jacklangerman commited on
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1 Parent(s): dd5adff
Files changed (7) hide show
  1. LICENSE.txt +13 -0
  2. README.md +15 -0
  3. hoho/__init__.py +23 -0
  4. hoho/color_mappings.py +182 -0
  5. hoho/hoho.py +0 -3
  6. hoho/read_write_colmap.py +489 -0
  7. hoho/viz3d.py +302 -0
LICENSE.txt ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Copyright 2024 Jack Langerman & Dmytro Mishkin
2
+
3
+ Licensed under the Apache License, Version 2.0 (the "License");
4
+ you may not use this file except in compliance with the License.
5
+ You may obtain a copy of the License at
6
+
7
+ http://www.apache.org/licenses/LICENSE-2.0
8
+
9
+ Unless required by applicable law or agreed to in writing, software
10
+ distributed under the License is distributed on an "AS IS" BASIS,
11
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12
+ See the License for the specific language governing permissions and
13
+ limitations under the License.
README.md ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # HoHo Tools
2
+
3
+
4
+ ```bash
5
+ # pip install over ssh
6
+ pip install git+ssh://git@hf.co/test-org-usm3d/tools.git
7
+
8
+ # pip install over http
9
+ pip install git+http://hf.co/test-org-usm3d/tools.git
10
+
11
+ # editable
12
+ git clone http://hf.co/test-org-usm3d/tools
13
+ cd tools
14
+ pip install -e .
15
+ ```
hoho/__init__.py CHANGED
@@ -1,2 +1,25 @@
1
  from .hoho import *
2
  from . import vis
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  from .hoho import *
2
  from . import vis
3
+ from . import read_write_colmap
4
+
5
+ import importlib
6
+ import sys
7
+ class LazyLoadModule:
8
+ def __init__(self, module_name):
9
+ self.module_name = module_name
10
+ self.module = None
11
+
12
+ def __getattribute__(self, attr):
13
+ if attr == 'module_name' or attr == 'module':
14
+ return super().__getattribute__(attr)
15
+
16
+ if self.module is None:
17
+ self.module = importlib.import_module(f'hoho.{self.module_name}')
18
+ sys.modules[self.module_name] = self.module
19
+
20
+ return getattr(self.module, attr)
21
+
22
+ print('hi')
23
+ vis = LazyLoadModule('vis')
24
+ viz3d = LazyLoadModule('viz3d')
25
+ print(viz3d)
hoho/color_mappings.py ADDED
@@ -0,0 +1,182 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ gestalt_color_mapping = {
2
+ "unclassified": (215, 62, 138),
3
+ "apex": (235, 88, 48),
4
+ "eave_end_point": (248, 130, 228),
5
+ "flashing_end_point": (71, 11, 161),
6
+ "ridge": (214, 251, 248),
7
+ "rake": (13, 94, 47),
8
+ "eave": (54, 243, 63),
9
+ "post": (187, 123, 236),
10
+ "ground_line": (136, 206, 14),
11
+ "flashing": (162, 162, 32),
12
+ "step_flashing": (169, 255, 219),
13
+ "hip": (8, 89, 52),
14
+ "valley": (85, 27, 65),
15
+ "roof": (215, 232, 179),
16
+ "door": (110, 52, 23),
17
+ "garage": (50, 233, 171),
18
+ "window": (230, 249, 40),
19
+ "shutter": (122, 4, 233),
20
+ "fascia": (95, 230, 240),
21
+ "soffit": (2, 102, 197),
22
+ "horizontal_siding": (131, 88, 59),
23
+ "vertical_siding": (110, 187, 198),
24
+ "brick": (171, 252, 7),
25
+ "concrete": (32, 47, 246),
26
+ "other_wall": (112, 61, 240),
27
+ "trim": (151, 206, 58),
28
+ "unknown": (127, 127, 127),
29
+ }
30
+
31
+ ade20k_color_mapping = {
32
+ 'wall': (120, 120, 120),
33
+ 'building;edifice': (180, 120, 120),
34
+ 'sky': (6, 230, 230),
35
+ 'floor;flooring': (80, 50, 50),
36
+ 'tree': (4, 200, 3),
37
+ 'ceiling': (120, 120, 80),
38
+ 'road;route': (140, 140, 140),
39
+ 'bed': (204, 5, 255),
40
+ 'windowpane;window': (230, 230, 230),
41
+ 'grass': (4, 250, 7),
42
+ 'cabinet': (224, 5, 255),
43
+ 'sidewalk;pavement': (235, 255, 7),
44
+ 'person;individual;someone;somebody;mortal;soul': (150, 5, 61),
45
+ 'earth;ground': (120, 120, 70),
46
+ 'door;double;door': (8, 255, 51),
47
+ 'table': (255, 6, 82),
48
+ 'mountain;mount': (143, 255, 140),
49
+ 'plant;flora;plant;life': (204, 255, 4),
50
+ 'curtain;drape;drapery;mantle;pall': (255, 51, 7),
51
+ 'chair': (204, 70, 3),
52
+ 'car;auto;automobile;machine;motorcar': (0, 102, 200),
53
+ 'water': (61, 230, 250),
54
+ 'painting;picture': (255, 6, 51),
55
+ 'sofa;couch;lounge': (11, 102, 255),
56
+ 'shelf': (255, 7, 71),
57
+ 'house': (255, 9, 224),
58
+ 'sea': (9, 7, 230),
59
+ 'mirror': (220, 220, 220),
60
+ 'rug;carpet;carpeting': (255, 9, 92),
61
+ 'field': (112, 9, 255),
62
+ 'armchair': (8, 255, 214),
63
+ 'seat': (7, 255, 224),
64
+ 'fence;fencing': (255, 184, 6),
65
+ 'desk': (10, 255, 71),
66
+ 'rock;stone': (255, 41, 10),
67
+ 'wardrobe;closet;press': (7, 255, 255),
68
+ 'lamp': (224, 255, 8),
69
+ 'bathtub;bathing;tub;bath;tub': (102, 8, 255),
70
+ 'railing;rail': (255, 61, 6),
71
+ 'cushion': (255, 194, 7),
72
+ 'base;pedestal;stand': (255, 122, 8),
73
+ 'box': (0, 255, 20),
74
+ 'column;pillar': (255, 8, 41),
75
+ 'signboard;sign': (255, 5, 153),
76
+ 'chest;of;drawers;chest;bureau;dresser': (6, 51, 255),
77
+ 'counter': (235, 12, 255),
78
+ 'sand': (160, 150, 20),
79
+ 'sink': (0, 163, 255),
80
+ 'skyscraper': (140, 140, 140),
81
+ 'fireplace;hearth;open;fireplace': (250, 10, 15),
82
+ 'refrigerator;icebox': (20, 255, 0),
83
+ 'grandstand;covered;stand': (31, 255, 0),
84
+ 'path': (255, 31, 0),
85
