def play_pause():
"""
Called when the Play/Pause button is pressed. Starts/stops/resumes a song.
"""
if not Playlist.is_playing():
play_pause_btn.setText("Pause")
Playlist.play()
now_playing_text.show()
if not current_song_text.isVisible():
current_song_text.setText("{}".format(Playlist.get_current_song()))
current_song_text.show()
else:
play_pause_btn.setText("Play")
Playlist.pause()
now_playing_text.hide()
def refresh():
"""
Called when new images are to be displayed on the screen (i.e. new reaction from the user). Sets a new pixmap
component for each of the image object on the screen. Finally, repaints the whole window.
"""
# The later two parameters of scaled() are for keeping the aspect ratio and smoothing the result of scaling
camera_img.setPixmap(QPixmap(CAMERA_IMG_PATH).scaled(camera_img.width(), camera_img.height(), 1, 1))
live_img.setPixmap(QPixmap(LIVE_IMG_PATH).scaled(live_img.width(), live_img.height(), 1, 1))
prog_img.setPixmap(QPixmap(PROG_IMG_PATH).scaled(prog_img.width(), prog_img.height(), 1, 1))
if Playlist.is_playing():
current_song_text.setText("{}".format(Playlist.get_current_song()))
window.show()
def play_entry(label):
"""
Called to trigger the playing/pausing of a specific entry, given its label. This also sets specific buttons
and labels to appropriate states to reflect the change.
:param label: The label containing the name of the entry to be played or paused.
:return:
"""
Playlist.play_song(label)
if not Playlist.is_playing():
user_interface.GUI.play_pause_btn.setText("Pause")
user_interface.GUI.now_playing_text.show()
user_interface.GUI.current_song_text.setText("{}".format(label.text()))
if not user_interface.GUI.current_song_text.isVisible():
user_interface.GUI.current_song_text.show()
else:
user_interface.GUI.play_pause_btn.setText("Play")
Playlist.pause()
user_interface.GUI.now_playing_text.hide()
def main():
"""
Main method.
"""
# Choose running model.
global args
args = CLIparser.parseFlags()
db, sessionID = initialize()
# Start the camera and the GUI.
thread = threading.Thread(target=GUI.run)
thread.setDaemon(True)
vc = cv2.VideoCapture(0)
fv = FaceVerification(sessionID, args.test)
GUI.setSomeVariables(vc, sessionID, fv)
# vc.set(cv2.CAP_PROP_BUFFERSIZE, 1)
thread.start()
start_time = time.time()
while True:
frame = get_frame(vc)
# Query the Model once every 3 seconds.
end_time = time.time()
if end_time - start_time < 3.1: # Uncomment the following two lines for a continuos camera feed.
#WARNING: A Raspberry Pi 4 model B, 2GB RAM, will not support this change.
# cv2.imwrite('frame.png', frame)
# GUI.refresh_frame()
continue
start_time = time.time()
if not GUI.dead and not GUI.frozen:
if args.azure:
# Query Azure.
if fv.getStatus():
emotions = get_facial_emotion(frame, fv)
else:
emotions = get_facial_emotion(frame, None)
else:
# Query our model.
remove_frame()
face_isolated = facechop(frame)
emotions = classify(None, face_isolated)
if emotions:
if Playlist.is_playing():
# Update global descriptors based on song descriptors and user emotions.
current_song = Playlist.get_current_song()
current_descriptors = Tracklist.get_song(
db, current_song)['descriptors']
emotion_list = getEmotionList(emotions)
descriptors.update_descriptors(emotion_list,
current_descriptors)
progress_history.update_progress_log(
db, sessionID, emotion_list)
current_song_score = descriptors.get_song_score(
current_descriptors)
if args.test:
print('Current song score: %s' % current_song_score)
# Change song if song score is low.
if current_song_score <= THRESHOLD:
Playlist.skip_song()
remove_frame("progress_plot")
remove_frame("emotions_plot")
if args.azure:
plotter.write_plot(emotions)
else:
plotter.write_plot({'': emotions})
GUI.refresh()
if GUI.dead:
if args.test:
print("GUI is closed, shutting down...")
break
print("[EMMA]: Closing the camera...")
close_camera(vc)
cleanup()
thread.join()