Source: https://github.com/aipoch/medical-research-skills

DPI Upscaler & Checker

Check if images meet 300 DPI printing standards, and intelligently restore blurry low-resolution images using AI super-resolution technology.

Input Validation

This skill accepts: image files (JPG, PNG, TIFF, BMP, WebP) or folder paths for DPI checking and/or AI super-resolution upscaling.

If the user's request does not involve image DPI checking or upscaling — for example, asking to analyze text documents, process audio files, or perform general data analysis — do not proceed with the workflow. Instead respond:

"dpi-upscaler-checker is designed to check image DPI standards and restore low-resolution images. Your request appears to be outside this scope. Please provide an image file path or folder, or use a more appropriate tool for your task."

Do not continue the workflow when the request is out of scope, missing a critical input (

--input

When to Use

• Check whether images meet 300 DPI printing standards
• Upscale or restore low-resolution images using AI super-resolution
• Batch-process folders of mixed-DPI images for print readiness

Quick Check

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py --demo
python -c "import PIL; print('Pillow OK')"
python scripts/main.py check --input image.jpg --json

Workflow

1. Validate input first — confirm the request is within scope and

   --input

   path is provided before any processing.
2. Confirm the user objective, required inputs, and non-negotiable constraints.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Usage

Check Single Image DPI

python scripts/main.py check --input image.jpg
python scripts/main.py check --input image.jpg --json        # JSON to stdout for agent consumption

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

Demo Mode (no real images required)

python scripts/main.py --demo

Parameters

Check Command

--input

--output

--target-dpi

--json

Upscale Command

--input

--output

--scale

--min-dpi

--denoise

--face-enhance

Output

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

• Saved as

  <original_filename>_upscaled.<extension>

• Preserves original EXIF information
• Sets DPI metadata to target value

Algorithm

• DPI:

  print_size_cm = (pixel_count / dpi) * 2.54

  ;

  recommended_scale = target_dpi / avg_dpi

• Super-resolution fallback chain: Real-ESRGAN → OpenCV DNN → PIL Lanczos
• RGBA alpha channel upscaled separately and reattached

Known Limitations

• Super-resolution cannot create non-existent information; extremely blurry images have limited improvement
• GPU acceleration requires CUDA environment (optional)
• Batch upscale mode does not currently save a JSON summary report (only check mode saves JSON to

  --output

  )
• EXIF parsing uses

  except (AttributeError, KeyError, TypeError, ZeroDivisionError)

  — bare except replaced with specific exception types
• Output format parameters are conditioned on file extension (JPEG:

  quality=95

  ; PNG:

  compress_level=6

  )
• Batch processing uses

  Path.rglob

  ; resolve paths with

  path.resolve()

  before processing to avoid unexpected directory traversal via symlinks

Fallback Behavior

If

scripts/main.py

1. Report the exact failure point and error message (sanitized — no internal paths).
2. State what can still be completed safely (e.g., DPI check without upscale).
3. Manual fallback:

   from PIL import Image; img = Image.open('file.jpg'); print(img.info.get('dpi'))

   .
4. Do not fabricate execution outcomes or file contents.

Error Handling

• If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
• If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
• If

  scripts/main.py

  fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
• Do not fabricate files, citations, data, search results, or execution outcomes.
• Script exits with non-zero code on error in both check and upscale modes.

Response Template

1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next Checks

Dependencies

• Python >= 3.8
• Pillow >= 9.0.0
• opencv-python >= 4.5.0
• numpy >= 1.21.0
• realesrgan (optional, for best results)

pip install -r requirements.txt