+ 'stairs;steps': (255, 224, 0),
86
+ 'runway': (153, 255, 0),
87
+ 'case;display;case;showcase;vitrine': (0, 0, 255),
88
+ 'pool;table;billiard;table;snooker;table': (255, 71, 0),
89
+ 'pillow': (0, 235, 255),
90
+ 'screen;door;screen': (0, 173, 255),
91
+ 'stairway;staircase': (31, 0, 255),
92
+ 'river': (11, 200, 200),
93
+ 'bridge;span': (255 ,82, 0),
94
+ 'bookcase': (0, 255, 245),
95
+ 'blind;screen': (0, 61, 255),
96
+ 'coffee;table;cocktail;table': (0, 255, 112),
97
+ 'toilet;can;commode;crapper;pot;potty;stool;throne': (0, 255, 133),
98
+ 'flower': (255, 0, 0),
99
+ 'book': (255, 163, 0),
100
+ 'hill': (255, 102, 0),
101
+ 'bench': (194, 255, 0),
102
+ 'countertop': (0, 143, 255),
103
+ 'stove;kitchen;stove;range;kitchen;range;cooking;stove': (51, 255, 0),
104
+ 'palm;palm;tree': (0, 82, 255),
105
+ 'kitchen;island': (0, 255, 41),
106
+ 'computer;computing;machine;computing;device;data;processor;electronic;computer;information;processing;system': (0, 255, 173),
107
+ 'swivel;chair': (10, 0, 255),
108
+ 'boat': (173, 255, 0),
109
+ 'bar': (0, 255, 153),
110
+ 'arcade;machine': (255, 92, 0),
111
+ 'hovel;hut;hutch;shack;shanty': (255, 0, 255),
112
+ 'bus;autobus;coach;charabanc;double-decker;jitney;motorbus;motorcoach;omnibus;passenger;vehicle': (255, 0, 245),
113
+ 'towel': (255, 0, 102),
114
+ 'light;light;source': (255, 173, 0),
115
+ 'truck;motortruck': (255, 0, 20),
116
+ 'tower': (255, 184, 184),
117
+ 'chandelier;pendant;pendent': (0, 31, 255),
118
+ 'awning;sunshade;sunblind': (0, 255, 61),
119
+ 'streetlight;street;lamp': (0, 71, 255),
120
+ 'booth;cubicle;stall;kiosk': (255, 0, 204),
121
+ 'television;television;receiver;television;set;tv;tv;set;idiot;box;boob;tube;telly;goggle;box': (0, 255, 194),
122
+ 'airplane;aeroplane;plane': (0, 255, 82),
123
+ 'dirt;track': (0, 10, 255),
124
+ 'apparel;wearing;apparel;dress;clothes': (0, 112, 255),
125
+ 'pole': (51, 0, 255),
126
+ 'land;ground;soil': (0, 194, 255),
127
+ 'bannister;banister;balustrade;balusters;handrail': (0, 122, 255),
128
+ 'escalator;moving;staircase;moving;stairway': (0, 255, 163),
129
+ 'ottoman;pouf;pouffe;puff;hassock': (255, 153, 0),
130
+ 'bottle': (0, 255, 10),
131
+ 'buffet;counter;sideboard': (255, 112, 0),
132
+ 'poster;posting;placard;notice;bill;card': (143, 255, 0),
133
+ 'stage': (82, 0, 255),
134
+ 'van': (163, 255, 0),
135
+ 'ship': (255, 235, 0),
136
+ 'fountain': (8, 184, 170),
137
+ 'conveyer;belt;conveyor;belt;conveyer;conveyor;transporter': (133, 0, 255),
138
+ 'canopy': (0, 255, 92),
139
+ 'washer;automatic;washer;washing;machine': (184, 0, 255),
140
+ 'plaything;toy': (255, 0, 31),
141
+ 'swimming;pool;swimming;bath;natatorium': (0, 184, 255),
142
+ 'stool': (0, 214, 255),
143
+ 'barrel;cask': (255, 0, 112),
144
+ 'basket;handbasket': (92, 255, 0),
145
+ 'waterfall;falls': (0, 224, 255),
146
+ 'tent;collapsible;shelter': (112, 224, 255),
147
+ 'bag': (70, 184, 160),
148
+ 'minibike;motorbike': (163, 0, 255),
149
+ 'cradle': (153, 0, 255),
150
+ 'oven': (71, 255, 0),
151
+ 'ball': (255, 0, 163),
152
+ 'food;solid;food': (255, 204, 0),
153
+ 'step;stair': (255, 0, 143),
154
+ 'tank;storage;tank': (0, 255, 235),
155
+ 'trade;name;brand;name;brand;marque': (133, 255, 0),
156
+ 'microwave;microwave;oven': (255, 0, 235),
157
+ 'pot;flowerpot': (245, 0, 255),
158
+ 'animal;animate;being;beast;brute;creature;fauna': (255, 0, 122),
159
+ 'bicycle;bike;wheel;cycle': (255, 245, 0),
160
+ 'lake': (10, 190, 212),
161
+ 'dishwasher;dish;washer;dishwashing;machine': (214, 255, 0),
162
+ 'screen;silver;screen;projection;screen': (0, 204, 255),
163
+ 'blanket;cover': (20, 0, 255),
164
+ 'sculpture': (255, 255, 0),
165
+ 'hood;exhaust;hood': (0, 153, 255),
166
+ 'sconce': (0, 41, 255),
167
+ 'vase': (0, 255, 204),
168
+ 'traffic;light;traffic;signal;stoplight': (41, 0, 255),
169
+ 'tray': (41, 255, 0),
170
+ 'ashcan;trash;can;garbage;can;wastebin;ash;bin;ash-bin;ashbin;dustbin;trash;barrel;trash;bin': (173, 0, 255),
171
+ 'fan': (0, 245, 255),
172
+ 'pier;wharf;wharfage;dock': (71, 0, 255),
173
+ 'crt;screen': (122, 0, 255),
174
+ 'plate': (0, 255, 184),
175
+ 'monitor;monitoring;device': (0, 92, 255),
176
+ 'bulletin;board;notice;board': (184, 255, 0),
177
+ 'shower': (0, 133, 255),
178
+ 'radiator': (255, 214, 0),
179
+ 'glass;drinking;glass': (25, 194, 194),
180
+ 'clock': (102, 255, 0),
181
+ 'flag': (92, 0, 255),
182
+ }
hoho/hoho.py CHANGED
@@ -156,9 +156,6 @@ def temp_working_directory():
156
 
157
  ############# Dataset #############
158
  def proc(row, split='train'):
159
- # column_names_train = ['ade20k', 'depthcm', 'gestalt', 'colmap', 'KRt', 'mesh', 'wireframe']
160
- # column_names_test = ['ade20k', 'depthcm', 'gestalt', 'colmap', 'KRt', 'wireframe']
161
- # cols = column_names_train if split == 'train' else column_names_test
162
  out = {}
163
  for k, v in row.items():
164
  colname = k.split('.')[0]
 
156
 
157
  ############# Dataset #############
158
  def proc(row, split='train'):
 
 
 
159
  out = {}
160
  for k, v in row.items():
161
  colname = k.split('.')[0]
hoho/read_write_colmap.py ADDED
@@ -0,0 +1,489 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Modified to read from bytes-like object by Dmytro Mishkin.
