Ubuntu build instructions.

Author: Fmeson

README.md

@@ -31,16 +31,72 @@ It uses a deep learning–based denoising model designed to preserve fine image
 
 ---
 
-## Installation
+## Installation 
+
+### Build from source from git (linux):
+
+Clone the repository, enter the RawRefinery directory and install locally with pip. I recommend setting up a python 3.11 virtual environment, conda environment, or the equivalent. 
+
+#### Install required libraries
+sudo apt install python3 python3.12-venv build-essential python3-dev spice-vdagent qemu-guest-agent, upx-ucl
+
+
+```bash
+sudo apt install python3 python3.12-venv build-essential python3-dev
+git clone https://github.com/rymuelle/RawRefinery.git
+cd RawRefinery
+python3 -m venv .venv
+. .venv/bin/activate
+python3 -m pip install .
+```
+After this step, you can run the program as:
+
+```bash
+python3 main.py
+```
+
+However, if you wish to build an installable applicaiton, you may use pyinstaller. Still in the RawRefinery top level directory:
+
+```bash
+python3 -m pip install pyinstaller
+# Clean up previous builds 
+rm -rf build dist __pycache__ 
+pyinstaller linux.spec
+```
+
+
+# To build .deb
+sudo apt update
+sudo apt install ruby ruby-dev build-essential
+sudo gem install --no-document fpm
+
+
+```
+mkdir -p staging/opt/RawRefinery
+mkdir -p staging/usr/share/applications
+cp -r dist/RawRefinery/* staging/opt/RawRefinery/
+cp linux/RawRefinery.desktop staging/usr/share/applications/RawRefinery.desktop
+fpm -n rawrefinery -v 1.0.0 --description "A PySide6 application for Raw Data Processing." \
+    -t deb -s dir \
+    -C staging \
+    --url "http://example.com/rawrefinery" \
+    --vendor "Ryan Mueller" \
+    --license "MIT" \
+    .
+```
+
+```bash
+sudo dpkg -i rawrefinery_1.0.0_amd64.deb
+```
+
+### Download prebuilt installer (Mac OS Only, Windows and Linux executables coming soon)
 
 Download the macOS build here:
 [**RawRefinery v1.3.0-alpha**](https://github.com/rymuelle/RawRefinery/releases/download/v1.3.0-alpha)
 
-Windows and Linux versions are coming soon, along with setup instructions for building from source.
-
 ---
 
-## 🚀 Usage
+## Usage
 
 1. **First launch:**
    On first run, the app will download the denoising model (~500 MB).

linux.spec

@@ -0,0 +1,47 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+datas = [
+    ('RawRefinery/verify/model_signing_public_key.pem', 'RawRefinery/verify')
+]
+
+a = Analysis(
+    ['main.py'],
+    pathex=[],
+    binaries=[],
+    datas=datas,
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    [],
+    exclude_binaries=True,
+    name='RawRefinery',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.datas,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    name='RawRefinery',
+)