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MisterMap
/
lie-pose-net
mirror of https://github.com/MisterMap/lie-pose-net

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  1. train-pose-net:
    2. 

  2.   cmd: python train.py --config configs/pose_net.yaml --out models/pose_net.pth --seed
    3. 

  3.     1 --gpu 1 --log_every_n_steps 1
    4. 

  4.   deps:
    5. 

  5.   - path: lieposenet
    6. 

  6.     md5: ceee33cedeed84daf9c06760e7c301b4.dir
    7. 

  7.     size: 102472
    8. 

  8.     nfiles: 47
    9. 

  9.   - path: train.py
    10. 

  10.     md5: ceb05b50de7c71946a909cc44dc939aa
    11. 

  11.     size: 1780
    12. 

  12.   params:
    13. 

  13.     configs/pose_net.yaml:
    14. 

  14.       data_module:
    15. 

  15.         batch_size: 32
    16. 

  16.         use_test: true
    17. 

  17.         num_workers: 4
    18. 

  18.       max_epochs: 15
    19. 

  19.       model:
    20. 

  20.         name: pose_net
    21. 

  21.         feature_extractor:
    22. 

  22.           name: resnet34
    23. 

  23.           pretrained: true
    24. 

  24.         criterion:
    25. 

  25.           name: se3
    26. 

  26.         feature_dimension: 2048
    27. 

  27.         drop_rate: 0.15
    28. 

  28.         optimizer:
    29. 

  29.           betas: 0.9 0.999
    30. 

  30.           lr: 0.0001
    31. 

  31.           weight_decay: 0.0005
    32. 

  32.         scheduler:
    33. 

  33.           step_size: 2
    34. 

  34.           gamma: 0.5
    35. 

  35.         bias: true
    36. 

  36.   outs:
    37. 

  37.   - path: models/pose_net.pth.ckpt
    38. 

  38.     md5: 38250b40f095515c11e68854b8f14ed8
    39. 

  39.     size: 268930751
    40. 

  40. test-pose-net:
    41. 

  41.   cmd: python eval.py --config configs/pose_net.yaml --model models/pose_net.pth.ckpt
    42. 

  42.     --seed 1 --gpu 1 --log_every_n_steps 1
    43. 

  43.   deps:
    44. 

  44.   - path: eval.py
    45. 

  45.     md5: 26b2f43da3a26164ef75e5cd753265da
    46. 

  46.     size: 2073
    47. 

  47.   - path: lieposenet
    48. 

  48.     md5: ceee33cedeed84daf9c06760e7c301b4.dir
    49. 

  49.     size: 102472
    50. 

  50.     nfiles: 47
    51. 

  51.   - path: models/pose_net.pth.ckpt
    52. 

  52.     md5: 38250b40f095515c11e68854b8f14ed8
    53. 

  53.     size: 268930751
    54. 

  54.   params:
    55. 

  55.     configs/pose_net.yaml:
    56. 

  56.       data_module:
    57. 

  57.         batch_size: 32
    58. 

  58.         use_test: true
    59. 

  59.         num_workers: 4
    60. 

  60.       model:
    61. 

  61.         name: pose_net
    62. 

  62.         feature_extractor:
    63. 

  63.           name: resnet34
    64. 

  64.           pretrained: true
    65. 

  65.         criterion:
    66. 

  66.           name: se3
    67. 

  67.         feature_dimension: 2048
    68. 

  68.         drop_rate: 0.15
    69. 

  69.         optimizer:
    70. 

  70.           betas: 0.9 0.999
    71. 

  71.           lr: 0.0001
    72. 

  72.           weight_decay: 0.0005
    73. 

  73.         scheduler:
    74. 

  74.           step_size: 2
    75. 

  75.           gamma: 0.5
    76. 

  76.         bias: true
    77. 

  77.   outs:
    78. 

  78.   - path: metrics.json
    79. 

  79.     md5: 6d065f44c9f94ff21e6f7921cbb93c5b
    80. 

  80.     size: 199
    81. 

  81.   - path: trajectories.npy
    82. 

  82.     md5: 74176dad648bfa49cebebc7204800e5e
    83. 

  83.     size: 336644
    84. 

  84. train-fire:
    85. 

  85.   cmd: python train.py --config configs/pose_net.yaml --dataset_name fire --out models/fire_pose_net.pth
    86. 

