https://github.com/scanner-research/esper

Query, analysis, and visualization of large video collections
https://github.com/scanner-research/esper

Last synced: about 2 months ago
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Query, analysis, and visualization of large video collections

• Host: GitHub
• URL: https://github.com/scanner-research/esper
• Owner: scanner-research
• Created: 2019-04-12T18:49:34.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2022-12-09T06:29:29.000Z (about 2 years ago)
• Last Synced: 2024-04-14T19:52:49.667Z (9 months ago)
• Language: Python
• Size: 3.18 MB
• Stars: 9
• Watchers: 5
• Forks: 2
• Open Issues: 24
• Metadata Files:
  • Readme: README.md

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README

        
# Esper: a framework for end-to-end video analytics

Esper is a development environment that provides out-of-the-box integration for a variety of tools useful for analyzing videos, including:

* [Scanner](https://github.com/scanner-research/scanner): high-performance parallel processing of videos

* [Rekall](https://github.com/scanner-research/rekall): data representation and operations for spatiotemporal data in Python

* [VGrid](https://github.com/scanner-research/vgrid): visualizing metadata on videos using Python and Javascript

* [Frameserver](https://github.com/scanner-research/frameserver): dynamically extracting frames from a video

* [Django](https://docs.djangoproject.com/en/2.2/): managing SQL models and serving web pages

* [Spark](https://spark.apache.org/): parallel analysis of metadata

Esper is kind of like Ruby on Rails but for video analytics. It provides a skeleton of a data science workbench that you can customize for your particular project, along with a set of useful utility functions, models, preinstalled dependencies, and so on.

**:warning: WARNING :warning:**: Esper is a tool for programmers. It uses a programmatic query interface, which means we use **_REMOTE CODE EXECUTION_** to run queries. DO NOT expose this interface publicly, or else risk having a hacker trash your computer, data, and livelihood.

## Setup

First, install [Docker CE](https://docs.docker.com/engine/installation/#supported-platforms), [Python 3.5](https://www.python.org/downloads/), [jq](https://stedolan.github.io/jq/download/), and [pip](https://pip.pypa.io/en/stable/installing/). If you're on Ubuntu, you can install Python/pip/jq as follows:

```

sudo apt-get install python3 python3-pip jq

```

Ensure that you have Docker version >= 17.12, which you can check by running:

```

$ docker --version

Docker version 17.12.0-ce, build c97c6d6

```

> Note: If you have a GPU and are running on Linux, then install [nvidia-docker2](https://github.com/NVIDIA/nvidia-docker). Set `device = "gpu-9.1-cudnn7` in `config/local.toml`.

Next, you need to install Esper. You can do this through pip, or see the developer instructions below for installing from source.

```

pip3 install esper-video

```

Finally you need to set up your Esper project.

```

mkdir my_project

cd my_project

wget https://raw.githubusercontent.com/scanner-research/esper/master/config/local.toml

esper -c local.toml

docker-compose up -d

```

TODO: next steps

### Esper developers

If you're developing the Esper core platform or otherwise want to stay up to date with our dependencies, then you should clone and link our submodules.

```

git clone --recursive https://github.com/scanner-research/esper

```

TODO: remaining instructions