Program not ending when the video is completed and no more images.

[davehardenatubihere]

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)