def main():
background_locked = False
timer_time = time.monotonic()
def run_inference(engine, input_tensor):
return engine.run_inference(input_tensor)
def render_overlay(engine, output, src_size, inference_box):
nonlocal timer_time, background_locked
svg_canvas = svgwrite.Drawing('', size=src_size)
outputs, inference_time = engine.ParseOutput()
now_time = time.monotonic()
if not background_locked:
print('Waiting for everyone to leave the frame...')
pose_camera.shadow_text(svg_canvas, 10, 20,
'Waiting for everyone to leave the frame...')
if outputs: # frame still has people in it, restart timer
timer_time = now_time
elif now_time > timer_time + BACKGROUND_DELAY: # frame has been empty long enough
background_locked = True
print('Background set.')
for pose in outputs:
pose_camera.draw_pose(svg_canvas, pose, src_size, inference_box)
return (svg_canvas.tostring(), background_locked)
pose_camera.run(run_inference, render_overlay)
def main():
background_image = None
timer_time = time.monotonic()
def render_overlay(engine, image, svg_canvas):
nonlocal timer_time, background_image
outputs, inference_time = engine.DetectPosesInImage(image)
now_time = time.monotonic()
if background_image is None:
pose_camera.shadow_text(
svg_canvas, 10, 20,
'Waiting for everyone to leave the frame...')
if outputs: # frame still has people in it, restart timer
print('Waiting for everyone to leave the frame...')
timer_time = now_time
elif now_time > timer_time + BACKGROUND_DELAY: # frame has been empty long enough
background_image = image
print('Background set.')
else:
image = background_image
for pose in outputs:
pose_camera.draw_pose(svg_canvas, pose)
return image
pose_camera.run(render_overlay, use_appsrc=True)
def main():
pose_tracker = PoseTracker()
synth = fluidsynth.Synth()
synth.start('alsa')
soundfont_id = synth.sfload('/usr/share/sounds/sf2/FluidR3_GM.sf2')
for channel, instrument in enumerate(CHANNELS):
synth.program_select(channel, soundfont_id, 0, instrument)
prev_notes = set()
def run_inference(engine, input_tensor):
return engine.run_inference(input_tensor)
def render_overlay(engine, output, src_size, inference_box):
nonlocal prev_notes
svg_canvas = svgwrite.Drawing('', size=src_size)
outputs, inference_time = engine.ParseOutput(output)
poses = [
pose for pose in (Pose(pose, 0.2) for pose in outputs)
if pose.keypoints
]
pose_tracker.assign_pose_ids(poses)
velocities = {}
for pose in poses:
left = pose.keypoints.get('left wrist')
right = pose.keypoints.get('right wrist')
if not (left and right): continue
identity = IDENTITIES[pose.id % len(IDENTITIES)]
left = 1 - left.yx[0] / engine.image_height
right = 1 - right.yx[0] / engine.image_height
velocity = int(left * 100)
i = int(right * identity.extent)
note = (identity.base_note + OCTAVE * (i // len(SCALE)) +
SCALE[i % len(SCALE)])
velocities[(identity.channel, note)] = velocity
for note in prev_notes:
if note not in velocities: synth.noteoff(*note)
for note, velocity in velocities.items():
if note not in prev_notes: synth.noteon(*note, velocity)
prev_notes = velocities.keys()
for i, pose in enumerate(poses):
identity = IDENTITIES[pose.id % len(IDENTITIES)]
pose_camera.draw_pose(svg_canvas,
pose,
src_size,
inference_box,
color=identity.color)
return (svg_canvas.tostring(), False)
pose_camera.run(run_inference, render_overlay)
def main():
pose_tracker = PoseTracker()
def run_inference(engine, input_tensor):
return engine.run_inference(input_tensor)
def render_overlay(engine, output, src_size, inference_box):
svg_canvas = svgwrite.Drawing('', size=src_size)
outputs, inference_time = engine.ParseOutput(output)
poses = [
pose for pose in (Pose(pose, 0.2) for pose in outputs)
if pose.keypoints
]
pose_tracker.assign_pose_ids(poses)
velocities = {}
for pose in poses:
left = pose.keypoints.get('left wrist')
right = pose.keypoints.get('right wrist')
if not (left and right): continue
identity = IDENTITIES[pose.id % len(IDENTITIES)]
lefty = 1 - left.yx[0] / engine.image_height
leftx = 1 - left.yx[1] / engine.image_width
righty = 1 - right.yx[0] / engine.image_height
rightx = 1 - right.yx[1] / engine.image_width
#print (lefty, leftx, righty, rightx)
#print (int(lefty * 1200)+900 , int(leftx * 2400)+900, int(righty * 1200)+900, int((rightx-0.5) * 2400)+900 )
#ch3 = int(lefty * 1200)+900
#ch4 = int(leftx * 2400)+900
#ch2 = int(righty * 1200)+900
# ch1 = int((rightx-0.5) * 2400)+900
#These values have been scaled down , making control easier
ch3 = int(lefty * 600) + 1200
ch4 = int(leftx * 1200) + 1200
ch2 = int(righty * 600) + 1200
ch1 = int((rightx - 0.5) * 1200) + 1200
print(ch1, ch2, ch3, ch4)
#print("Set Ch1-Ch8 overrides to 110-810 respectively")
vehicle.channels.overrides = {
'1': ch1,
'2': ch2,
'3': ch3,
'4': ch4,
'5': 1000,
'6': 1000,
'7': 1000,
'8': 1000
}
#Need to reduce command stream to 10 Hz, so we don<t get buffers overflow and lag
time.sleep(0.1)
for i, pose in enumerate(poses):
identity = IDENTITIES[pose.id % len(IDENTITIES)]
pose_camera.draw_pose(svg_canvas,
pose,
src_size,
inference_box,
color=identity.color)
return (svg_canvas.tostring(), False)
pose_camera.run(run_inference, render_overlay)