---
name: dpi-upscaler-checker
description: Check if images meet 300 DPI printing standards, and intelligently restore blurry low-resolution images using AI super-resolution technology.
license: MIT
author: AIPOCH
---
> **Source**: [https://github.com/aipoch/medical-research-skills](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` path), or would require unsupported assumptions. For missing inputs, state exactly which fields are missing.

## 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

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

### Super-Resolution Restoration
```text
python scripts/main.py upscale --input image.jpg --output upscaled.jpg --scale 4
```

### Batch Fix Low DPI Images
```text
python scripts/main.py upscale --input ./images/ --output ./output/ --min-dpi 300 --scale 2
```

### Demo Mode (no real images required)
```text
python scripts/main.py --demo
```

## 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 |
| `--json` | flag | false | No | Output results as JSON to stdout |

### 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

### DPI Check Report (JSON)
```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` fails or required inputs are incomplete:
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)

```text
pip install -r requirements.txt
```


---
Source attribution: aipoch
Original project: https://github.com/aipoch/medical-research-skills
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: aipoch
Original project: https://github.com/aipoch/medical-research-skills
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Design, Marketing
Roles: Content Marketer, Graphic Designer, UX Designer
Specialties: API
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 4eaaba9341e42929b18b76989ed9bc7a4147b0e0052f8357ed238d24624b8cf1