2
+ # The original license is below:
3
+ # Copyright (c) 2018, ETH Zurich and UNC Chapel Hill.
4
+ # All rights reserved.
5
+ #
6
+ # Redistribution and use in source and binary forms, with or without
7
+ # modification, are permitted provided that the following conditions are met:
8
+ #
9
+ # * Redistributions of source code must retain the above copyright
10
+ # notice, this list of conditions and the following disclaimer.
11
+ #
12
+ # * Redistributions in binary form must reproduce the above copyright
13
+ # notice, this list of conditions and the following disclaimer in the
14
+ # documentation and/or other materials provided with the distribution.
15
+ #
16
+ # * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
17
+ # its contributors may be used to endorse or promote products derived
18
+ # from this software without specific prior written permission.
19
+ #
20
+ # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
21
+ # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
22
+ # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
23
+ # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
24
+ # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
25
+ # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
26
+ # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
27
+ # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
28
+ # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
29
+ # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
30
+ # POSSIBILITY OF SUCH DAMAGE.
31
+ #
32
+ # Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)
33
+
34
+ import os
35
+ import collections
36
+ import numpy as np
37
+ import struct
38
+ import argparse
39
+
40
+
41
+ CameraModel = collections.namedtuple(
42
+ "CameraModel", ["model_id", "model_name", "num_params"])
43
+ Camera = collections.namedtuple(
44
+ "Camera", ["id", "model", "width", "height", "params"])
45
+ BaseImage = collections.namedtuple(
46
+ "Image", ["id", "qvec", "tvec", "camera_id", "name", "xys", "point3D_ids"])
47
+ Point3D = collections.namedtuple(
48
+ "Point3D", ["id", "xyz", "rgb", "error", "image_ids", "point2D_idxs"])
49
+
50
+
51
+ class Image(BaseImage):
52
+ def qvec2rotmat(self):
53
+ return qvec2rotmat(self.qvec)
54
+
55
+
56
+ CAMERA_MODELS = {
57
+ CameraModel(model_id=0, model_name="SIMPLE_PINHOLE", num_params=3),
58
+ CameraModel(model_id=1, model_name="PINHOLE", num_params=4),
59
+ CameraModel(model_id=2, model_name="SIMPLE_RADIAL", num_params=4),
60
+ CameraModel(model_id=3, model_name="RADIAL", num_params=5),
61
+ CameraModel(model_id=4, model_name="OPENCV", num_params=8),
62
+ CameraModel(model_id=5, model_name="OPENCV_FISHEYE", num_params=8),
63
+ CameraModel(model_id=6, model_name="FULL_OPENCV", num_params=12),
64
+ CameraModel(model_id=7, model_name="FOV", num_params=5),
65
+ CameraModel(model_id=8, model_name="SIMPLE_RADIAL_FISHEYE", num_params=4),
66
+ CameraModel(model_id=9, model_name="RADIAL_FISHEYE", num_params=5),
67
+ CameraModel(model_id=10, model_name="THIN_PRISM_FISHEYE", num_params=12)
68
+ }
69
+ CAMERA_MODEL_IDS = dict([(camera_model.model_id, camera_model)
70
+ for camera_model in CAMERA_MODELS])
71
+ CAMERA_MODEL_NAMES = dict([(camera_model.model_name, camera_model)
72
+ for camera_model in CAMERA_MODELS])
73
+
74
+
75
+ def read_next_bytes(fid, num_bytes, format_char_sequence, endian_character="<"):
76
+ """Read and unpack the next bytes from a binary file.
77
+ :param fid:
78
+ :param num_bytes: Sum of combination of {2, 4, 8}, e.g. 2, 6, 16, 30, etc.
79
+ :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}.
80
+ :param endian_character: Any of {@, =, <, >, !}
81
+ :return: Tuple of read and unpacked values.
82
+ """
83
+ data = fid.read(num_bytes)
84
+ return struct.unpack(endian_character + format_char_sequence, data)
85
+
86
+
87
+ def write_next_bytes(fid, data, format_char_sequence, endian_character="<"):
88
+ """pack and write to a binary file.
89
+ :param fid:
90
+ :param data: data to send, if multiple elements are sent at the same time,
91
+ they should be encapsuled either in a list or a tuple
92
+ :param format_char_sequence: List of {c, e, f, d, h, H, i, I, l, L, q, Q}.
