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go_pro_Stingray2_800x600.yaml
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#K:
#- [fx, 0, cx],
#- [0, fy, cy],
#- [0, 0, 1]])
K:
- [ 704.262404172678908, 0.0 , 403.525703941033044]
- [ 0.0 , 700.985126030791616, 295.719954850563636]
- [ 0.0 , 0.0 , 1.0 ]
D:
- [-0.279159318136002921, 0.123589235024440372, -0.000189443288522673765, 0.0000476664883196381510,
-0.0187031411930424600]
# Use these paths if using on an OSX system
osx_image_folder: '/Users/vik748/Google Drive/data/Stingray2_080718_800x600'
osx_masks_folder: '/Users/vik748/Google Drive/data/Stingray2_080718_800x600_masks_out'
osx_ground_truth_poses: '/Users/vik748/Google Drive/data/Multibeam_pointcloud_correction/Stingray2_080718/Stingray2_08072018_camera_poses_in_mts_20200422.txt'
# Use these paths if using on linux
linux_image_folder: '/home/vik748/data/Stingray2_080718_800x600'
linux_masks_folder: '/home/vik748/data/Stingray2_080718_800x600_masks_out'
linux_ground_truth_poses: '/home/vik748/data/Multibeam_pointcloud_correction/Stingray2_080718/Stingray2_08072018_camera_poses_in_mts_20200422.txt'
image_ext: 'png' # Extension of image files
use_masks: False # True if providing masks to mask out sections of images
masks_ext: 'png' # Extension of image masks
chessboard: False #
# Indexes of initial images. These should have good baseline separation to enable the algorithm to initialize well
init_image_indxs: [0, 20] #[1215, 1225]
# Step size between images. Since this algorithm does not have keyframe selection, we manually provide image separation for numerical stability
image_step: 10
plot_landmarks: True # Plot the landmarks in 3D plot (grey color)
display_candidates: True
lowe_ratio_test_threshold: 0.90
use_RecoverPose_Filter: False
pause_every_iteration: True
use_gtsam: True
gtsam_interval: 1
use_tiling_non_max_supression: False
tiling_non_max_tile_y: 4
tiling_non_max_tile_x: 3
radial_non_max: False
radial_non_max_radius: 5
use_clahe: False
CLAHE_settings:
clipLimit: 10.0
tileGridSize: !!python/tuple [8,6]
Triangulation_settings:
z_threshold: 400 # In units set by frame 1 and 2
subtended_angle_threshold: .00005 # In degrees
findEssential_settings:
prob: 0.9999
threshold: 0.002
solvePnPRansac_settings:
iterationsCount: 500
reprojectionError: 0.003 # Using normalized coordinates, this is 1/width * (error in pixels) so 1/800 * 2 rounded to 0.003
confidence: 0.9999
iSAM2_settings:
#pose0_to_pose1_range: 1.0
relinearizeThreshold: 0.1
relinearizeSkip: 5
proj_noise_val: 0.000125 # 1/800
feature_detector_type: zernike
feature_descriptor_type: zernike
ZERNIKE_settings:
Nfeats: 1200
seci: 4
secj: 3
levels: 6
ratio: 0.8334
sigi: 2.75
sigd: 1.0
nmax: 8
like_matlab: True
lmax_nd: 3
harris_threshold: 0.1
ORB_settings:
WTA_K: 2
edgeThreshold: 31
patchSize: 31
fastThreshold: 3
firstLevel: 0
nfeatures: 1200
nlevels: 6
scaleFactor: 1.2
scoreType: 0
SURF_settings:
hessianThreshold: 50
nOctaves: 6
SIFT_settings:
nfeatures: 1200
nOctaveLayers: 3
contrastThreshold: 0.01
edgeThreshold: 20
sigma: 1.6
#KLT_settings:
# criteria: !!python/tuple [3, 500, 0.001] #criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 50, 0.03))
# maxLevel: 4
# winSize: !!python/tuple [15,15]