1
2
3
4

git clone git@github.com:mapillary/OpenSfM.git
cd OpenSfM
git checkout v0.5.1
git submodule update --init --recursive

1
2
3

sudo apt-get install build-essential cmake libatlas-base-dev libatlas-base-dev libgoogle-glog-dev \
                     libopencv-dev libsuitesparse-dev python3-pip python3-dev  python3-numpy python3-opencv \
                     python3-pyproj python3-scipy python3-yaml libeigen3-dev

1
2
3
4
5

mkdir source && cd source/
git clone --recurse-submodules -j8 https://github.com/laurentkneip/opengv.git
cd opengv && mkdir build && cd build
cmake .. -DBUILD_TESTS=OFF -DBUILD_PYTHON=ON -DPYBIND11_PYTHON_VERSION=3.6 -DPYTHON_INSTALL_DIR=/usr/local/lib/python3.6/dist-packages/
sudo make install

1
2
3
4
5

cd ../../
curl -L http://ceres-solver.org/ceres-solver-1.14.0.tar.gz | tar xz
cd ./ceres-solver-1.14.0 && mkdir build-code && cd build-code
cmake .. -DCMAKE_C_FLAGS=-fPIC -DCMAKE_CXX_FLAGS=-fPIC -DBUILD_EXAMPLES=OFF -DBUILD_TESTING=OFF
sudo make -j4 install

1
2

cd ../../../ && pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
python3 setup.py build

1
2

bin/opensfm_run_all data/berlin
python3 -m http.server

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55

# 完整下载OpenSfM仓库（2317fbb），包括里面的pybind11等
git clone --recursive https://github.com/mapillary/OpenSfM opensfm
# 进入opensfm主目录
cd opensfm
git checkout v0.5.1
# 再次更新子模块保证最新
git submodule update --init --recursive
# 更新源
sudo apt-get update
# 安装依赖的包
sudo apt-get install -y \
    build-essential vim curl cmake git \
    libatlas-base-dev libeigen3-dev \
    libgoogle-glog-dev libopencv-dev libsuitesparse-dev \
    python3-dev python3-numpy python3-opencv python3-pip \
    python3-pyproj python3-scipy python3-yaml
# ---------编译安装ceres---------
# 创建临时目录
mkdir source && cd source
# 下载ceres v1.14并解压
curl -L http://ceres-solver.org/ceres-solver-1.14.0.tar.gz | tar xz
# 创建编译文件夹
cd ceres-solver-1.14.0 && mkdir build && cd build
# cmake
cmake .. -DCMAKE_C_FLAGS=-fPIC -DCMAKE_CXX_FLAGS=-fPIC -DBUILD_EXAMPLES=OFF -DBUILD_TESTING=OFF
# 开启48线程编译安装
sudo make -j48 install
# ----------编译安装opengv-------
# 回到source文件夹下
cd ../../
# 下载opengv
git clone https://github.com/paulinus/opengv.git
# 更新子模块保证代码最新
cd opengv && git submodule update --init --recursive
# 创建编译文件夹
mkdir build && cd build
# cmake
cmake .. -DBUILD_TESTS=OFF \
         -DBUILD_PYTHON=ON \
         -DPYBIND11_PYTHON_VERSION=3.6 \
         -DPYTHON_INSTALL_DIR=/usr/local/lib/python3.6/dist-packages/
# 开启48线程编译安装
sudo make -j48 install
# 安装opensfm需要的python库
/usr/bin/pip3 install \
    exifread==2.1.2 gpxpy==1.1.2 networkx==1.11 \
    numpy pyproj==1.9.5.1 pytest==3.0.7 \
    python-dateutil==2.6.0 PyYAML==3.12 \
    scipy xmltodict==0.10.2 \
    loky repoze.lru
# ----------编译opensfm----------
/usr/bin/python3 setup.py build
# 安装特定版本的opencv-contrib，此时可用SIFT特征提取算法
/usr/bin/pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple opencv-contrib-python==3.4.2.16

1
2
3
4

git clone git@github.com:mapillary/OpenSfM.git
cd OpenSfM
git checkout v0.5.1
git submodule update --init --recursive

1

docker build -t sfm:vvd .

1
2
3
4

> docker images
REPOSITORY                         TAG                       IMAGE ID       CREATED         SIZE
sfm                                vvd                       187a50a0777e   16 hours ago    1.84GB
...

