
- risk_level
- Medium
- skill_type
- Tool/Script
- owner
- AIPOCH
- reviewer
- last_updated
- 2026-02-06
DPI Upscaler & Checker
Check if images meet 300 DPI printing standards, and intelligently restore blurry low-resolution images using AI super-resolution technology.
Features
- DPI Detection: Read and verify image DPI information
- Intelligent Analysis: Calculate actual print size and pixel density
- Super-Resolution Restoration: Use Real-ESRGAN algorithm to enhance image clarity
- Batch Processing: Support single image and batch folder processing
- Format Support: JPG, PNG, TIFF, BMP, WebP
Use Cases
- Academic paper figure DPI checking
- Print image quality pre-inspection
- Low-resolution material restoration
- Document scan enhancement
Usage
Check Single Image DPI
python scripts/main.py check --input image.jpg
Batch Check Folder
python scripts/main.py check --input ./images/ --output report.json
Super-Resolution Restoration
python scripts/main.py upscale --input image.jpg --output upscaled.jpg --scale 4
Batch Fix Low DPI Images
python scripts/main.py upscale --input ./images/ --output ./output/ --min-dpi 300 --scale 2
Parameters
Check Command
| Parameter | Type | Default | Required | Description |
|---|
--input | string | - | Yes | Input image path or folder |
--output | string | stdout | No | Output report path |
--target-dpi | int | 300 | No | Target DPI threshold |
Upscale Command
| Parameter | Type | Default | Required | Description |
|---|
--input | string | - | Yes | Input image path or folder |
--output | string | - | Yes | Output path |
--scale | int | 2 | No | Scale factor (2/3/4) |
--min-dpi | int | - | No | Only process images below this DPI |
--denoise | int | 0 | No | Denoise level (0-3) |
--face-enhance | flag | false | No | Enable face enhancement |
Output Description
DPI Check Report
{
"file": "image.jpg",
"dpi": [72, 72],
"width_px": 1920,
"height_px": 1080,
"print_width_cm": 67.7,
"print_height_cm": 38.1,
"meets_300dpi": false,
"recommended_scale": 4.17
}
Restored Image
- Automatically saved as
<original_filename>_upscaled.<extension> - Preserves original EXIF information
- Sets DPI to 300
Dependencies
- Python >= 3.8
- Pillow >= 9.0.0
- opencv-python >= 4.5.0
- numpy >= 1.21.0
- realesrgan (optional, for best results)
Algorithm Description
DPI Calculation
Actual DPI = Pixel dimensions / Physical dimensions
Print size (cm) = Pixel count / DPI * 2.54
Super-Resolution
- Default use of Real-ESRGAN model
- Support lightweight bicubic interpolation fallback
- Intelligent model selection (general/anime/face)
Notes
- Input image DPI information may be inaccurate; actual pixel calculation shall prevail
- Super-resolution cannot create non-existent information; extremely blurry images have limited improvement
- Large file processing requires more memory
- GPU acceleration requires CUDA environment (optional)
Risk Assessment
| Risk Indicator | Assessment | Level |
|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
Security Checklist
- [ ] No hardcoded credentials or API keys
- [ ] No unauthorized file system access (../)
- [ ] Output does not expose sensitive information
- [ ] Prompt injection protections in place
- [ ] Input file paths validated (no ../ traversal)
- [ ] Output directory restricted to workspace
- [ ] Script execution in sandboxed environment
- [ ] Error messages sanitized (no stack traces exposed)
- [ ] Dependencies audited
Prerequisites
# Python dependencies
pip install -r requirements.txt
Evaluation Criteria
Success Metrics
- [ ] Successfully executes main functionality
- [ ] Output meets quality standards
- [ ] Handles edge cases gracefully
- [ ] Performance is acceptable
Test Cases
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- Performance: Large dataset → Acceptable processing time
Lifecycle Status
- Current Stage: Draft
- Next Review Date: 2026-03-06
- Known Issues: None
- Planned Improvements:
- Performance optimization - Additional feature support
