def is_new_frame_better(source, driving, precitor):
global avatar_kp
global display_string
if avatar_kp is None:
display_string = "No face detected in avatar."
return False
if predictor.get_start_frame() is None:
display_string = "No frame to compare to."
return True
driving_smaller = resize(driving, (128, 128))[..., :3]
new_kp = predictor.get_frame_kp(driving)
if new_kp is not None:
new_norm = (np.abs(avatar_kp - new_kp)**2).sum()
old_norm = (np.abs(avatar_kp -
predictor.get_start_frame_kp())**2).sum()
out_string = "{0} : {1}".format(int(new_norm * 100),
int(old_norm * 100))
display_string = out_string
log(out_string)
return new_norm < old_norm
else:
display_string = "No face found!"
return False
def load_images(IMG_SIZE=256):
avatars = []
images_list = sorted(glob.glob(f'{opt.avatars}/*'))
for i, f in enumerate(images_list):
if f.endswith('.jpg') or f.endswith('.jpeg') or f.endswith('.png'):
key = len(avatars) + 1
log(f'Key {key}: {f}')
img = cv2.imread(f)
if img.ndim == 2:
img = np.tile(img[..., None], [1, 1, 3])
img = img[..., :3][..., ::-1]
img = resize(img, (IMG_SIZE, IMG_SIZE))
avatars.append(img)
return avatars
def check_connection(socket, timeout=1000):
old_rcvtimeo = socket.RCVTIMEO
socket.RCVTIMEO = timeout
try:
data = msgpack.packb(([], {}))
socket.send_data('hello', data)
attr_recv, data_recv = socket.recv_data()
response = msgpack.unpackb(data_recv)
except zmq.error.Again:
return False
finally:
socket.RCVTIMEO = old_rcvtimeo
log(f"Response to hello is {response}")
return response == 'OK'
def query_cameras(n_cams):
cam_frames = {}
cap = None
for camid in range(n_cams):
log(f"Trying camera with id {camid}")
cap = cv2.VideoCapture(camid)
if not cap.isOpened():
log(f"Camera with id {camid} is not available")
continue
ret, frame = cap.read()
if not ret or frame is None:
log(f"Could not read from camera with id {camid}")
cap.release()
continue
for i in range(10):
ret, frame = cap.read()
cam_frames[camid] = frame.copy()
cap.release()
return cam_frames
cv2.imshow(window, grid)
while True:
key = cv2.waitKey(10)
if g_selected_cam is not None:
break
if key == 27:
break
cv2.destroyAllWindows()
if g_selected_cam is not None:
return list(cam_frames)[g_selected_cam]
else:
return list(cam_frames)[0]
if __name__ == '__main__':
with open('config.yaml', 'r') as f:
config = yaml.load(f, Loader=yaml.FullLoader)
cam_frames = query_cameras(config['query_n_cams'])
if cam_frames:
selected_cam = select_camera(cam_frames)
print(f"Selected camera {selected_cam}")
else:
log("No cameras are available")
def print_help():
log('\n\n=== Control keys ===')
log('1-9: Change avatar')
log('W: Zoom camera in')
log('S: Zoom camera out')
log('A: Previous avatar in folder')
log('D: Next avatar in folder')
log('Q: Get random avatar')
log('X: Calibrate face pose')
log('I: Show FPS')
log('ESC: Quit')
log('\nFull key list: https://github.com/alievk/avatarify#controls')
log('\n\n')
log('X: Calibrate face pose')
log('I: Show FPS')
log('ESC: Quit')
log('\nFull key list: https://github.com/alievk/avatarify#controls')
log('\n\n')
if __name__ == "__main__":
global display_string
display_string = ""
IMG_SIZE = 256
if opt.no_stream:
log('Force no streaming')
_streaming = False
log('Loading Predictor')
predictor_args = {
'config_path': opt.config,
'checkpoint_path': opt.checkpoint,
'relative': opt.relative,
'adapt_movement_scale': opt.adapt_scale,
'enc_downscale': opt.enc_downscale
}
if opt.is_worker:
from afy import predictor_worker
predictor_worker.run_worker(opt.worker_port)
sys.exit(0)
elif opt.worker_host:
import numpy as np
import cv2
from afy.videocaptureasync import VideoCaptureAsync
from afy.arguments import opt
from afy.utils import Once, log, crop, pad_img, resize, TicToc
from sys import platform as _platform
_streaming = False
if _platform == 'linux' or _platform == 'linux2':
import pyfakewebcam
_streaming = True
if _platform == 'darwin':
if opt.worker_host is None:
log('\nOnly remote GPU mode is supported for Mac (use --worker-host option to connect to the server)'
)
log('Standalone version will be available lately!\n')
exit()
def is_new_frame_better(source, driving, precitor):
global avatar_kp
global display_string
if avatar_kp is None:
display_string = "No face detected in avatar."
return False
if predictor.get_start_frame() is None:
display_string = "No frame to compare to."
return True