1

docker run -it --name mysfm  sfm:vvd bash

1

bin/opensfm_run_all data/berlin

1

bin/opensfm_run_all data/customer

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30

project/
├── config.yaml
├── images/
   ├── image_filename
├── masks/
   ├── image_filename.png
├── gcp_list.txt
├── exif/
├── camera_models.json
├── features/
├── matches/
├── tracks.csv
├── reconstruction.json
├── reconstruction.meshed.json
└── undistorted/
    ├── images/
       ├── image_filename
    ├── masks/
       ├── image_filename.png
    ├── tracks.csv
    ├── reconstruction.json
    └── depthmaps/
        └── merged.ply
 └── stats/
    ├── stats.json
    ├── report.pdf
    ├── topview.png
    ├── matchgraph.png
    ├── heatmap_XXX.png
    ├── residuals_XXX.png

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43

reconstruction.json: [RECONSTRUCTION, ...]
RECONSTRUCTION: {
    "cameras": {
        CAMERA_ID: CAMERA,
        ...
    },
    "shots": {
        SHOT_ID: SHOT,
        ...
    },
    "points": {
        POINT_ID: POINT,
        ...
    }
}
CAMERA: {
    "projection_type": "perspective",  # Can be perspective, brown, fisheye or equirectangular
    "width": NUMBER,                   # Image width in pixels
    "height": NUMBER,                  # Image height in pixels
    # Depending on the projection type more parameters are stored.
    # These are the parameters of the perspective camera.
    "focal": NUMBER,                   # Estimated focal length
    "k1": NUMBER,                      # Estimated distortion coefficient
    "k2": NUMBER,                      # Estimated distortion coefficient
}
SHOT: {
    "camera": CAMERA_ID,
    "rotation": [X, Y, Z],      # Estimated rotation as an angle-axis vector
    "translation": [X, Y, Z],   # Estimated translation
    "gps_position": [X, Y, Z],  # GPS coordinates in the reconstruction reference frame
    "gps_dop": METERS,          # GPS accuracy in meters
    "orientation": NUMBER,      # EXIF orientation tag (can be 1, 3, 6 or 8)
    "capture_time": SECONDS     # Capture time as a UNIX timestamp
}
POINT: {
    "coordinates": [X, Y, Z],      # Estimated position of the point
    "color": [R, G, B],            # Color of the point
}

1
2
3
4
5
6
7
8
9

lab
├── config.yaml
└── images
    ├── DJI_1_0239.JPG
    ├── DJI_1_0240.JPG
    ├── DJI_1_0242.JPG
    └── DJI_1_0268.JPG
 1 directory, 5 files

