def main(filename):
from TFLiteFaceDetector import UltraLightFaceDetecion
from TFLiteFaceAlignment import CoordinateAlignmentModel
cap = cv2.VideoCapture(filename)
fd = UltraLightFaceDetecion("weights/RFB-320.tflite", conf_threshold=0.95)
fa = CoordinateAlignmentModel("weights/coor_2d106.tflite")
hp = HeadPoseEstimator("weights/head_pose_object_points.npy", cap.get(3),
cap.get(4))
color = (125, 255, 125)
while True:
ret, frame = cap.read()
if not ret:
break
bboxes, _ = fd.inference(frame)
for pred in fa.get_landmarks(frame, bboxes):
for p in np.round(pred).astype(np.int):
cv2.circle(frame, tuple(p), 1, color, 1, cv2.LINE_AA)
face_center = np.mean(pred, axis=0)
euler_angle = hp.get_head_pose(pred).flatten()
print(*euler_angle)
hp.draw_axis(frame, euler_angle, face_center)
cv2.imshow("result", frame)
if cv2.waitKey(0) == ord('q'):
break
if __name__ == "__main__":
import sys
from SolvePnPHeadPoseEstimation import HeadPoseEstimator
from TFLiteFaceAlignment import CoordinateAlignmentModel
from TFLiteFaceDetector import UltraLightFaceDetecion
gpu_ctx = -1
video = sys.argv[1]
YAW_THD = 45
cap = cv2.VideoCapture(video)
fd = UltraLightFaceDetecion(
"pretrained/version-RFB-320_without_postprocessing.tflite",
conf_threshold=0.9)
fa = CoordinateAlignmentModel(
"pretrained/coor_2d106_face_alignment.tflite")
hp = HeadPoseEstimator("pretrained/head_pose_object_points.npy",
cap.get(3), cap.get(4))
gs = IrisLocalizationModel("pretrained/iris_localization.tflite")
counter = 0
while True:
ret, frame = cap.read()
if not ret:
break
# frame = frame[:480, 380:920, :] # dress
# frame = cv2.resize(frame, (960, 1080))
from TFLiteFaceAlignment import CoordinateAlignmentModel
from TFLiteIrisLocalization import IrisLocalizationModel
from SolvePnPHeadPoseEstimation import HeadPoseEstimator
from threading import Thread
import cv2
import sys
import numpy as np
from queue import Queue
import socketio
cap = cv2.VideoCapture(sys.argv[1])
fd = UltraLightFaceDetecion(
"pretrained/version-RFB-320_without_postprocessing.tflite",
conf_threshold=0.98)
fa = CoordinateAlignmentModel("pretrained/coor_2d106_face_alignment.tflite")
hp = HeadPoseEstimator("pretrained/head_pose_object_points.npy", cap.get(3),
cap.get(4))
gs = IrisLocalizationModel("pretrained/iris_localization.tflite")
QUEUE_BUFFER_SIZE = 18
box_queue = Queue(maxsize=QUEUE_BUFFER_SIZE)
landmark_queue = Queue(maxsize=QUEUE_BUFFER_SIZE)
iris_queue = Queue(maxsize=QUEUE_BUFFER_SIZE)
upstream_queue = Queue(maxsize=QUEUE_BUFFER_SIZE)
# ======================================================
sio = socketio.Client()
if __name__ == "__main__":
import sys
from SolvePnPHeadPoseEstimation import HeadPoseEstimator
from TFLiteFaceAlignment import CoordinateAlignmentModel
from TFLiteFaceDetector import UltraLightFaceDetecion
gpu_ctx = -1
video = sys.argv[1]
YAW_THD = 45
cap = cv2.VideoCapture(video)
fd = UltraLightFaceDetecion("weights/RFB-320.tflite", conf_threshold=0.9)
fa = CoordinateAlignmentModel("weights/coor_2d106.tflite")
hp = HeadPoseEstimator("weights/head_pose_object_points.npy", cap.get(3),
cap.get(4))
gs = IrisLocalizationModel("weights/iris_localization.tflite")
counter = 0
while True:
ret, frame = cap.read()
if not ret:
break
# frame = frame[:480, 380:920, :] # dress
# frame = cv2.resize(frame, (960, 1080))