bundling

.gitignore

@@ -1,10 +1,23 @@
+# Virtual environments
 venv
+.venv
+
+# Cache
 __pycache__
+
+# IDEs
 .idea
+
+# Test output
 video_output
 audio.wav
 /keyboard_output.txt
 /mouse_output.txt
 /vpt-audio.wav
 /vpt-keyboard.txt
 /vpt-mouse.txt
+
+# PyInstaller
+*.spec
+build
+dist

Pipfile

@@ -19,9 +19,12 @@ matplotlib = "*"
 [dev-packages]
 python-language-server = {extras = ["all"], version = "*"}
 pylint = "*"
+pyinstaller = "*"
 
 [requires]
 python_version = "3.8"
 
 [scripts]
 vpt = "python -m vpt"
+bundle-win = "pyinstaller ./vpt/__main__.py --name vpt --distpath ./dist --add-data 'models;models'"
+bundle-unix = "pyinstaller ./vpt/__main__.py --name vpt --distpath ./dist --add-data \"models:models\""

README.md

@@ -23,8 +23,17 @@ On Arch Linux, use:
 
 ## Usage
 
-Run `pipenv run  vpt <subcommand>`. For detailed usage information, run `pipenv run vpt -h`.
+Run `pipenv run vpt <subcommand>`. For detailed usage information, run `pipenv run vpt -h`.
 
 If you are using Linux, you might need to run some commands as root (or with `sudo`)
 as [mouse recording](https://github.com/boppreh/mouse#:~:text=requires%20sudo)
 and [keyboard recording](https://github.com/boppreh/keyboard#:~:text=requires%20sudo) require it.
+
+## Bundling
+
+To bundle the application as a distributable executable, run `pipenv run bundle-win` on Windows, or `pipenv run bundle-unix` on most unix-based systems.
+The resulting program can be found in the "_dist/vpt_" folder, with the exeuctable file itself called `vpt`.
+
+Note: The Windows version requires that the ["Microsoft C++ Redistributable
+for Visual Studio 2015, 2017 and 2019"](https://support.microsoft.com/help/2977003/the-latest-supported-visual-c-downloads) be installed on the system before running.
+They are **not** bundled with the program.

vpt/__main__.py

@@ -13,5 +13,6 @@
 elif args['cmd'] == 'check':
     check()
 elif args['cmd'] is None:
+    # If no argument, fall back to recording
     # record(args['audio'], args['video'])
     pass

vpt/cli/record.py

@@ -0,0 +1,2 @@
+def record():
+    pass

vpt/processors/gaze_detector/__init__.py

@@ -1,5 +1,7 @@
 """Human facial landmark detector based on Convolutional Neural Network."""
 import math
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # To disable TF's warnings
 
 import cv2
 import numpy as np
@@ -12,6 +14,8 @@
 from vpt.processors.base import ProcessorBase
 from vpt.sources.base import SourceBase
 
+tf.get_logger().setLevel('ERROR')
+
 
 class FaceDetector:
     """Detect human face from image"""