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160

# Metadata
use_exif_size: yes
default_focal_prior: 0.85
 # Params for features
feature_type: HAHOG           # Feature type (AKAZE, SURF, SIFT, HAHOG, ORB)
feature_root: 1               # If 1, apply square root mapping to features
feature_min_frames: 4000      # If fewer frames are detected, sift_peak_threshold/surf_hessian_threshold is reduced.
feature_process_size: 2048    # Resize the image if its size is larger than specified. Set to -1 for original size
feature_use_adaptive_suppression: no
 # Params for SIFT
sift_peak_threshold: 0.1     # Smaller value -> more features
sift_edge_threshold: 10       # See OpenCV doc
 # Params for SURF
surf_hessian_threshold: 3000  # Smaller value -> more features
surf_n_octaves: 4             # See OpenCV doc
surf_n_octavelayers: 2        # See OpenCV doc
surf_upright: 0               # See OpenCV doc
 # Params for AKAZE (See details in lib/src/third_party/akaze/AKAZEConfig.h)
akaze_omax: 4                      # Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
akaze_dthreshold: 0.001            # Detector response threshold to accept point
akaze_descriptor: MSURF            # Feature type
akaze_descriptor_size: 0           # Size of the descriptor in bits. 0->Full size
akaze_descriptor_channels: 3       # Number of feature channels (1,2,3)
akaze_kcontrast_percentile: 0.7
akaze_use_isotropic_diffusion: no
 # Params for HAHOG
hahog_peak_threshold: 0.00001
hahog_edge_threshold: 10
hahog_normalize_to_uchar: yes
 # Params for general matching
lowes_ratio: 0.8              # Ratio test for matches
matcher_type: FLANN           # FLANN, BRUTEFORCE, or WORDS
symmetric_matching: yes       # Match symmetricly or one-way
 # Params for FLANN matching
flann_branching: 8           # See OpenCV doc
flann_iterations: 10          # See OpenCV doc
flann_checks: 20             # Smaller -> Faster (but might lose good matches)
 # Params for BoW matching
bow_file: bow_hahog_root_uchar_10000.npz
bow_words_to_match: 50        # Number of words to explore per feature.
bow_num_checks: 20            # Number of matching features to check.
bow_matcher_type: FLANN       # Matcher type to assign words to features
 # Params for VLAD matching
vlad_file: bow_hahog_root_uchar_64.npz
 # Params for matching
matching_gps_distance: 150            # Maximum gps distance between two images for matching
matching_gps_neighbors: 0             # Number of images to match selected by GPS distance. Set to 0 to use no limit (or disable if matching_gps_distance is also 0)
matching_time_neighbors: 0            # Number of images to match selected by time taken. Set to 0 to disable
matching_order_neighbors: 0           # Number of images to match selected by image name. Set to 0 to disable
matching_bow_neighbors: 0             # Number of images to match selected by BoW distance. Set to 0 to disable
matching_bow_gps_distance: 0          # Maximum GPS distance for preempting images before using selection by BoW distance. Set to 0 to disable
matching_bow_gps_neighbors: 0         # Number of images (selected by GPS distance) to preempt before using selection by BoW distance. Set to 0 to use no limit (or disable if matching_bow_gps_distance is also 0)
matching_bow_other_cameras: False     # If True, BoW image selection will use N neighbors from the same camera + N neighbors from any different camera.
matching_vlad_neighbors: 0            # Number of images to match selected by VLAD distance. Set to 0 to disable
matching_vlad_gps_distance: 0         # Maximum GPS distance for preempting images before using selection by VLAD distance. Set to 0 to disable
matching_vlad_gps_neighbors: 0        # Number of images (selected by GPS distance) to preempt before using selection by VLAD distance. Set to 0 to use no limit (or disable if matching_vlad_gps_distance is also 0)
matching_vlad_other_cameras: False    # If True, VLAD image selection will use N neighbors from the same camera + N neighbors from any different camera.
matching_use_filters: False           # If True, removes static matches using ad-hoc heuristics
 # Params for geometric estimation
robust_matching_threshold: 0.004        # Outlier threshold for fundamental matrix estimation as portion of image width
robust_matching_calib_threshold: 0.004  # Outlier threshold for essential matrix estimation during matching in radians
robust_matching_min_match: 20           # Minimum number of matches to accept matches between two images
five_point_algo_threshold: 0.004        # Outlier threshold for essential matrix estimation during incremental reconstruction in radians
five_point_algo_min_inliers: 20         # Minimum number of inliers for considering a two view reconstruction valid
five_point_refine_match_iterations: 10  # Number of LM iterations to run when refining relative pose during matching
five_point_refine_rec_iterations: 1000  # Number of LM iterations to run when refining relative pose during reconstruction
triangulation_threshold: 0.006          # Outlier threshold for accepting a triangulated point in radians
triangulation_min_ray_angle: 1.0        # Minimum angle between views to accept a triangulated point
triangulation_type: FULL                # Triangulation type : either considering all rays (FULL), or sing a RANSAC variant (ROBUST)
resection_threshold: 0.004              # Outlier threshold for resection in radians
resection_min_inliers: 10               # Minimum number of resection inliers to accept it
 # Params for track creation
min_track_length: 2             # Minimum number of features/images per track
 # Params for bundle adjustment
loss_function: SoftLOneLoss     # Loss function for the ceres problem (see: http://ceres-solver.org/modeling.html#lossfunction)
loss_function_threshold: 1      # Threshold on the squared residuals.  Usually cost is quadratic for smaller residuals and sub-quadratic above.
