def __init__(self, inputdirectory, feature = "ORB"):
self.input_directory = inputdirectory
# Use ORB features
self.detector = cv2.ORB_create()
self.bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
self.frame_generator = FrameGenerator(self.detector)
self.list_of_frames = []
self.map = Map()
self.three_dim_viewport = Display3D()
self.feature_mapper = {}
self.feature_history = {}
print("Map: %d points, %d frames" %
(len(self.mapp.points), len(self.mapp.frames)))
print("Time: %.2f ms" % ((time.time() - start_time) * 1000.0))
print(np.linalg.inv(f1.pose))
if __name__ == "__main__":
if len(sys.argv) < 2:
print("%s <video.mp4>" % sys.argv[0])
exit(-1)
disp2d, disp3d = None, None
if os.getenv("HEADLESS") is None:
disp3d = Display3D()
cap = cv2.VideoCapture(sys.argv[1])
# camera parameters
W = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
H = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
CNT = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
F = float(os.getenv("F", "525"))
if os.getenv("SEEK") is not None:
cap.set(cv2.CAP_PROP_POS_FRAMES, int(os.getenv("SEEK")))
if W > 1024:
downscale = 1024.0 / W
F *= downscale