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ovmf.py
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ovmf.py
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from pathlib import Path
import sys
import time
import numpy as np
from PIL import Image
from lib.connection import Sender, Receiver
from lib.module_base import loadConfig
class Interface:
'''
Python Interface to the Open Virtual Mirror Framework
Please see psychopy_example.py
'''
def __init__(self, view_only = False, debug = True, pipeline=None):
'''
Set view_only = True if you want to display the avatar only.
Only useful if you want to use multiple Interfaces.
Set debug = True to print out some infos.
'''
self.debug = debug
config = loadConfig(pipeline=pipeline, module='blender_render_output')
self.receiver = Receiver(address = config['address'], type='render_output', queue_size=config['queue_size'])['render_output']
self.view_only = view_only
if not view_only:
self.commands = Sender(address = config['control_commands'])
# Need some time to init...
time.sleep(1)
def check_view_only(self):
if self.view_only:
if self.debug:
print("Avatar class is view-only. Can't change parameters.")
return True
def set_parameter(self, update):
'''
Set generic parameters in form of a dictionary.
Look at the modules for supported parameters.
'''
if self.debug:
print("Parameter: " + str(update))
self.commands.send(update)
def set_delay(self, delay_seconds = 0):
'''
Set the avatar motion delay in seconds
'''
if self.check_view_only():
return
params = {
'delay_sec' : float(delay_seconds)
}
self.set_parameter(params)
def set_avatar(self, avatar_name = 'FexMM'):
if self.check_view_only():
return
params = {
'avatar_name' : avatar_name
}
self.set_parameter(params)
def set_scale(self, avatar_scale = 1.0):
'''
set avatar uniform scale in 3d
'''
if self.check_view_only():
return
params = {
'avatar_scale' : avatar_scale
}
self.set_parameter(params)
def set_depth_scale(self, avatar_depth_scale = 1.0):
'''
set avatar depth scale factor
'''
if self.check_view_only():
return
params = {
'avatar_depth_scale' : avatar_depth_scale
}
self.set_parameter(params)
def set_location_offset(self, avatar_location_offset = [0,0,0]):
'''
set avatar location offset (before application of scale factor)
'''
if self.check_view_only():
return
params = {
'avatar_location_offset' : avatar_location_offset
}
self.set_parameter(params)
def set_rotation_offset(self, avatar_rotation_offset = [0,0,0]):
'''
set avatar rotation offset (before application of scale factor)
'''
if self.check_view_only():
return
params = {
'avatar_rotation_offset' : avatar_rotation_offset
}
self.set_parameter(params)
def set_gaze_offset(self, gaze_offset = [0,0] ):
'''
set avatar gaze offset relative to the screen midpoint in blender units
'''
if self.check_view_only():
return
params = {
'avatar_gaze_offset_x' : gaze_offset[0],
'avatar_gaze_offset_y' : gaze_offset[1]
}
self.set_parameter(params)
def receive_image(self):
return self.receiver.receive(block = False)
def receive_and_set_image(self, imgStim = None, adjust_render_size = True, fill_color = 'black'):
'''
Receives a new rendered image if available (non-blocking) and sets it to the Psychopy
image stimulus (imgStim).
If adjust_render_size is True, the size of the rendered image
will be adjusted to fit into imgStim. Aspect ratio is kept and fill_color is used to
fill-in the border area.
Otherwise, the size of imgStim is adjusted to the size of the rendered image.
'''
if imgStim is not None:
data, image = self.receive_image()
# SLOW. TODO: Improve and fix if image exceeds ImageStim size
if image is not None:
# print(image.shape)
if adjust_render_size:
img = Image.fromarray(image).convert('RGBA')
size = (int(imgStim.size[0]),int(imgStim.size[1]))
img.thumbnail(size)
image = Image.new('RGBA', size, fill_color)
offset = (int((imgStim.size[0] - img.size[0])/2),
int((imgStim.size[1] - img.size[1])/2))
image.paste(img, offset)
image = image.convert('RGB')
image = np.asarray(image)
image = image / 255
else:
imgStim.size = (image.shape[1] , image.shape[0])
image = image / 255
size = imgStim.size
imgStim.image = image
# Workaround to avoid imagestim to resize
imgStim.size = size
return data
return None
def receive_and_convert_image(self):
'''
Receives a new rendered image if available (non-blocking) and sets it to the numpy array.
'''
data, im = self.receive_image()
if data is None or im is None:
return None, None
im = im / 255
return data, im
if __name__ == '__main__':
print("This is the Python interface for external toolboxes.")
print("If you want to start the OVMF, please use startup.py")