reprojection_error_sd: 0.004    # The standard deviation of the reprojection error
exif_focal_sd: 0.01             # The standard deviation of the exif focal length in log-scale
principal_point_sd: 0.01        # The standard deviation of the principal point coordinates
radial_distorsion_k1_sd: 0.01   # The standard deviation of the first radial distortion parameter
radial_distorsion_k2_sd: 0.01   # The standard deviation of the second radial distortion parameter
radial_distorsion_k3_sd: 0.01   # The standard deviation of the third radial distortion parameter
radial_distorsion_p1_sd: 0.01   # The standard deviation of the first tangential distortion parameter
radial_distorsion_p2_sd: 0.01   # The standard deviation of the second tangential distortion parameter
bundle_outlier_filtering_type: FIXED    # Type of threshold for filtering outlier : either fixed value (FIXED) or based on actual distribution (AUTO)
bundle_outlier_auto_ratio: 3.0          # For AUTO filtering type, projections with larger reprojection than ratio-times-mean, are removed
bundle_outlier_fixed_threshold: 0.006   # For FIXED filtering type, projections with larger reprojection error after bundle adjustment are removed
optimize_camera_parameters: yes         # Optimize internal camera parameters during bundle
bundle_max_iterations: 100      # Maximum optimizer iterations.
 retriangulation: yes                # Retriangulate all points from time to time
retriangulation_ratio: 1.2          # Retriangulate when the number of points grows by this ratio
bundle_interval: 999999             # Bundle after adding 'bundle_interval' cameras
bundle_new_points_ratio: 1.2        # Bundle when the number of points grows by this ratio
local_bundle_radius: 3              # Max image graph distance for images to be included in local bundle adjustment
local_bundle_min_common_points: 20  # Minimum number of common points betwenn images to be considered neighbors
local_bundle_max_shots: 30          # Max number of shots to optimize during local bundle adjustment
 save_partial_reconstructions: no    # Save reconstructions at every iteration
 # Params for GPS alignment
use_altitude_tag: no                  # Use or ignore EXIF altitude tag
align_method: orientation_prior       # orientation_prior or naive
align_orientation_prior: horizontal   # horizontal, vertical or no_roll
bundle_use_gps: yes                   # Enforce GPS position in bundle adjustment
bundle_use_gcp: no                    # Enforce Ground Control Point position in bundle adjustment
 # Params for navigation graph
nav_min_distance: 0.01                # Minimum distance for a possible edge between two nodes
nav_step_pref_distance: 6             # Preferred distance between camera centers
nav_step_max_distance: 20             # Maximum distance for a possible step edge between two nodes
nav_turn_max_distance: 15             # Maximum distance for a possible turn edge between two nodes
nav_step_forward_view_threshold: 15   # Maximum difference of angles in degrees between viewing directions for forward steps
nav_step_view_threshold: 30           # Maximum difference of angles in degrees between viewing directions for other steps
nav_step_drift_threshold: 36          # Maximum motion drift with respect to step directions for steps in degrees
nav_turn_view_threshold: 40           # Maximum difference of angles in degrees with respect to turn directions
nav_vertical_threshold: 20            # Maximum vertical angle difference in motion and viewing direction in degrees
nav_rotation_threshold: 30            # Maximum general rotation in degrees between cameras for steps
 # Params for image undistortion
undistorted_image_format: jpg         # Format in which to save the undistorted images
undistorted_image_max_size: 100000    # Max width and height of the undistorted image
 # Params for depth estimation
depthmap_method: PATCH_MATCH_SAMPLE   # Raw depthmap computation algorithm (PATCH_MATCH, BRUTE_FORCE, PATCH_MATCH_SAMPLE)
depthmap_resolution: 640              # Resolution of the depth maps
depthmap_num_neighbors: 10            # Number of neighboring views
depthmap_num_matching_views: 6        # Number of neighboring views used for each depthmaps
depthmap_min_depth: 0                 # Minimum depth in meters.  Set to 0 to auto-infer from the reconstruction.
depthmap_max_depth: 0                 # Maximum depth in meters.  Set to 0 to auto-infer from the reconstruction.
depthmap_patchmatch_iterations: 3     # Number of PatchMatch iterations to run
depthmap_patch_size: 7                # Size of the correlation patch
depthmap_min_patch_sd: 1.0            # Patches with lower standard deviation are ignored
depthmap_min_correlation_score: 0.1   # Minimum correlation score to accept a depth value
depthmap_same_depth_threshold: 0.01   # Threshold to measure depth closeness
depthmap_min_consistent_views: 3      # Min number of views that should reconstruct a point for it to be valid
depthmap_save_debug_files: no         # Save debug files with partial reconstruction results
 # Other params
processes: 1                  # Number of threads to use
 # Params for submodel split and merge
submodel_size: 80                                                    # Average number of images per submodel
submodel_overlap: 30.0                                               # Radius of the overlapping region between submodels
submodels_relpath: "submodels"                                       # Relative path to the submodels directory
submodel_relpath_template: "submodels/submodel_%04d"                 # Template to generate the relative path to a submodel directory
submodel_images_relpath_template: "submodels/submodel_%04d/images"   # Template to generate the relative path to a submodel images directory