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#

bash

python scripts/main.py check --input image.jpg

Batch Check Folder#

bash

python scripts/main.py check --input ./images/ --output report.json

Super-Resolution Restoration#

bash

python scripts/main.py upscale --input image.jpg --output upscaled.jpg --scale 4

Batch Fix Low DPI Images#

bash

python scripts/main.py upscale --input ./images/ --output ./output/ --min-dpi 300 --scale 2

Parameters#

Check Command#

ParameterTypeDefaultRequiredDescription--inputstring-YesInput image path or folder--outputstringstdoutNoOutput report path--target-dpiint300NoTarget DPI threshold

Upscale Command#

ParameterTypeDefaultRequiredDescription--inputstring-YesInput image path or folder--outputstring-YesOutput path--scaleint2NoScale factor (2/3/4)--min-dpiint-NoOnly process images below this DPI--denoiseint0NoDenoise level (0-3)--face-enhanceflagfalseNoEnable face enhancement

Output Description#

DPI Check Report#

json

{
  "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#

text

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#

1. Input image DPI information may be inaccurate; actual pixel calculation shall prevail
2. Super-resolution cannot create non-existent information; extremely blurry images have limited improvement
3. Large file processing requires more memory
4. GPU acceleration requires CUDA environment (optional)

Risk Assessment#

Risk IndicatorAssessmentLevelCode ExecutionPython/R scripts executed locallyMediumNetwork AccessNo external API callsLowFile System AccessRead input files, write output filesMediumInstruction TamperingStandard prompt guidelinesLowData ExposureOutput files saved to workspaceLow

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#

bash

# 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#

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. 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