Program not ending when the video is completed and no more images.
davehardenatubihere opened this issue · comments
I am running the Pyslam and with personal videos and the program is not shutting down when there are no more images in the dataset. I have attached the pyslam/main_slam file code below.
import numpy as np
import cv2
import math
import time
import platform
from config import Config
from slam import Slam, SlamState
from camera import PinholeCamera
from ground_truth import groundtruth_factory
from dataset import dataset_factory
from mplot3d import Mplot3d
from mplot2d import Mplot2d
from mplot_thread import Mplot2d, Mplot3d
if platform.system() == 'Linux':
from display2D import Display2D # !NOTE: pygame generate troubles under macOS!
from viewer3D import Viewer3D
from utils_sys import getchar, Printer
from feature_tracker import feature_tracker_factory, FeatureTrackerTypes
from feature_manager import feature_manager_factory
from feature_types import FeatureDetectorTypes, FeatureDescriptorTypes, FeatureInfo
from feature_matcher import feature_matcher_factory, FeatureMatcherTypes
from feature_tracker_configs import FeatureTrackerConfigs
from parameters import Parameters
import multiprocessing as mp
if name == "main":
config = Config()
dataset = dataset_factory(config.dataset_settings)
# groundtruth = groundtruth_factory(config.dataset_settings)
groundtruth = None # not actually used by Slam() class; could be used for evaluating performances
cam = PinholeCamera(config.cam_settings['Camera.width'], config.cam_settings['Camera.height'],
config.cam_settings['Camera.fx'], config.cam_settings['Camera.fy'],
config.cam_settings['Camera.cx'], config.cam_settings['Camera.cy'],
config.DistCoef, config.cam_settings['Camera.fps'])
num_features = 2000
tracker_type = FeatureTrackerTypes.DES_BF # descriptor-based, brute force matching with knn
# tracker_type = FeatureTrackerTypes.DES_FLANN # descriptor-based, FLANN-based matching
# select your tracker configuration (see the file feature_tracker_configs.py)
# FeatureTrackerConfigs: SHI_TOMASI_ORB, FAST_ORB, ORB, ORB2, ORB2_FREAK, ORB2_BEBLID, BRISK, AKAZE, FAST_FREAK, SIFT, ROOT_SIFT, SURF, SUPERPOINT, FAST_TFEAT, CONTEXTDESC
tracker_config = FeatureTrackerConfigs.TEST
tracker_config['num_features'] = num_features
tracker_config['tracker_type'] = tracker_type
print('tracker_config: ', tracker_config)
feature_tracker = feature_tracker_factory(**tracker_config)
# create SLAM object
slam = Slam(cam, feature_tracker, groundtruth)
time.sleep(1) # to show initial messages
viewer3D = Viewer3D()
if platform.system() == 'Linux':
display2d = Display2D(cam.width, cam.height) # pygame interface
else:
display2d = None # enable this if you want to use opencv window
matched_points_plt = Mplot2d(xlabel='img id', ylabel='# matches', title='# matches')
do_step = False
is_paused = False
img_id = 0 # 180, 340, 400 # you can start from a desired frame id if needed
while dataset.isOk():
if not is_paused:
print('..................................')
print('image: ', img_id)
img = dataset.getImageColor(img_id)
if img is None:
print('image is empty, exiting. . .')
getchar()
slam.quit()
exit()
timestamp = dataset.getTimestamp() # get current timestamp
next_timestamp = dataset.getNextTimestamp() # get next timestamp
frame_duration = next_timestamp - timestamp
if img is not None:
time_start = time.time()
slam.track(img, img_id, timestamp) # main SLAM function
# 3D display (map display)
if viewer3D is not None:
viewer3D.draw_map(slam)
img_draw = slam.map.draw_feature_trails(img)
# 2D display (image display)
if display2d is not None:
display2d.draw(img_draw)
else:
slam.map.save_map()
slam.quit()
cv2.destroyAllWindows()
exit()
img_id += 1
else:
time.sleep(1)
if matched_points_plt is not None:
if slam.tracking.num_matched_kps is not None:
matched_kps_signal = [img_id, slam.tracking.num_matched_kps]
matched_points_plt.draw(matched_kps_signal, '# keypoint matches', color='r')
if slam.tracking.num_inliers is not None:
inliers_signal = [img_id, slam.tracking.num_inliers]
matched_points_plt.draw(inliers_signal, '# inliers', color='g')
if slam.tracking.num_matched_map_points is not None:
valid_matched_map_points_signal = [img_id,
slam.tracking.num_matched_map_points] # valid matched map points (in current pose optimization)
matched_points_plt.draw(valid_matched_map_points_signal, '# matched map pts', color='b')
if slam.tracking.num_kf_ref_tracked_points is not None:
kf_ref_tracked_points_signal = [img_id, slam.tracking.num_kf_ref_tracked_points]
matched_points_plt.draw(kf_ref_tracked_points_signal, '# $KF_{ref}$ tracked pts', color='c')
if slam.tracking.descriptor_distance_sigma is not None:
descriptor_sigma_signal = [img_id, slam.tracking.descriptor_distance_sigma]
matched_points_plt.draw(descriptor_sigma_signal, 'descriptor distance $\sigma_{th}$', color='k')
matched_points_plt.refresh()
duration = time.time() - time_start
if (frame_duration > duration):
print('sleeping for frame')
time.sleep(frame_duration - duration)
else:
slam.map.save_map()
slam.quit()
cv2.destroyAllWindows()
img_id += 1
else:
time.sleep(1)
# get keys
key = matched_points_plt.get_key()
key_cv = cv2.waitKey(1) & 0xFF
# manage interface infos
if key == 'Esc' or key_cv == 27: # 'Esc' key
slam.map.save_map()
viewer3D.quit()
cv2.destroyAllWindows()
slam.quit()
exit()
if slam.tracking.state == SlamState.LOST:
if display2d is not None:
getchar()
else:
key_cv = cv2.waitKey(0) & 0xFF # useful when drawing stuff for debugging
if do_step and img_id > 1:
# stop at each frame
if display2d is not None:
getchar()
else:
key_cv = cv2.waitKey(0) & 0xFF
if key == 'd' or (key_cv == ord('d')):
do_step = not do_step
Printer.green('do step: ', do_step)
if key == 'q' or (key_cv == ord('q')):
if display2d is not None:
display2d.quit()
if viewer3D is not None:
viewer3D.quit()
if matched_points_plt is not None:
matched_points_plt.quit()
break
# if key == 'i':
# slam.map.save_map()
# viewer3D.quit()
# cv2.destroyAllWindows()
# slam.quit()
# exit()
# if viewer3D is not None:
# is_paused = not viewer3D.is_paused()
# slam.quit()
# cv2.destroyAllWindows()
# exit()
# cv2.waitKey(0)