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# Error Level Analysis (ELA) Detector
This module provides a function to perform Error Level Analysis (ELA) on images to detect potential manipulations or edits.
## Function: `run_ela`
```python
def run_ela(image: Image.Image, quality: int = 90, threshold: int = 15) -> bool:
```
### Description
Error Level Analysis (ELA) works by recompressing an image at a specified JPEG quality level and comparing it to the original image. Differences between the two images reveal areas with inconsistent compression artifacts — often indicating image manipulation.
The function computes the maximum pixel difference across all color channels and uses a threshold to determine if the image is likely edited.
### Parameters
| Parameter | Type | Default | Description |
| ----------- | ----------- | ------- | ------------------------------------------------------------------------------------------- |
| `image` | `PIL.Image` | N/A | Input image in RGB mode to analyze. |
| `quality` | `int` | 90 | JPEG compression quality used for recompression during analysis (lower = more compression). |
| `threshold` | `int` | 15 | Pixel difference threshold to flag the image as edited. |
### Returns
`bool`
- `True` if the image is likely edited (max pixel difference > threshold).
- `False` if the image appears unedited.
### Usage Example
```python
from PIL import Image
from detectors.ela import run_ela
# Open and convert image to RGB
img = Image.open("example.jpg").convert("RGB")
# Run ELA detection
is_edited = run_ela(img, quality=90, threshold=15)
print("Image edited:", is_edited)
```
### Notes
- The input image **must** be in RGB mode for accurate analysis.
- ELA is a heuristic technique; combining it with other detection methods increases reliability.
- Visualizing the enhanced difference image can help identify edited regions (not returned by this function but possible to add).
### Installation
Make sure you have Pillow installed:
```bash
pip install pillow
```
### Running Locally
Just put the function in a notebook or script file and run it with your image. It works well for basic images.
[🔙 Back to Main README](../README.md)
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