This application helps you find out if an image is generated by AI or if it is a real photo. It does this by checking the image’s metadata and using smart machine learning techniques behind the scenes.
- Detect AI-created images instantly
- Use metadata info normally hidden to the eye
- Works for most common image types, like JPG and PNG
- No technical knowledge needed to run the app
To make sure the app works well on your computer, check these basic needs:
- Operating System: Windows 10 or higher / macOS 10.14 or higher
- Processor: At least a dual-core CPU, 2 GHz or better
- Memory: Minimum 4 GB RAM
- Storage: Around 200 MB free space for installation
- Internet: Required for first-time setup and updates, but not for regular use
- Graphics: No special GPU required
Follow these steps to get the app on your computer and start checking images:
Visit the release page to get the latest version of the software.
On the releases page, look for the file that matches your system:
- For Windows, look for files ending with
.exeor.msi - For Mac, look for
.dmgor.pkg
Choose the latest version to get all features and fixes.
- On Windows: Double-click the downloaded
.exeor.msifile and follow the on-screen instructions. - On Mac: Open the
.dmgfile and drag the app icon to your Applications folder.
After installation, open the app like any other program on your computer.
You can access the latest official version from the GitHub releases page:
When you open the page:
- Scroll down to the "Assets" section under the newest release
- Download the file that suits your operating system
- Follow the installation instructions from the previous section
Once the app is open, here’s how to check an image:
-
Select the Image
Click the “Browse” or “Select Image” button to find the picture you want to test. The app supports common formats like JPG, PNG, and TIFF. -
Start the Detection
Press the “Analyze” or “Check Image” button to begin. The software will review the image's metadata and run its machine learning checks. -
View the Result
After a moment, the app will display whether it found signs that the image was AI-generated or likely real. -
Additional Info
You can see details about the metadata that influenced the decision. This helps you understand why the software reached its conclusion.
Metadata is hidden information stored inside image files. It includes details like:
- When and where the image was created
- The device used to take the photo
- Software used to edit the image
- Technical data about how the image was saved
AI-generated images often have missing or unusual metadata because software creates them differently than real cameras. Our app looks for these clues to tell what is real.
The app includes simple settings that let you adjust how deep the checks go:
- Basic Scan: Quick check of key metadata fields
- Full Scan: More detailed analysis for better accuracy
- File History: Optionally save past scan results for review
- Update Checks: Enable automatic updates to keep detection methods current
You can access these from the settings menu in the app.
The app works with most popular image types:
- JPEG / JPG (.jpg, .jpeg)
- PNG (.png)
- TIFF (.tif, .tiff)
- BMP (.bmp)
If your image type is not supported, convert it to one of these formats using any free image converter online.
If you run into any problems, try these steps:
- Make sure your system meets the requirements listed above
- Download and install the latest version from the releases page
- Restart the app and try again
- Test with another image to see if the issue is specific
- If the app won’t open, try running it as an administrator on Windows or check macOS security settings for permission to run apps from identified developers
For detailed technical questions, check the GitHub repository issues tab or contact support.
This tool was created to help users check if images have been made by AI. It combines metadata analysis with machine learning to give quick and readable results. This helps people spot deepfakes, AI art, or tampered photos.
If you need help beyond this guide, visit the Issues section on GitHub or open a new support request.