Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Improve docs for building and installation steps #101

Merged
merged 3 commits into from
Apr 6, 2024
Merged

Improve docs for building and installation steps #101

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
6373c3a
Improve docs for building and installation steps
isZumpo Apr 5, 2024
654f135
Fix typo in readme
isZumpo Apr 5, 2024
8ec33a9
Update doc/installation.md
isZumpo Apr 5, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
132 changes: 4 additions & 128 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -33,138 +33,14 @@ skills and a keen interest in contributing to a nature-focused project, I'd love

<img src="doc/BirdNET-Go-dashboard.webp" />

## Executable Distributions
## Installation

Ready to run binaries can be found from releases section https://github.com/tphakala/BirdNET-Go/releases/
Archives also contains libtensorflowlite_c library.
For detailed installation instructions, see the [installation documentation](doc/installation.md).

### Docker

```
docker run -ti \
-p 8080:8080 \
--env ALSA_CARD=<index/name>
--device /dev/snd \
-v /path/to/config:/config \
-v /path/to/data:/data \
ghcr.io/tphakala/birdnet-go:latest
```

| Parameter | Function |
| :----: | --- |
| `-p 8080` | BirdNET-GO webserver port. |
| `--env ALSA_CARD=<index/name>` | ALSA capture device to use. Find index/name of desired device by executing `arecord -l` on the host. [More info.](#deciding-alsa-card)|
| `--device /dev/snd` | Mounts in audio devices to the container. |
| `-v /config` | Config directory in the container. |
| `-v /data` | Data such as database and recordings. |


#### Deciding ALSA_CARD value

Within the BirdNET-Go container, knowledge of the designated microphone is absent. Consequently, it is necessary to specify the appropriate ALSA_CARD environment variable. Determining the correct value for this variable involves the following steps on the host computer:
1. Open a terminal and execute the command `arecord -l` to list all available capture devices.

```
> arecord -l
**** List of CAPTURE Hardware Devices ****
card 0: PCH [Generic Analog], device 0: Analog [Analog]
Subdevices: 1/1
Subdevice #0: subdevice #0
card 0: PCH [Generic Analog], device 2: Alt Analog [Alt Analog]
Subdevices: 1/1
Subdevice #0: subdevice #0
card 1: Microphone [USB Microphone], device 0: USB Audio [USB Audio]
Subdevices: 1/1
Subdevice #0: subdevice #0
```
2. Identify the desired capture device. In the example above, cards 0 and 1 are available.
3. Specify the ALSA_CARD value when running the BirdNET-Go container. For instance, if the USB Microphone device is chosen, set `ALSA_CARD` to either `ALSA_CARD=1` or `ALSA_CARD=Microphone`.

## Compiling for Linux

### Install TensorFlow Lite C library and setup headers for compile process

Download precompiled TensorFlow Lite C library for Linux from https://github.com/tphakala/tflite_c/releases/tag/v2.14.0

Copy libtensorflowlite_c.so to /usr/local/lib and run ```ldconfig```

```bash
sudo cp libtensorflowlite_c.so /usr/local/lib
sudo ldconfig
```

Clone tensorflow repository, this is required for header files to be present while compiling with CGO

```bash
mkdir ~/src
cd ~/src
git clone https://github.com/tensorflow/tensorflow.git
```

Checkout TensorFlow v2.14.0 release

```bash
cd tensorflow
git checkout tags/v2.14.0
```

### Building BirdNET-Go

Clone BirdNET-Go repository

```bash
git clone https://github.com/tphakala/BirdNET-Go.git
```

Build BirdNET-Go by make, compiled binary will be placed in go-birdnet/bin directory

```bash
cd BirdNET-Go
make
```

## Compiling for Windows

Windows build is cross compiled on Linux, for this you need MinGW-w64 on your build system

```bash
sudo apt install mingw-w64-tools gcc-mingw-w64-x86-64 gcc-mingw-w64-i686
```

Download precompiled TensorFlow Lite C library for Windows from https://github.com/tphakala/tflite_c/releases/tag/v2.14.0

Copy **libtensorflowlite_c.dll** to /usr/x86_64-w64-mingw32/lib/

```bash
sudo cp libtensorflowlite_c.dll /usr/x86_64-w64-mingw32/lib/
```

Clone tensorflow repository, this is required for header files to be present while compiling with CGO

```bash
mkdir ~/src
cd ~/src
git clone https://github.com/tensorflow/tensorflow.git
```

### Cross compiling BirdNET-Go

Clone BirdNET-Go repository

```bash
git clone https://github.com/tphakala/BirdNET-Go.git
```

Build BirdNET-Go by running make windows

```bash
cd BirdNET-Go
make windows
```

Windows executable is in **bin/birdnet.exe**, copy this and **libtensorflowlite_c.so** to your Windows system, library file must be in PATH for birdnet.exe to run properly.
## Building
For instructions on how to build the project, see the [building documentation](doc/building.md).

Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for compile process, and on Windows you need **libtensorflowlite_c.so** for runtime. This sounds backwards but this is how it works.

## Usage

Expand Down
101 changes: 101 additions & 0 deletions doc/building.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
# Building

Building can be a bit tricky because of the many dependencies. It is recommended to follow the [building locally guide](#building-locally) for building the project. However, there is also a provided [devcontainer](#devcontainer) approach that allows for easy development.

## Devcontainer

For convenient development in VSCode, a [devcontainer](https://code.visualstudio.com/docs/remote/containers) can be used. Simply open the project in VSCode and hit `F1`, type `Remote-Containers: Reopen in Container` and wait for the container to build.

The provided [`.devcontainer/devcontainer.json`](.devcontainer/devcontainer.json) contains all required dependencies and also mounts the source code into the container, so one can immediately start coding. When the container starts, a development server is started that can be reached at [localhost:8080](http://localhost:8080). The server automatically reloads the application on any code changes.

Note: Ensure Docker and VSCode with [Remote Development](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack) extension are installed.



## Building locally

### Install prerequisites

#### Install TensorFlow Lite C library

Download precompiled TensorFlow Lite C library for Linux from https://github.com/tphakala/tflite_c/releases/tag/v2.14.0

Copy libtensorflowlite_c.so to /usr/local/lib and run ```ldconfig```

```bash
sudo cp libtensorflowlite_c.so /usr/local/lib
sudo ldconfig
```

Clone tensorflow repository, this is required for header files to be present while compiling with CGO

```bash
mkdir ~/src
cd ~/src
git clone https://github.com/tensorflow/tensorflow.git
```

Checkout TensorFlow v2.14.0 release

```bash
cd tensorflow
git checkout tags/v2.14.0
```

### Building BirdNET-Go

Clone BirdNET-Go repository

```bash
git clone https://github.com/tphakala/BirdNET-Go.git
```

Build BirdNET-Go by make, compiled binary will be placed in go-birdnet/bin directory

```bash
cd BirdNET-Go
make
```

#### Compiling for Windows

Windows build is cross compiled on Linux, for this you need MinGW-w64 on your build system

```bash
sudo apt install mingw-w64-tools gcc-mingw-w64-x86-64 gcc-mingw-w64-i686
```

Download precompiled TensorFlow Lite C library for Windows from https://github.com/tphakala/tflite_c/releases/tag/v2.14.0

Copy **libtensorflowlite_c.dll** to /usr/x86_64-w64-mingw32/lib/

```bash
sudo cp libtensorflowlite_c.dll /usr/x86_64-w64-mingw32/lib/
```

Clone tensorflow repository, this is required for header files to be present while compiling with CGO

```bash
mkdir ~/src
cd ~/src
git clone https://github.com/tensorflow/tensorflow.git
```

### Cross #compiling BirdNET-Go

Clone BirdNET-Go repository

```bash
git clone https://github.com/tphakala/BirdNET-Go.git
```

Build BirdNET-Go by running make windows

```bash
cd BirdNET-Go
make windows
```

Windows executable is in **bin/birdnet.exe**, copy this and **libtensorflowlite_c.so** to your Windows system, library file must be in PATH for birdnet.exe to run properly.

Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for compile process, and on Windows you need **libtensorflowlite_c.so** for runtime. This sounds backwards but this is how it works.
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Correct the explanation regarding the use of libtensorflowlite_c.dll and libtensorflowlite_c.so for Windows compilation and runtime. It seems there might be a mix-up in the explanation. Clarify that libtensorflowlite_c.dll is needed for runtime on Windows, not libtensorflowlite_c.so.

- Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for compile process, and on Windows you need **libtensorflowlite_c.so** for runtime.
+ Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for the compile process, and on Windows, you need **libtensorflowlite_c.dll** for runtime.
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for compile process, and on Windows you need **libtensorflowlite_c.so** for runtime. This sounds backwards but this is how it works.
Yes it is correct that you need **libtensorflowlite_c.dll** in /usr/x86_64-w64-mingw32/lib/ for the compile process, and on Windows, you need **libtensorflowlite_c.dll** for runtime. This sounds backwards but this is how it works.

