1. Controlling MXW through Python

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Revision as of 20:13, 3 December 2023 by Hwendler (talk | contribs)
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Python is used in MXW trough a plugin interface. Specified program paths are searched for plugins which are registered, and then loaded through the user interface.

As of version 7.2., plugins are available in the playlist. There are two paths searched during program startup, the program folder and the user folder:

  • (Program folder)/plugins/playlist/python/
  • ~.StageDesigner/plugins/playlist/python/ (Unix)
  • ~.StageDesigner/plugins/playlist/python/ (Windows)

Each plugin resides in a folder. Inside this folder, two files have to be present,

  • mxw_plugin.ini
  • mxw_main.py

The file mxw_plugin.ini defines the registration of the plugin. The following fields are valid:

Caption text
Tag Use Values/Example
plugin_version Plugin Version 1
plugin_script_language Plugin Script Language Python
plugin_action_level Plugin Activity Switch disabled = not visible
plugin_menu_parent Top level parent in playlist menu "AI", "IO" ..
plugin_menu_name Playlist menu entry "Face detection"
plugin_grid_name Default name in grid (may be completed via script) "Face detect"
plugin_grid_bg_color Default color in grid (may be changed via script) 0.95 0.05 0.45 1.00 (RGBA with range 0..1)
plugin_tooltip Tool tip in grid and panel "This plugin triggers the playlist when it finds a Face"

An example mxw_plugin.ini looks like this:

[mxw_plugin]                            ; must be here
plugin_version = 1                      ; must be V1 (as of V7.2)
plugin_script_language = Python         ; must be Python (as of V7.2)
plugin_menu_parent = AI
plugin_menu_name = NeuronalNet(Dlib) Face Detect Plugin
plugin_grid_name = Face Detect Plugin
plugin_grid_bg_color = 0.950000 0.050000 0.450000 1.000000 ; set plugin color.
plugin_tooltip = This plugin triggers the playlist when it finds a Face using a neuronal net (Dlib)

The plugins are defined in a mxw_main.py file. This file is loaded, and the main UI calls the provided interface functions. This is a minimal video writing example:

import tempfile
import mxw, mxw_imgui	# for mxw interaction, mxw ui interaction
import cv2 	        # image processing
import numpy as np	# math

capture_device=""
videosize = (640,480)
f = object()
out = object()

# -----------------------------------------------------------------------------------
def onCreate():
	global capture_device
	dev = mxw.media().get_capture_device_names()
	capture_device = dev[1]
	return

def onAction():
	global capture_device, out, f
	f = tempfile.NamedTemporaryFile(suffix='.avi')
	f.close()
	fourcc = cv2.VideoWriter_fourcc('M','P','4','V')
	out = cv2.VideoWriter(f.name, fourcc, mxw.fps, videosize)
	m = mxw.media(capture_device)
	if(m.isvalid()):
		m.reference(True)
	return

def onPostAction():
	global capture_device, out, f
	out.release()
	mxw.preload(1).set_media(f.name)
	m = mxw.media(capture_device)
	if(m.isvalid()):
		m.reference(False)
	return

def onNewFrameInPlayoutCue():
	global capture_device, out, f
	m = mxw.media(capture_device)
	if(m.isvalid()):
		img = m.get_image_sample_cvmat(videosize[0],videosize[1])
		img = np.array(img, copy=False)
		img = cv2.flip(img, 0)
		out.write(img)
	return

# render in panel for settings etc
def onRenderPanel():
	mxw_imgui.text_unformatted("This plugin records a camera")
	return