Metadata-Version: 2.1
Name: streamlit-terran-timeline
Version: 0.0.17
Summary: Create faces timelines from videos
Home-page: https://github.com/pentogroup/streamlit-terran-timeline
Author: Pento AI
Author-email: hello@pento.ai
License: UNKNOWN
Description: ![Streamlit Terran Timeline logo](resources/logo.jpg)
        
        # Terran timelines
        
        Creating face-recognition timelines on videos has never been so easy! Using the power
        of [Terran](https://github.com/pento-group/terran) we can easily build these timelines.
        
        ## Installation
        
        This Streamlit component requires the following packages for working properly:
        
        ```bash
        # Install dependencies
        pip install --upgrade streamlit terran youtube-dl
        
        # Install the component
        pip install streamlit-terran-timeline
        ```
        
        ## Usage
        
        <p align="center">
          <img src="resources/animation.gif" alt="Streamlit Terran Video animation"/>
        </p>
        
        You can generate a timeline from **any** kind of video using the `generate_timeline` function and then using the `terran_timeline` Streamlit component like this:
        
        ```python
        import streamlit as st
        from streamlit_terran_timeline import generate_timeline, terran_timeline
        
        # Generate the timeline information
        timeline = generate_timeline("https://www.youtube.com/watch?v=dQw4w9WgXcQ")
        
        #
        # Display the timeline. If the users click, you'll get the exact second of
        # the part of the timeline video. By default, it returns 0.
        #
        start_time = terran_timeline(timeline)
        
        st.write(f"User clicked on second {start_time}")
        ```
        
        You can also check out more examples in the [examples folder](streamlit_terran_timeline/examples).
        
        ## Development process
        
        1. First, switch the `_RELEASE` variable from `streamlit_terran_timeline/__init__.py` to `False`.
        2. Then, start a development server at `streamlit_terran_timeline/frontend` by running `npm install` and then `npm run start`
        3. Also, you'll need to install the package internally like `pip install -e .`
        4. Finally, run streamlit on and use the component! For example, you can run `streamlit run streamlit_terran_timeline/examples/youtube.py`
        
        ## What's Terran?
        
        [Terran](https://github.com/pento-group/terran) is human-perception library made by [Pento](https://pento.ai) 🚀
        
        With Terran, making this demo was super easy! You can take a look at the [`generate_timeline`](streamlit_terran_timeline/timeline/generator.py) function to understand how Terran modules works with **videos**, **face-recognition**, and **face-detection**.
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
