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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) | |