| # 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) |
| |
