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https://github.com/yurijmikhalevich/rclip
AI-Powered Command-Line Photo Search Tool
https://github.com/yurijmikhalevich/rclip
artificial-intelligence computer-vision hacktoberfest image-search photography python
Last synced: 3 months ago
JSON representation
AI-Powered Command-Line Photo Search Tool
- Host: GitHub
- URL: https://github.com/yurijmikhalevich/rclip
- Owner: yurijmikhalevich
- License: mit
- Created: 2021-06-04T16:13:21.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-02T10:10:10.000Z (4 months ago)
- Last Synced: 2024-03-02T11:26:02.191Z (4 months ago)
- Topics: artificial-intelligence, computer-vision, hacktoberfest, image-search, photography, python
- Language: Python
- Homepage:
- Size: 1.14 MB
- Stars: 591
- Watchers: 5
- Forks: 48
- Open Issues: 13
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Lists
- Awesome-Linux-Software - ](#contributors-)
[[Blog]](https://mikhalevi.ch/rclip-an-ai-powered-command-line-photo-search-tool/) [[Demo on YouTube]](https://www.youtube.com/watch?v=tAJHXOkHidw) [[Paper]](https://www.thinkmind.org/index.php?view=article&articleid=content_2023_1_20_60011)
**rclip** is a command-line photo search tool powered by the awesome OpenAI's [CLIP](https://github.com/openai/CLIP) neural network.
## Installation
### Linux
```bash
sudo snap install rclip
```
Alternative options (AppImage and pip)
If your Linux distribution doesn't support [snap](https://snapcraft.io/rclip), you can use one of the alternative installation options:
#### AppImage (self-contained x86_64 executable)
On Linux x86_64, you can install **rclip** as a self-contained executable.
1. Download the AppImage from the latest [release](https://github.com/yurijmikhalevich/rclip/releases).
2. Execute the following commands:
```bash
chmod +x
sudo mv /usr/local/bin/rclip
```
#### Using pip
```bash
pip install --extra-index-url https://download.pytorch.org/whl/cpu rclip
```
### macOS
```bash
brew install yurijmikhalevich/tap/rclip
```
Alternative option (pip)
```bash
pip install rclip
```
### Windows
1. Download the "*.msi" from the latest [release](https://github.com/yurijmikhalevich/rclip/releases).
2. Install **rclip** by running the installer.
Alternative option (pip)
```bash
pip install rclip
```
## Usage
```bash
cd photos && rclip "search query"
```
When you run **rclip** for the first time in a particular directory, it will extract features from the photos, which takes time. How long it will take depends on your CPU and the number of pictures you will search through. It took about a day to process 73 thousand photos on my NAS, which runs an old-ish Intel Celeron J3455, 7 minutes to index 50 thousand images on my MacBook with an M1 Max CPU, and three hours to process 1.28 million images on the same MacBook.
For a detailed demonstration, watch the video: https://www.youtube.com/watch?v=tAJHXOkHidw.
### Similar image search
You can use another image as a query by passing a file path or even an URL to the image file, and **rclip** will find the images most similar to the one you used as a query. If you are referencing a local image via a relative path, you **must** prefix it with `./`. For example:
```bash
cd photos && rclip ./cat.jpg
# or use URL
cd photos && rclip https://raw.githubusercontent.com/yurijmikhalevich/rclip/main/tests/e2e/images/cat.jpg
```
Check this video out for the image-to-image search demo: https://www.youtube.com/watch?v=1YQZKeCBxWM.
### Combining multiple queries
You can add and subtract image and text queries from each other; here are a few usage examples:
```bash
cd photos && rclip horse + stripes
cd photos && rclip apple - fruit
cd photos && rclip "./new york city.jpg" + night
cd photos && rclip "2:golden retriever" + "./swimming pool.jpg"
cd photos && rclip "./racing car.jpg" - "2:sports car" + "2:snow"
```
If you want to see how these queries perform when executed on the 1.28 million images ImageNet-1k dataset, check out the demo on YouTube: https://www.youtube.com/watch?v=MsTgYdOpgcQ.
### How do I preview the results?
If you are using either one of [iTerm2](https://iterm2.com/), [Konsole](https://konsole.kde.org/) (version 22.04 and higher), [wezterm](https://wezfurlong.org/wezterm/), [Mintty](https://mintty.github.io/), or [mlterm](https://mlterm.sourceforge.net/) all you need to do is pass `--preview` (or `-p`) argument to **rclip**:
```bash
rclip -p kitty
```
Using a different terminal or viewer
If you are using any other terminal or want to view the results in your viewer of choice, you can pass the output of **rclip** to it. For example, on Linux, the command from below will open top-5 results for "kitty" in your default image viewer:
```bash
rclip -f -t 5 kitty | xargs -d '\n' -n 1 xdg-open
```
The `-f` param or `--filepath-only` makes **rclip** print the file paths only, without scores or the header, which makes it ideal to use together with a custom viewer as in the example.
I prefer to use **feh**'s thumbnail mode to preview multiple results:
```bash
rclip -f -t 5 kitty | feh -f - -t
```
## Help
```bash
rclip --help
```
## Contributing
This repository follows the [Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0/) standard.
### Running locally from the source code
To run **rclip** locally from the source code, you must have [Python](https://www.python.org/downloads/) and [Poetry](https://python-poetry.org/) installed.
Then do:
```bash
# clone the source code repository
git clone [email protected]:yurijmikhalevich/rclip.git
# install dependencies and rclip
cd rclip
poetry install
# activate the new poetry environment
poetry shell
```
If the poetry environment is active, you can use **rclip** locally, as described in the [Usage](#usage) section above.
## Contributors ✨
Thanks go to these wonderful people and organizations ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
Thanks to [Caphyon](https://github.com/Caphyon) and Advanced Installer team for generously supplying **rclip** project with the Professional Advanced Installer license for creating the Windows installer.
This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind are welcome!
## License
MIT