93
+ should be the same length as the data list or tuple
94
+ :param endian_character: Any of {@, =, <, >, !}
95
+ """
96
+ if isinstance(data, (list, tuple)):
97
+ bytes = struct.pack(endian_character + format_char_sequence, *data)
98
+ else:
99
+ bytes = struct.pack(endian_character + format_char_sequence, data)
100
+ fid.write(bytes)
101
+
102
+
103
+ def read_cameras_text(path):
104
+ """
105
+ see: src/base/reconstruction.cc
106
+ void Reconstruction::WriteCamerasText(const std::string& path)
107
+ void Reconstruction::ReadCamerasText(const std::string& path)
108
+ """
109
+ cameras = {}
110
+ with open(path, "r") as fid:
111
+ while True:
112
+ line = fid.readline()
113
+ if not line:
114
+ break
115
+ line = line.strip()
116
+ if len(line) > 0 and line[0] != "#":
117
+ elems = line.split()
118
+ camera_id = int(elems[0])
119
+ model = elems[1]
120
+ width = int(elems[2])
121
+ height = int(elems[3])
122
+ params = np.array(tuple(map(float, elems[4:])))
123
+ cameras[camera_id] = Camera(id=camera_id, model=model,
124
+ width=width, height=height,
125
+ params=params)
126
+ return cameras
127
+
128
+
129
+ def read_cameras_binary(path_to_model_file=None, fid=None):
130
+ """
131
+ see: src/base/reconstruction.cc
132
+ void Reconstruction::WriteCamerasBinary(const std::string& path)
133
+ void Reconstruction::ReadCamerasBinary(const std::string& path)
134
+ """
135
+ cameras = {}
136
+ if fid is None:
137
+ fid = open(path_to_model_file, "rb")
138
+ num_cameras = read_next_bytes(fid, 8, "Q")[0]
139
+ for _ in range(num_cameras):
140
+ camera_properties = read_next_bytes(
141
+ fid, num_bytes=24, format_char_sequence="iiQQ")
142
+ camera_id = camera_properties[0]
143
+ model_id = camera_properties[1]
144
+ model_name = CAMERA_MODEL_IDS[camera_properties[1]].model_name
145
+ width = camera_properties[2]
146
+ height = camera_properties[3]
147
+ num_params = CAMERA_MODEL_IDS[model_id].num_params
148
+ params = read_next_bytes(fid, num_bytes=8*num_params,
149
+ format_char_sequence="d"*num_params)
150
+ cameras[camera_id] = Camera(id=camera_id,
151
+ model=model_name,
152
+ width=width,
153
+ height=height,
154
+ params=np.array(params))
155
+ assert len(cameras) == num_cameras
156
+ if path_to_model_file is not None:
157
+ fid.close()
158
+ return cameras
159
+
160
+
161
+ def write_cameras_text(cameras, path):
162
+ """
163
+ see: src/base/reconstruction.cc
164
+ void Reconstruction::WriteCamerasText(const std::string& path)
165
+ void Reconstruction::ReadCamerasText(const std::string& path)
166
+ """
167
+ HEADER = "# Camera list with one line of data per camera:\n" + \
168
+ "# CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]\n" + \
169
+ "# Number of cameras: {}\n".format(len(cameras))
170
+ with open(path, "w") as fid:
171
+ fid.write(HEADER)
172
+ for _, cam in cameras.items():
173
+ to_write = [cam.id, cam.model, cam.width, cam.height, *cam.params]
174
+ line = " ".join([str(elem) for elem in to_write])
175
+ fid.write(line + "\n")
176
+
177
+
178
+ def write_cameras_binary(cameras, path_to_model_file):
179
+ """
180
+ see: src/base/reconstruction.cc
181
+ void Reconstruction::WriteCamerasBinary(const std::string& path)
182
+ void Reconstruction::ReadCamerasBinary(const std::string& path)
183
+ """
184
+ with open(path_to_model_file, "wb") as fid:
185
+ write_next_bytes(fid, len(cameras), "Q")
186
+ for _, cam in cameras.items():
187
+ model_id = CAMERA_MODEL_NAMES[cam.model].model_id
188
+ camera_properties = [cam.id,
189
+ model_id,
190
+ cam.width,
191
+ cam.height]
192
+ write_next_bytes(fid, camera_properties, "iiQQ")
193
+ for p in cam.params:
194
+ write_next_bytes(fid, float(p), "d")
195
+ return cameras
196
+
197
+
198
+ def read_images_text(path):
199
+ """
200
+ see: src/base/reconstruction.cc
201
+ void Reconstruction::ReadImagesText(const std::string& path)
202
+ void Reconstruction::WriteImagesText(const std::string& path)
203
+ """
204
+ images = {}
205
+ with open(path, "r") as fid:
206
+ while True:
207
+ line = fid.readline()
208
+ if not line:
209
+ break
210
+ line = line.strip()
211
+ if len(line) > 0 and line[0] != "#":
212
+ elems = line.split()
213
+ image_id = int(elems[0])
214
+ qvec = np.array(tuple(map(float, elems[1:5])))
215
+ tvec = np.array(tuple(map(float, elems[5:8])))
216
+ camera_id = int(elems[8])
217
+ image_name = elems[9]
218
+ elems = fid.readline().split()
219
+ xys = np.column_stack([tuple(map(float, elems[0::3])),
220
+ tuple(map(float, elems[1::3]))])
221
+ point3D_ids = np.array(tuple(map(int, elems[2::3])))
222
+ images[image_id] = Image(
223
+ id=image_id, qvec=qvec, tvec=tvec,
224
+ camera_id=camera_id, name=image_name,
225
+ xys=xys, point3D_ids=point3D_ids)
226
+ return images
227
+
228
+
229
+ def read_images_binary(path_to_model_file=None, fid=None):
230
+ """
231
+ see: src/base/reconstruction.cc
232
+ void Reconstruction::ReadImagesBinary(const std::string& path)
233
+ void Reconstruction::WriteImagesBinary(const std::string& path)
234
+ """
235
+ images = {}
236
+ if fid is None:
237
+ fid = open(path_to_model_file, "rb")
238
+ num_reg_images = read_next_bytes(fid, 8, "Q")[0]
239
+ for _ in range(num_reg_images):
240
+ binary_image_properties = read_next_bytes(
