Dpi Upscaler Checker

Check image DPI and intelligently upscale low-resolution images using super-resolution

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

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

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 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

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