  86.     --seed 1 --gpu 1 --log_every_n_steps 1
    87. 

  87.   deps:
    88. 

  88.   - path: lieposenet
    89. 

  89.     md5: 228a3bc8cb2c60e2c8f639019ffb586e.dir
    90. 

  90.     size: 119819
    91. 

  91.     nfiles: 54
    92. 

  92.   - path: train.py
    93. 

  93.     md5: fb5134f26ef06de4bc0d4dc0de875864
    94. 

  94.     size: 1839
    95. 

  95.   params:
    96. 

  96.     configs/pose_net.yaml:
    97. 

  97.       data_module:
    98. 

  98.         batch_size: 32
    99. 

  99.         use_test: true
    100. 

  100.         num_workers: 4
    101. 

  101.         image_size: 256
    102. 

  102.       max_epochs: 300
    103. 

  103.       model:
    104. 

  104.         name: pose_net
    105. 

  105.         feature_extractor:
    106. 

  106.           name: resnet34
    107. 

  107.           pretrained: true
    108. 

  108.         criterion:
    109. 

  109.           name: se3
    110. 

  110.           rotation_koef: -3.0
    111. 

  111.           translation_koef: -3.0
    112. 

  112.         feature_dimension: 2048
    113. 

  113.         drop_rate: 0.15
    114. 

  114.         optimizer:
    115. 

  115.           betas: 0.9 0.999
    116. 

  116.           lr: 0.0001
    117. 

  117.           weight_decay: 0.0005
    118. 

  118.         scheduler:
    119. 

  119.           step_size: 20
    120. 

  120.           gamma: 0.5
    121. 

  121.         bias: true
    122. 

  122.         activation: relu
    123. 

  123.   outs:
    124. 

  124.   - path: models/fire_pose_net.pth.ckpt
    125. 

  125.     md5: ffa24d6be0e3bdbd9e87a56e42f8cb88
    126. 

  126.     size: 268932377
    127. 

  127. train-chess:
    128. 

  128.   cmd: python train.py --config configs/pose_net.yaml --dataset_name chess --out models/chess_pose_net.pth
    129. 

  129.     --seed 1 --gpu 1 --log_every_n_steps 1
    130. 

  130.   deps:
    131. 

  131.   - path: lieposenet
    132. 

  132.     md5: 5659fb263ee57d5ba8ce4dae29af91b3.dir
    133. 

  133.     size: 103849
    134. 

  134.     nfiles: 47
    135. 

  135.   - path: train.py
    136. 

  136.     md5: fb5134f26ef06de4bc0d4dc0de875864
    137. 

  137.     size: 1839
    138. 

  138.   params:
    139. 

  139.     configs/pose_net.yaml:
    140. 

  140.       data_module:
    141. 

  141.         batch_size: 32
    142. 

  142.         use_test: true
    143. 

  143.         num_workers: 4
    144. 

  144.       max_epochs: 15
    145. 

  145.       model:
    146. 

  146.         name: pose_net
    147. 

  147.         feature_extractor:
    148. 

  148.           name: resnet34
    149. 

  149.           pretrained: true
    150. 

  150.         criterion:
    151. 

  151.           name: se3
    152. 

  152.         feature_dimension: 2048
    153. 

  153.         drop_rate: 0.15
    154. 

  154.         optimizer:
    155. 

  155.           betas: 0.9 0.999
    156. 

  156.           lr: 0.0001
    157. 

  157.           weight_decay: 0.0005
    158. 

  158.         bias: true
    159. 

  159.   outs:
    160. 

  160.   - path: models/chess_pose_net.pth.ckpt
    161. 

  161.     md5: ab5330585ba5be0640d0fc04635c4deb
    162. 

  162.     size: 268931019
    163. 

  163. test-chess:
    164. 

  164.   cmd: python eval.py --config configs/pose_net.yaml --dataset_name chess --result
    165. 

  165.     metrics/chess_metrics.json --data_saver_path metrics/chess_trajectories.npy --model
    166. 

  166.     models/chess_pose_net.pth.ckpt --seed 1 --gpu 1 --log_every_n_steps 1
    167. 

  167.   deps:
    168. 

  168.   - path: eval.py
    169. 

  169.     md5: f4dae0d7273fb4ef256bda2228a1ae74
    170. 