241
+ fid, num_bytes=64, format_char_sequence="idddddddi")
242
+ image_id = binary_image_properties[0]
243
+ qvec = np.array(binary_image_properties[1:5])
244
+ tvec = np.array(binary_image_properties[5:8])
245
+ camera_id = binary_image_properties[8]
246
+ image_name = ""
247
+ current_char = read_next_bytes(fid, 1, "c")[0]
248
+ while current_char != b"\x00": # look for the ASCII 0 entry
249
+ image_name += current_char.decode("utf-8")
250
+ current_char = read_next_bytes(fid, 1, "c")[0]
251
+ num_points2D = read_next_bytes(fid, num_bytes=8,
252
+ format_char_sequence="Q")[0]
253
+ x_y_id_s = read_next_bytes(fid, num_bytes=24*num_points2D,
254
+ format_char_sequence="ddq"*num_points2D)
255
+ xys = np.column_stack([tuple(map(float, x_y_id_s[0::3])),
256
+ tuple(map(float, x_y_id_s[1::3]))])
257
+ point3D_ids = np.array(tuple(map(int, x_y_id_s[2::3])))
258
+ images[image_id] = Image(
259
+ id=image_id, qvec=qvec, tvec=tvec,
260
+ camera_id=camera_id, name=image_name,
261
+ xys=xys, point3D_ids=point3D_ids)
262
+ if path_to_model_file is not None:
263
+ fid.close()
264
+ return images
265
+
266
+
267
+ def write_images_text(images, path):
268
+ """
269
+ see: src/base/reconstruction.cc
270
+ void Reconstruction::ReadImagesText(const std::string& path)
271
+ void Reconstruction::WriteImagesText(const std::string& path)
272
+ """
273
+ if len(images) == 0:
274
+ mean_observations = 0
275
+ else:
276
+ mean_observations = sum((len(img.point3D_ids) for _, img in images.items()))/len(images)
277
+ HEADER = "# Image list with two lines of data per image:\n" + \
278
+ "# IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME\n" + \
279
+ "# POINTS2D[] as (X, Y, POINT3D_ID)\n" + \
280
+ "# Number of images: {}, mean observations per image: {}\n".format(len(images), mean_observations)
281
+
282
+ with open(path, "w") as fid:
283
+ fid.write(HEADER)
284
+ for _, img in images.items():
285
+ image_header = [img.id, *img.qvec, *img.tvec, img.camera_id, img.name]
286
+ first_line = " ".join(map(str, image_header))
287
+ fid.write(first_line + "\n")
288
+
289
+ points_strings = []
290
+ for xy, point3D_id in zip(img.xys, img.point3D_ids):
291
+ points_strings.append(" ".join(map(str, [*xy, point3D_id])))
292
+ fid.write(" ".join(points_strings) + "\n")
293
+
294
+
295
+ def write_images_binary(images, path_to_model_file):
296
+ """
297
+ see: src/base/reconstruction.cc
298
+ void Reconstruction::ReadImagesBinary(const std::string& path)
299
+ void Reconstruction::WriteImagesBinary(const std::string& path)
300
+ """
301
+ with open(path_to_model_file, "wb") as fid:
302
+ write_next_bytes(fid, len(images), "Q")
303
+ for _, img in images.items():
304
+ write_next_bytes(fid, img.id, "i")
305
+ write_next_bytes(fid, img.qvec.tolist(), "dddd")
306
+ write_next_bytes(fid, img.tvec.tolist(), "ddd")
307
+ write_next_bytes(fid, img.camera_id, "i")
308
+ for char in img.name:
309
+ write_next_bytes(fid, char.encode("utf-8"), "c")
310
+ write_next_bytes(fid, b"\x00", "c")
311
+ write_next_bytes(fid, len(img.point3D_ids), "Q")
312
+ for xy, p3d_id in zip(img.xys, img.point3D_ids):
313
+ write_next_bytes(fid, [*xy, p3d_id], "ddq")
314
+
315
+
316
+ def read_points3D_text(path):
317
+ """
318
+ see: src/base/reconstruction.cc
319
+ void Reconstruction::ReadPoints3DText(const std::string& path)
320
+ void Reconstruction::WritePoints3DText(const std::string& path)
321
+ """
322
+ points3D = {}
323
+ with open(path, "r") as fid:
324
+ while True:
325
+ line = fid.readline()
326
+ if not line:
327
+ break
328
+ line = line.strip()
329
+ if len(line) > 0 and line[0] != "#":
330
+ elems = line.split()
331
+ point3D_id = int(elems[0])
332
+ xyz = np.array(tuple(map(float, elems[1:4])))
333
+ rgb = np.array(tuple(map(int, elems[4:7])))
334
+ error = float(elems[7])
335
+ image_ids = np.array(tuple(map(int, elems[8::2])))
336
+ point2D_idxs = np.array(tuple(map(int, elems[9::2])))
337
+ points3D[point3D_id] = Point3D(id=point3D_id, xyz=xyz, rgb=rgb,
338
+ error=error, image_ids=image_ids,
339
+ point2D_idxs=point2D_idxs)
340
+ return points3D
341
+
342
+
343
+ def read_points3D_binary(path_to_model_file=None, fid=None):
344
+ """
345
+ see: src/base/reconstruction.cc
346
+ void Reconstruction::ReadPoints3DBinary(const std::string& path)
347
+ void Reconstruction::WritePoints3DBinary(const std::string& path)
348
+ """
349
+ points3D = {}
350
+ if fid is None:
351
+ fid = open(path_to_model_file, "rb")
352
+ num_points = read_next_bytes(fid, 8, "Q")[0]
353
+ for _ in range(num_points):
354
+ binary_point_line_properties = read_next_bytes(
355
+ fid, num_bytes=43, format_char_sequence="QdddBBBd")
356
+ point3D_id = binary_point_line_properties[0]
357
+ xyz = np.array(binary_point_line_properties[1:4])
358
+ rgb = np.array(binary_point_line_properties[4:7])
359
+ error = np.array(binary_point_line_properties[7])
360
+ track_length = read_next_bytes(
361
+ fid, num_bytes=8, format_char_sequence="Q")[0]
362
+ track_elems = read_next_bytes(
363
+ fid, num_bytes=8*track_length,
364
+ format_char_sequence="ii"*track_length)
365
+ image_ids = np.array(tuple(map(int, track_elems[0::2])))
366
+ point2D_idxs = np.array(tuple(map(int, track_elems[1::2])))
367
+ points3D[point3D_id] = Point3D(
