Metadata-Version: 2.1
Name: chrysalis
Version: 1.0.0
Summary: Chrysalis Python Cloud SDK for streaming live media
Home-page: https://github.com/chryscloud/chrys-cloud-sdk-python.git
Author: Igor Rendulic
License: UNKNOWN
Description: # Python Chrysalis Cloud SDK
        
        This repository houses the official Chrysalis Cloud Python SDK for use with [Chryscloud.com](https://chryscloud.com/) cloud, end-to-end media streaming and analytics platform.
        
        Chrysalis Cloud SDK aims to provide easy and powerful control over live media streaming consumption and ingestion into various machine learning libraries in the cloud.
        
        If you're looking for a hybrid edge-cloud solution we recommend you look into our open source project [Chrysalis Edge Proxy](https://github.com/chryscloud/video-edge-ai-proxy)
        
        ## Contents
        
        - [Features](#features)
        - [Prerequisite](#prerequisite)
        - [Installation](#installation)
        - [Usage](#usage)
            - [Probing](#probe)
            - [Live stream frames](#retrieve-latest-video-image-from-a-live-stream)
            - [Buffered frames in the past](#retrieve-video-images-from-the-past)
            - [Thumbnail image from video stream](#thumbnail-image-from-video-stream)
            - [Turn permanent storage on/off](#turn-storage-on-and-off)
            - [Example](#example)
              - [Live stream with OpenCV](#display-live-stream-with-opencv)
        - [Development](#development)
            - [Mac OS X](#mac-os-x)
            - [Ubuntu >= 18.04 LTS](#mac-os-x)
            - [Ubuntu < 18.04 LTS](#mac-os-x)
            - [Installing](#installing)
        
        ## Features
        
        - Easy integration with numerous machine learning platforms
        - Support for easy access to RTMP live video stream from Chrysalis Cloud (live video/audio streaming)
        - Supporting for any camera that has RTMP streaming abilities
        - Deals with complexities of media stream management
        - Secure access media streams
        
        ## Prerequisite
        
        - [Install anaconda](https://docs.anaconda.com/anaconda/install/)
        - [Install FFmpeg > 4.0](https://ffmpeg.org/download.html)
        
        Check `FFmpeg` version:
        ```
        ffmpeg -version
        ```
        
        ## Installation
        
        Create `environment.yml` file. 
        
        You can easily add to this file dependencies and additional image manipulation libraries such as Pillow and OpenCV.
        
        [If you need GPU support, you can check how to work with Anaconda and GPU packages](https://docs.anaconda.com/anaconda/user-guide/tasks/gpu-packages/). 
        
        
        ```yaml
        name: chryssdktest
        channels:
          - conda-forge
        dependencies:
          - ca-certificates=2020.1.1=0
          - certifi=2020.4.5.1=py37_0
          - pip=20.0.2=py37_1
          - wheel=0.34.2=py37_0
          - python=3.7.7=hcf32534_0_cpython
          - opencv=4.2.0
          - av=7.0.1
          - numpy=1.18.1
          - redis-py=3.4.1
          - pip:
            - Cython
            - chrysalis==1.0.0
        ```
        
        Create new conda environment:
        ```shell
        conda env create -f environment.yml
        ```
        
        ## Usage
        
        - all returned images are in numpy format.
        - all returned images are in bgr24 pixel format.
        
        Check ChImage attributes for more details
        
        ### Probe
        
        Probing returns information about the streaming media. It gives you a sense if the camera is streaming, when it was last seen, what is the frame cache duration stored on the Chrysalis streaming server.
        
        ```python
        import chrysalis
        # connection to Chrysalis Cloud
        chrys = chrysalis.Connect(host="https://myserver.at.chrysvideo.com", port="1234", password="mypassword", ssl_ca_cert="mycert.cer")
        # returns ProbeInfo object
        probe = chrys.Probe()
        print("start {}, end {}, duration {} s, assessed fps {}".format(probe.start_timestamp, probe.end_timestamp, probe.duration, probe.fps))
        ```
        
        The ProbeInfo object returns the information about cached frames as well as assessment of FPS (frames per second) streamed from the camera.
        
        `start_timestamp` and `end_timestamp` are UTC times in milliseconds since epoch.
        
        ```python
        ProbeInfo Attributes
            ----------
            start_timestamp : int
                Earlies contained media data in video stream cache
            end_timestamp : int
                Latest contained media data in video stream cache
            duration : int
                Duration of the buffered media stream in seconds
            fps : int
                Approximation of Frames per Second of source stream
            """
        ```
        
        ## Retrieve latest video image from a live stream
        
        Chrysalis Cloud Python SDK takes care of delivering crisp and clear images from your live video stream, regardless of the processing speeds, speed ups or slow downs because of the latency or even if your camera disconnects from the network.
        
        ```python
        import chrysalis
        
        # connection to Chrysalis Cloud
        chrys = chrysalis.Connect(host="https://myserver.at.chrysvideo.com", port="1234", password="mypassword", ssl_ca_cert="mycert.cer")
        
        # Perpetual reading of the stream
        while True:
            # VideoLatestImage returns ChImage object
            img = chrys.VideoLatestImage()
        ```
        
        `ChImage` object returned from VideoLatestImage has a following structure:
        
        ```python
        ChImage Attributes
            ----------
            data: numpy
                Image stored in numpy in bgr24 format
            start_timestamp : int
                Earlies contained media data in video stream cache
            end_timestamp : int
                Latest contained media data in video stream cache
            duration : int
                Duration of the buffered media stream in seconds
            fps : int
                Approximation of Frames per Second of source stream
            """
        ```
        
        VideoLatestImage returns `None` image when frame not available.
        