  170.     size: 2095
    171. 

  171.   - path: lieposenet
    172. 

  172.     md5: 5659fb263ee57d5ba8ce4dae29af91b3.dir
    173. 

  173.     size: 103849
    174. 

  174.     nfiles: 47
    175. 

  175.   - path: models/chess_pose_net.pth.ckpt
    176. 

  176.     md5: ab5330585ba5be0640d0fc04635c4deb
    177. 

  177.     size: 268931019
    178. 

  178.   params:
    179. 

  179.     configs/pose_net.yaml:
    180. 

  180.       data_module:
    181. 

  181.         batch_size: 32
    182. 

  182.         use_test: true
    183. 

  183.         num_workers: 4
    184. 

  184.       model:
    185. 

  185.         name: pose_net
    186. 

  186.         feature_extractor:
    187. 

  187.           name: resnet34
    188. 

  188.           pretrained: true
    189. 

  189.         criterion:
    190. 

  190.           name: se3
    191. 

  191.         feature_dimension: 2048
    192. 

  192.         drop_rate: 0.15
    193. 

  193.         optimizer:
    194. 

  194.           betas: 0.9 0.999
    195. 

  195.           lr: 0.0001
    196. 

  196.           weight_decay: 0.0005
    197. 

  197.         bias: true
    198. 

  198.   outs:
    199. 

  199.   - path: metrics/chess_metrics.json
    200. 

  200.     md5: 887047ab9c9c3775abc41c38182ec4ac
    201. 

  201.     size: 199
    202. 

  202.   - path: metrics/chess_trajectories.npy
    203. 

  203.     md5: 5f3ce1fd12a32ba32be868d6de19f98b
    204. 

  204.     size: 752777
    205. 

  205. test-fire:
    206. 

  206.   cmd: python eval.py --config configs/pose_net.yaml --dataset_name fire --result
    207. 

  207.     metrics/fire_metrics.json --data_saver_path metrics/fire_trajectories.npy --model
    208. 

  208.     models/fire_pose_net.pth.ckpt --seed 1 --gpu 1 --log_every_n_steps 1
    209. 

  209.   deps:
    210. 

  210.   - path: eval.py
    211. 

  211.     md5: f4dae0d7273fb4ef256bda2228a1ae74
    212. 

  212.     size: 2095
    213. 

  213.   - path: lieposenet
    214. 

  214.     md5: 228a3bc8cb2c60e2c8f639019ffb586e.dir
    215. 

  215.     size: 119819
    216. 

  216.     nfiles: 54
    217. 

  217.   - path: models/fire_pose_net.pth.ckpt
    218. 

  218.     md5: ffa24d6be0e3bdbd9e87a56e42f8cb88
    219. 

  219.     size: 268932377
    220. 

  220.   params:
    221. 

  221.     configs/pose_net.yaml:
    222. 

  222.       data_module:
    223. 

  223.         batch_size: 32
    224. 

  224.         use_test: true
    225. 

  225.         num_workers: 4
    226. 

  226.         image_size: 256
    227. 

  227.       model:
    228. 

  228.         name: pose_net
    229. 

  229.         feature_extractor:
    230. 

  230.           name: resnet34
    231. 

  231.           pretrained: true
    232. 

  232.         criterion:
    233. 

  233.           name: se3
    234. 

  234.           rotation_koef: -3.0
    235. 

  235.           translation_koef: -3.0
    236. 

  236.         feature_dimension: 2048
    237. 

  237.         drop_rate: 0.15
    238. 

  238.         optimizer:
    239. 

  239.           betas: 0.9 0.999
    240. 

  240.           lr: 0.0001
    241. 

  241.           weight_decay: 0.0005
    242. 

  242.         scheduler:
    243. 

  243.           step_size: 20
    244. 

  244.           gamma: 0.5
    245. 

  245.         bias: true
    246. 

  246.         activation: relu
    247. 

  247.   outs:
    248. 

  248.   - path: metrics/fire_metrics.json
    249. 

  249.     md5: 9c530e1c7c61bd183d613deb96ea2bd9
    250. 

  250.     size: 199
    251. 

  251.   - path: metrics/fire_trajectories.npy
    252. 

  252.     md5: d1a719942ac6872a1a9405fbc97319f0
    253. 

  253.     size: 752777
    254.
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