368
+ id=point3D_id, xyz=xyz, rgb=rgb,
369
+ error=error, image_ids=image_ids,
370
+ point2D_idxs=point2D_idxs)
371
+ if path_to_model_file is not None:
372
+ fid.close()
373
+ return points3D
374
+
375
+
376
+ def write_points3D_text(points3D, path):
377
+ """
378
+ see: src/base/reconstruction.cc
379
+ void Reconstruction::ReadPoints3DText(const std::string& path)
380
+ void Reconstruction::WritePoints3DText(const std::string& path)
381
+ """
382
+ if len(points3D) == 0:
383
+ mean_track_length = 0
384
+ else:
385
+ mean_track_length = sum((len(pt.image_ids) for _, pt in points3D.items()))/len(points3D)
386
+ HEADER = "# 3D point list with one line of data per point:\n" + \
387
+ "# POINT3D_ID, X, Y, Z, R, G, B, ERROR, TRACK[] as (IMAGE_ID, POINT2D_IDX)\n" + \
388
+ "# Number of points: {}, mean track length: {}\n".format(len(points3D), mean_track_length)
389
+
390
+ with open(path, "w") as fid:
391
+ fid.write(HEADER)
392
+ for _, pt in points3D.items():
393
+ point_header = [pt.id, *pt.xyz, *pt.rgb, pt.error]
394
+ fid.write(" ".join(map(str, point_header)) + " ")
395
+ track_strings = []
396
+ for image_id, point2D in zip(pt.image_ids, pt.point2D_idxs):
397
+ track_strings.append(" ".join(map(str, [image_id, point2D])))
398
+ fid.write(" ".join(track_strings) + "\n")
399
+
400
+
401
+ def write_points3D_binary(points3D, path_to_model_file):
402
+ """
403
+ see: src/base/reconstruction.cc
404
+ void Reconstruction::ReadPoints3DBinary(const std::string& path)
405
+ void Reconstruction::WritePoints3DBinary(const std::string& path)
406
+ """
407
+ with open(path_to_model_file, "wb") as fid:
408
+ write_next_bytes(fid, len(points3D), "Q")
409
+ for _, pt in points3D.items():
410
+ write_next_bytes(fid, pt.id, "Q")
411
+ write_next_bytes(fid, pt.xyz.tolist(), "ddd")
412
+ write_next_bytes(fid, pt.rgb.tolist(), "BBB")
413
+ write_next_bytes(fid, pt.error, "d")
414
+ track_length = pt.image_ids.shape[0]
415
+ write_next_bytes(fid, track_length, "Q")
416
+ for image_id, point2D_id in zip(pt.image_ids, pt.point2D_idxs):
417
+ write_next_bytes(fid, [image_id, point2D_id], "ii")
418
+
419
+
420
+ def detect_model_format(path, ext):
421
+ if os.path.isfile(os.path.join(path, "cameras" + ext)) and \
422
+ os.path.isfile(os.path.join(path, "images" + ext)) and \
423
+ os.path.isfile(os.path.join(path, "points3D" + ext)):
424
+ print("Detected model format: '" + ext + "'")
425
+ return True
426
+
427
+ return False
428
+
429
+
430
+ def read_model(path, ext=""):
431
+ # try to detect the extension automatically
432
+ if ext == "":
433
+ if detect_model_format(path, ".bin"):
434
+ ext = ".bin"
435
+ elif detect_model_format(path, ".txt"):
436
+ ext = ".txt"
437
+ else:
438
+ print("Provide model format: '.bin' or '.txt'")
439
+ return
440
+
441
+ if ext == ".txt":
442
+ cameras = read_cameras_text(os.path.join(path, "cameras" + ext))
443
+ images = read_images_text(os.path.join(path, "images" + ext))
444
+ points3D = read_points3D_text(os.path.join(path, "points3D") + ext)
445
+ else:
446
+ cameras = read_cameras_binary(os.path.join(path, "cameras" + ext))
447
+ images = read_images_binary(os.path.join(path, "images" + ext))
448
+ points3D = read_points3D_binary(os.path.join(path, "points3D") + ext)
449
+ return cameras, images, points3D
450
+
451
+
452
+ def write_model(cameras, images, points3D, path, ext=".bin"):
453
+ if ext == ".txt":
454
+ write_cameras_text(cameras, os.path.join(path, "cameras" + ext))
455
+ write_images_text(images, os.path.join(path, "images" + ext))
456
+ write_points3D_text(points3D, os.path.join(path, "points3D") + ext)
457
+ else:
458
+ write_cameras_binary(cameras, os.path.join(path, "cameras" + ext))
459
+ write_images_binary(images, os.path.join(path, "images" + ext))
460
+ write_points3D_binary(points3D, os.path.join(path, "points3D") + ext)
461
+ return cameras, images, points3D
462
+
463
+
464
+ def qvec2rotmat(qvec):
465
+ return np.array([
466
+ [1 - 2 * qvec[2]**2 - 2 * qvec[3]**2,
467
+ 2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3],
468
+ 2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2]],
469
+ [2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3],
470
+ 1 - 2 * qvec[1]**2 - 2 * qvec[3]**2,
471
+ 2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1]],
472
+ [2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2],
473
+ 2 * qvec[2] * qvec[3] + 2 * qvec[0] * qvec[1],
474
+ 1 - 2 * qvec[1]**2 - 2 * qvec[2]**2]])
475
+
476
+
477
+ def rotmat2qvec(R):
478
+ Rxx, Ryx, Rzx, Rxy, Ryy, Rzy, Rxz, Ryz, Rzz = R.flat
479
+ K = np.array([
480
+ [Rxx - Ryy - Rzz, 0, 0, 0],
481
+ [Ryx + Rxy, Ryy - Rxx - Rzz, 0, 0],
482
+ [Rzx + Rxz, Rzy + Ryz, Rzz - Rxx - Ryy, 0],
483
+ [Ryz - Rzy, Rzx - Rxz, Rxy - Ryx, Rxx + Ryy + Rzz]]) / 3.0
484
+ eigvals, eigvecs = np.linalg.eigh(K)
485
+ qvec = eigvecs[[3, 0, 1, 2], np.argmax(eigvals)]
486
+ if qvec[0] < 0:
487
+ qvec *= -1
488
+ return qvec
489
+
hoho/viz3d.py ADDED
@@ -0,0 +1,302 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ """
3
+ Copyright [2022] [Paul-Edouard Sarlin and Philipp Lindenberger]
4
+
5
+ Licensed under the Apache License, Version 2.0 (the "License");
6
+ you may not use this file except in compliance with the License.