91 changes: 91 additions & 0 deletions doc/installation.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,91 @@
# Installation

BirdNET-Go can be installed either using Docker or binary provided releases. Docker is the
preferred method, as it provides a self-contained and easily reproducible
environment. However, binary releases are convenient option for users who prefer not to install Docker.


## Docker

**Note**: Docker is currently only supported when running inside a Linux based
isZumpo marked this conversation as resolved.
Show resolved Hide resolved
host system.


### Installing Docker

To install Docker, follow the instructions in the [official installation guide](https://docs.docker.com/engine/install) for your operating system.

### Running BirdNET-GO with Docker - Simple setup


The command bellow will start a container with the latest version BirdNET-Go:
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Fix the typo in "bellow" to "below" to correct the instruction text.

- The command bellow will start a container with the latest version BirdNET-Go:
+ The command below will start a container with the latest version BirdNET-Go:
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
The command bellow will start a container with the latest version BirdNET-Go:
The command below will start a container with the latest version BirdNET-Go:


> docker run -ti -p 8080:8080 --device /dev/snd ghcr.io/tphakala/birdnet-go:latest

Once executed, the service can be reached at [localhost:8080](http://localhost:8080).


### Running BirdNET-GO with Docker - Normal setup
While the [simple](##Running-BirdNET-GO-with-Docker-Simple) example above works, it is highly likely that customizing the runtime settings more as well as enabling persistent storage is desirable. The docker run snippet below offers many more options:

```
docker run -ti \
-p 8080:8080 \
--env ALSA_CARD=<index/name>
--env TZ="<TZ identifier>"
--device /dev/snd \
-v /path/to/config:/config \
-v /path/to/data:/data \
ghcr.io/tphakala/birdnet-go:latest
```

Summary of parameters:

| Parameter | Function |
| :----: | --- |
| `-p 8080` | BirdNET-GO webserver port. |
| `--env ALSA_CARD=<index/name>` | ALSA capture device to use. Find index/name of desired device by executing `arecord -l` on the host. [More info.](#deciding-alsa_card-value)|
| `--env TZ="TZ identifier"` | Timezone to use. See [wikipedia article](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones#List) to find TZ identifier.|
| `--device /dev/snd` | Mounts in audio devices to the container. |
| `-v /config` | Config directory in the container. |
| `-v /data` | Data such as database and recordings. |

#### Example setup

To start BirdNET-GO, simply fill in the values of the parameters. Below is an example of how it might look:

```
docker run -ti \
-p 8080:8080 \
--env ALSA_CARD=0
--env TZ="Europe/Stockholm"
--device /dev/snd \
-v $HOME/BirdNET-Go-Volumes/config:/config \
-v $HOME/BirdNET-Go-Volumes/config:/data \
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

There's a mistake in the volume mapping for the data directory. It should map to /data inside the container, not /config again.

- -v $HOME/BirdNET-Go-Volumes/config:/data \
+ -v $HOME/BirdNET-Go-Volumes/data:/data \
Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation.

Suggested change
-v $HOME/BirdNET-Go-Volumes/config:/data \
-v $HOME/BirdNET-Go-Volumes/data:/data \

ghcr.io/tphakala/birdnet-go:latest
```

#### Deciding ALSA_CARD value

Within the BirdNET-Go container, knowledge of the designated microphone is absent. Consequently, it is necessary to specify the appropriate ALSA_CARD environment variable. Determining the correct value for this variable involves the following steps on the host computer:
1. Open a terminal and execute the command `arecord -l` to list all available capture devices.

```
> arecord -l
**** List of CAPTURE Hardware Devices ****
card 0: PCH [Generic Analog], device 0: Analog [Analog]
Subdevices: 1/1
Subdevice #0: subdevice #0
card 0: PCH [Generic Analog], device 2: Alt Analog [Alt Analog]
Subdevices: 1/1
Subdevice #0: subdevice #0
card 1: Microphone [USB Microphone], device 0: USB Audio [USB Audio]
Subdevices: 1/1
Subdevice #0: subdevice #0
```
2. Identify the desired capture device. In the example above, cards 0 and 1 are available.
3. Specify the ALSA_CARD value when running the BirdNET-Go container. For instance, if the USB Microphone device is chosen, set `ALSA_CARD` to either `ALSA_CARD=1` or `ALSA_CARD=Microphone`.

## Binary releases

Ready to run binaries can be found in [releases](https://github.com/tphakala/BirdNET-Go/releases/) section. Unfortunately, not everything is contained inside the binary itself, meaning that certain dependencies must be installed on the host system first. One of them being TensorFlow Lite C library, see this [guide](building.md#install-tensorflow-lite-c-library) for more information.
Loading