Imeti
Local Image Privacy Tool
Overview
Imeti is a fully local desktop application for image privacy and forensic analysis. It provides a suite of redaction and analysis tools that run entirely on your machine, with no data sent to the cloud.
It is intended for journalists protecting sources, security researchers analyzing suspicious files, and anyone who wants control over what their images reveal.
Screenshots
Features
Privacy & Redaction
- Face Anonymization: AI-powered face detection with four anonymization methods — Gaussian blur, pixelation, black bar, and solid fill.
- Text Redaction: Automatically detects text regions in an image and redacts them using the EAST model.
- Metadata Scrubbing: Remove all metadata or selectively strip EXIF, IPTC, XMP, GPS data, ICC profiles, and hidden thumbnails.
- Batch Processing: Anonymize and clean entire folders of images at once.
Forensic Analysis
- Steganography Scanner: Detects hidden data payloads using LSB analysis, chi-square tests, and entropy analysis.
- Watermark Detection: Frequency-domain analysis to flag invisible watermarks.
- Cryptographic Hashing: Computes SHA-256, SHA-1, and MD5 hashes for file integrity verification.
- Metadata Injection: Deliberately inject custom or fake EXIF data to mislead trackers.
Installation & Setup
The Easy Way (PyPI)
You can install Imeti instantly via pip:
pip install imeti
Once installed, you can launch the app from anywhere in your terminal by simply typing:
imeti
The Developer Way (From Source)
# Clone the repository
git clone https://github.com/Astrosp/Imeti.git
cd Imeti
# Install locally
pip install -e .
Note: The first time you use Face Detection or Text Redaction, Imeti will briefly connect to the internet to download the required pre-trained AI models (~100MB). These are cached locally in the
models/directory afterward.
Usage Guide
- Load Media — Drag and drop an image, click "Open Image," or select "Batch" to process a folder.
- Configure Options — Use the sidebar to enable or disable Face Anonymization, Text Redaction, or Metadata Stripping.
- Analyze — Run Steganography or Watermark scans from the forensic tools section.
- Process — Click "Process" to apply the selected redactions.
- Save — Click "Save" to export the sanitized image to disk.
Privacy Guarantee
Imeti is designed to operate entirely offline:
- No telemetry
- No analytics
- No cloud APIs
Your data never leaves your computer.
License
This project is licensed under the MIT License, free for personal use only. See the LICENSE file for details.
Metadata
Release files for Imeti 1.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| imeti-1.0.3.tar.gz | 800.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| imeti-1.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.6 MB
Release files / imeti-1.0.3.tar.gz
| Download URL | imeti-1.0.3.tar.gz |
|---|---|
| Size | 800.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
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PyPI Publish Attestation
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Signed by GitHub Actions, verified by PyPI on Jul 17, 2026.
Transparency logRelease files / imeti-1.0.3-py3-none-any.whl
| Download URL | imeti-1.0.3-py3-none-any.whl |
|---|---|
| Size | 807.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 17, 2026.
Transparency log