7
+ You may obtain a copy of the License at
8
+
9
+ http://www.apache.org/licenses/LICENSE-2.0
10
+
11
+ Unless required by applicable law or agreed to in writing, software
12
+ distributed under the License is distributed on an "AS IS" BASIS,
13
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14
+ See the License for the specific language governing permissions and
15
+ limitations under the License.
16
+
17
+ 3D visualization based on plotly.
18
+ Works for a small number of points and cameras, might be slow otherwise.
19
+
20
+ 1) Initialize a figure with `init_figure`
21
+ 2) Add 3D points, camera frustums, or both as a pycolmap.Reconstruction
22
+
23
+ Written by Paul-Edouard Sarlin and Philipp Lindenberger.
24
+ """
25
+ # Slightly modified by Dmytro Mishkin
26
+
27
+ from typing import Optional
28
+ import numpy as np
29
+ import pycolmap
30
+ import plotly.graph_objects as go
31
+
32
+
33
+ ### Some helper functions for geometry
34
+ def qvec2rotmat(qvec):
35
+ return np.array([
36
+ [1 - 2 * qvec[2]**2 - 2 * qvec[3]**2,
37
+ 2 * qvec[1] * qvec[2] - 2 * qvec[0] * qvec[3],
38
+ 2 * qvec[3] * qvec[1] + 2 * qvec[0] * qvec[2]],
39
+ [2 * qvec[1] * qvec[2] + 2 * qvec[0] * qvec[3],
40
+ 1 - 2 * qvec[1]**2 - 2 * qvec[3]**2,
41
+ 2 * qvec[2] * qvec[3] - 2 * qvec[0] * qvec[1]],
42
+ [2 * qvec[3] * qvec[1] - 2 * qvec[0] * qvec[2],
43
+ 2 * qvec[2] * qvec[3] + 2 * qvec[0] * qvec[1],
44
+ 1 - 2 * qvec[1]**2 - 2 * qvec[2]**2]])
45
+
46
+
47
+ def to_homogeneous(points):
48
+ pad = np.ones((points.shape[:-1]+(1,)), dtype=points.dtype)
49
+ return np.concatenate([points, pad], axis=-1)
50
+
51
+ def t_to_proj_center(qvec, tvec):
52
+ Rr = qvec2rotmat(qvec)
53
+ tt = (-Rr.T) @ tvec
54
+ return tt
55
+
56
+ def calib(params):
57
+ out = np.eye(3)
58
+ if len(params) == 3:
59
+ out[0,0] = params[0]
60
+ out[1,1] = params[0]
61
+ out[0,2] = params[1]
62
+ out[1,2] = params[2]
63
+ else:
64
+ out[0,0] = params[0]
65
+ out[1,1] = params[1]
66
+ out[0,2] = params[2]
67
+ out[1,2] = params[3]
68
+ return out
69
+
70
+
71
+ ### Plotting functions
72
+
73
+ def init_figure(height: int = 800) -> go.Figure:
74
+ """Initialize a 3D figure."""
75
+ fig = go.Figure()
76
+ axes = dict(
77
+ visible=False,
78
+ showbackground=False,
79
+ showgrid=False,
80
+ showline=False,
81
+ showticklabels=True,
82
+ autorange=True,
83
+ )
84
+ fig.update_layout(
85
+ template="plotly_dark",
86
+ height=height,
87
+ scene_camera=dict(
88
+ eye=dict(x=0., y=-.1, z=-2),
89
+ up=dict(x=0, y=-1., z=0),
90
+ projection=dict(type="orthographic")),
91
+ scene=dict(
92
+ xaxis=axes,
93
+ yaxis=axes,
94
+ zaxis=axes,
95
+ aspectmode='data',
96
+ dragmode='orbit',
97
+ ),
98
+ margin=dict(l=0, r=0, b=0, t=0, pad=0),
99
+ legend=dict(
100
+ orientation="h",
101
+ yanchor="top",
102
+ y=0.99,
103
+ xanchor="left",
104
+ x=0.1
105
+ ),
106
+ )
107
+ return fig
108
+
109
+
110
+ def plot_lines_3d(
111
+ fig: go.Figure,
112
+ pts: np.ndarray,
113
+ color: str = 'rgba(255, 255, 255, 1)',
114
+ ps: int = 2,
115
+ colorscale: Optional[str] = None,
116
+ name: Optional[str] = None):
117
+ """Plot a set of 3D points."""
118
+ x = pts[..., 0]
119
+ y = pts[..., 1]
120
+ z = pts[..., 2]
121
+ traces = [go.Scatter3d(x=x1, y=y1, z=z1,
122
+ mode='lines',
123
+ line=dict(color=color, width=2)) for x1, y1, z1 in zip(x,y,z)]
124
+ for t in traces:
125
+ fig.add_trace(t)
126
+ fig.update_traces(showlegend=False)
127
+
128
+
129
+ def plot_points(
130
+ fig: go.Figure,
131
+ pts: np.ndarray,
132
+ color: str = 'rgba(255, 0, 0, 1)',
133
+ ps: int = 2,
134
+ colorscale: Optional[str] = None,
135
+ name: Optional[str] = None):
136
+ """Plot a set of 3D points."""
137
+ x, y, z = pts.T
138
+ tr = go.Scatter3d(
139
+ x=x, y=y, z=z, mode='markers', name=name, legendgroup=name,
140
+ marker=dict(
141
+ size=ps, color=color, line_width=0.0, colorscale=colorscale))
142
+ fig.add_trace(tr)
143
+
144
+ def plot_camera(
145
+ fig: go.Figure,
146
+ R: np.ndarray,
147
+ t: np.ndarray,
148
+ K: np.ndarray,
149
+ color: str = 'rgb(0, 0, 255)',
150
+ name: Optional[str] = None,
151
+ legendgroup: Optional[str] = None,
152
+ size: float = 1.0):
153
+ """Plot a camera frustum from pose and intrinsic matrix."""