        VideoLatestImage might return None in cases when querying for the next frame is faster than the camera stream produces them.
        
        The SDK will not return already consumed frames (images) in the perpetual reading of the stream.
        
        You can also consume live stream images from mutliple sinks in case when you need to run the same live stream (e.g. the same image) through multiple Computer Vision algorithms. Not returning already consumed frames applies per SDK instance basis.
        
        ## Retrieve video images from the past
        
        Based on what is available in the frame cache on Chrysalis streaming nodes you can also query video images from the past. Use `Probing` in case you need more information how much back in time you can query the video stream.
        
        ```python
        import chrysalis
        
        # connection to Chrysais Cloud
        chrys = chrysalis.Connect(hos="https://myserver.at.chrysvideo.com", prt="1234", password="mypassword", ssl_ca_cert="mycert.cer")
        
        probe = ch.Probe()
        start = probe.end_timestamp - (1000 * 30) # 30 seconds in the past
        end = probe.end_timestamp - (1000 * 15) # until 15 seconds in the past (end > start)
        
        # Perpetual reading of the stream until end is reached
        while True:
            # VideoLatestImage returns ChImage object
            img = ch.VideoPastImage(start, end)
        ```
        
        ## Thumbnail image from video stream
        
        Thumbnails are in `bgr24 format in numpy array`. In fact all images for local consumption are in the same format. This makes it easy to consume images in any processing and analytics after. 
        
        ```python
        import chrysalis
        
        chrys = chrysalis.Connect(host="https://myserver.at.chrysalis.com", port="1234", password="mypassword", ssl_ca_cert="mycert.crt")
        
         d = datetime.today() - timedelta(hours=0, minutes=0, seconds=2)
        img = chrys.Screenshot(dt=d)
        ```
        
        Due to the nature of H.264 straming it is not guaranteed the successfulness of the Screenshot method. In case no screenshot was found `img = None`. 
        
        This function tries to traverse the H.264 buffered stream seeking for I-Frame. the closest I-Frame to given `dt` (timestamp) is returned if I-Frame found. 
        
        ## Turn Storage On and Off
        
        Based on video analysis you can decide to store a stream into the permanent Chrysalis Cloud storage. Since live video form a webcam might be streaming 24/7 we don’t necessarily need to store everything, but rather we can perform simple analysis (e.g. movement detection, face recognition, …) to decide when and for how long we want to permanently store that video segment.
        
        `Coming soon`
        
        ## Example
        
        All examples are in `/examples` folder. Create conda environment from prepared `environment.yml` in examples folder before you run the examples.  
        
        ### Display live stream with OpenCV
        
        ```python
        import chrysalis
        
        # connection to Chrysalis Cloud
        chrys = chrysalis.Connect(host="https://myserver.at.chrysalis.com", port="1234", password="mypassword", ssl_ca_cert="mycert.cer")
        
        # Perpetual reading of the stream
        while True:
            # VideoLatestImage returns ChImage object
            img = chrys.VideoLatestImage()
            if img is not None:
                cv2.imshow("live video", img.data)
                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break
        ```
        
        # Development
        
        ## Install FFmpeg
        
        ### Mac OS X
        
        ```
        brew install ffmpeg pkg-config
        ```
        
        ### Ubuntu >= 18.04 LTS
        
        On Ubuntu 18.04 LTS everything can come from the default sources:
        
        ```
        sudo apt-get install -y python-dev pkg-config
        
        # Library components
        sudo apt-get install -y \
            libavformat-dev libavcodec-dev libavdevice-dev \
            libavutil-dev libswscale-dev libswresample-dev libavfilter-dev
        ```
        
        ### Ubuntu < 18.04 LTS
        
        On older Ubuntu releases you will be unable to satisfy these requirements with the default package sources. We recommend compiling and installing FFmpeg from source. For FFmpeg:
        
        ```
        sudo apt install \
            autoconf \
            automake \
            build-essential \
            cmake \
            libass-dev \
            libfreetype6-dev \
            libjpeg-dev \
            libtheora-dev \
            libtool \
            libvorbis-dev \
            libx264-dev \
            pkg-config \
            wget \
            yasm \
            zlib1g-dev
        
        wget http://ffmpeg.org/releases/ffmpeg-3.2.tar.bz2
        tar -xjf ffmpeg-3.2.tar.bz2
        cd ffmpeg-3.2
        
        ./configure --disable-static --enable-shared --disable-doc
        make
        ```
        
        
        ## Installing
        
        
        ```bash
        git clone https://github.com/cocoonhealth/ChrysalisPythonSDK.git
        
        cd ChrysalisPythonSDK
        
        sudo pip install -e . 
        ```
        This should install it's dependencies also. 
        
        # Contributing
        
        Please read `CONTRIBUTING.md` for details on our code of conduct, and the process of submitting pull requests to us. 
        
        # Versioning
        
        Current version is initial release - 1.0.0
        
        # License
        
        This project is licensed under Apache 2.0 License - see the `LICENSE` for details.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Multimedia :: Sound/Audio
Classifier: Topic :: Multimedia :: Sound/Audio :: Conversion
Classifier: Topic :: Multimedia :: Video
Classifier: Topic :: Multimedia :: Video :: Conversion
Requires-Python: >=3.6
Description-Content-Type: text/markdown