154
+ W, H = K[0, 2]*2, K[1, 2]*2
155
+ corners = np.array([[0, 0], [W, 0], [W, H], [0, H], [0, 0]])
156
+ if size is not None:
157
+ image_extent = max(size * W / 1024.0, size * H / 1024.0)
158
+ world_extent = max(W, H) / (K[0, 0] + K[1, 1]) / 0.5
159
+ scale = 0.5 * image_extent / world_extent
160
+ else:
161
+ scale = 1.0
162
+ corners = to_homogeneous(corners) @ np.linalg.inv(K).T
163
+ corners = (corners / 2 * scale) @ R.T + t
164
+
165
+ x, y, z = corners.T
166
+ rect = go.Scatter3d(
167
+ x=x, y=y, z=z, line=dict(color=color), legendgroup=legendgroup,
168
+ name=name, marker=dict(size=0.0001), showlegend=False)
169
+ fig.add_trace(rect)
170
+
171
+ x, y, z = np.concatenate(([t], corners)).T
172
+ i = [0, 0, 0, 0]
173
+ j = [1, 2, 3, 4]
174
+ k = [2, 3, 4, 1]
175
+
176
+ pyramid = go.Mesh3d(
177
+ x=x, y=y, z=z, color=color, i=i, j=j, k=k,
178
+ legendgroup=legendgroup, name=name, showlegend=False)
179
+ fig.add_trace(pyramid)
180
+ triangles = np.vstack((i, j, k)).T
181
+ vertices = np.concatenate(([t], corners))
182
+ tri_points = np.array([
183
+ vertices[i] for i in triangles.reshape(-1)
184
+ ])
185
+
186
+ x, y, z = tri_points.T
187
+ pyramid = go.Scatter3d(
188
+ x=x, y=y, z=z, mode='lines', legendgroup=legendgroup,
189
+ name=name, line=dict(color=color, width=1), showlegend=False)
190
+ fig.add_trace(pyramid)
191
+
192
+
193
+ def plot_camera_colmap(
194
+ fig: go.Figure,
195
+ image: pycolmap.Image,
196
+ camera: pycolmap.Camera,
197
+ name: Optional[str] = None,
198
+ **kwargs):
199
+ """Plot a camera frustum from PyCOLMAP objects"""
200
+ intr = calib(camera.params)
201
+ if intr[0][0] > 10000:
202
+ print("Bad camera")
203
+ return
204
+ plot_camera(
205
+ fig,
206
+ qvec2rotmat(image.qvec).T,
207
+ t_to_proj_center(image.qvec, image.tvec),
208
+ intr,#calibration_matrix(),
209
+ name=name or str(image.id),
210
+ **kwargs)
211
+
212
+
213
+ def plot_cameras(
214
+ fig: go.Figure,
215
+ reconstruction,#: pycolmap.Reconstruction,
216
+ **kwargs):
217
+ """Plot a camera as a cone with camera frustum."""
218
+ for image_id, image in reconstruction["images"].items():
219
+ plot_camera_colmap(
220
+ fig, image, reconstruction["cameras"][image.camera_id], **kwargs)
221
+
222
+
223
+ def plot_reconstruction(
224
+ fig: go.Figure,
225
+ rec,
226
+ color: str = 'rgb(0, 0, 255)',
227
+ name: Optional[str] = None,
228
+ points: bool = True,
229
+ cameras: bool = True,
230
+ cs: float = 1.0,
231
+ single_color_points=False,
232
+ camera_color='rgba(0, 255, 0, 0.5)'):
233
+ # rec is result of loading reconstruction from "read_write_colmap.py"
234
+ # Filter outliers
235
+ xyzs = []
236
+ rgbs = []
237
+ for k, p3D in rec['points'].items():
238
+ xyzs.append(p3D.xyz)
239
+ rgbs.append(p3D.rgb)
240
+
241
+ if points:
242
+ plot_points(fig, np.array(xyzs), color=color if single_color_points else np.array(rgbs), ps=1, name=name)
243
+ if cameras:
244
+ plot_cameras(fig, rec, color=camera_color, legendgroup=name, size=cs)
245
+
246
+
247
+ def plot_pointcloud(
248
+ fig: go.Figure,
249
+ pts: np.ndarray,
250
+ colors: np.ndarray,
251
+ ps: int = 2,
252
+ name: Optional[str] = None):
253
+ """Plot a set of 3D points."""
254
+ plot_points(fig, np.array(pts), color=colors, ps=ps, name=name)
255
+
256
+
257
+ def plot_triangle_mesh(
258
+ fig: go.Figure,
259
+ vert: np.ndarray,
260
+ colors: np.ndarray,
261
+ triangles: np.ndarray,
262
+ name: Optional[str] = None):
263
+ """Plot a triangle mesh."""
264
+ tr = go.Mesh3d(
265
+ x=vert[:,0],
266
+ y=vert[:,1],
267
+ z=vert[:,2],
268
+ vertexcolor = np.clip(255*colors, 0, 255),
269
+ # i, j and k give the vertices of triangles
270
+ # here we represent the 4 triangles of the tetrahedron surface
271
+ i=triangles[:,0],
272
+ j=triangles[:,1],
273
+ k=triangles[:,2],
274
+ name=name,
275
+ showscale=False
276
+ )
277
+ fig.add_trace(tr)
278
+
279
+ def plot_estimate_and_gt(pred_vertices, pred_connections, gt_vertices=None, gt_connections=None):
280
+ fig3d = init_figure()
281
+ c1 = (30, 20, 255)
282
+ img_color = [c1 for _ in range(len(pred_vertices))]
283
+ plot_points(fig3d, pred_vertices, color = img_color, ps = 10)
284
+ lines = []
285
+ for c in pred_connections:
286
+ v1 = pred_vertices[c[0]]
287
+ v2 = pred_vertices[c[1]]
288
+ lines.append(np.stack([v1, v2], axis=0))
289
+ plot_lines_3d(fig3d, np.array(lines), img_color, ps=4)
290
+ if gt_vertices is not None:
291
+ c2 = (30, 255, 20)
292
+ img_color2 = [c2 for _ in range(len(gt_vertices))]
293
+ plot_points(fig3d, gt_vertices, color = img_color2, ps = 10)
294
+ if gt_connections is not None:
295
+ gt_lines = []
296
+ for c in gt_connections:
297
+ v1 = gt_vertices[c[0]]
298
+ v2 = gt_vertices[c[1]]
299
+ gt_lines.append(np.stack([v1, v2], axis=0))
300
+ plot_lines_3d(fig3d, np.array(gt_lines), img_color2, ps=4)
301
+ fig3d.show()
302
+ return fig3d