log.txt 10 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216
  1. 2020-11-06 16:41:06 Config:
  2. {'all_joints': [[0],
  3. [1],
  4. [2],
  5. [3],
  6. [4],
  7. [5],
  8. [6],
  9. [7],
  10. [8],
  11. [9],
  12. [10],
  13. [11],
  14. [12],
  15. [13],
  16. [14],
  17. [15],
  18. [16],
  19. [17],
  20. [18]],
  21. 'all_joints_names': ['snout',
  22. 'neck',
  23. 'upper_back',
  24. 'middle_back',
  25. 'tailbase',
  26. 'shoulder_right',
  27. 'elbow_right',
  28. 'wrist_right',
  29. 'forepaw_right',
  30. 'forepaw_left',
  31. 'hip_right',
  32. 'knee_right',
  33. 'ankle_right',
  34. 'hindpaw_right',
  35. 'hindpaw_left',
  36. 'beam_left_top',
  37. 'beam_left_bottom',
  38. 'beam_right_top',
  39. 'beam_right_bottom'],
  40. 'batch_size': 1,
  41. 'bottomheight': 400,
  42. 'crop': True,
  43. 'crop_pad': 0,
  44. 'cropratio': 0.4,
  45. 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_RotatingBeam3.1Jul12/RotatingBeam3.1_Sebastian_Kloubert95shuffle5.mat',
  46. 'dataset_type': 'imgaug',
  47. 'deterministic': False,
  48. 'display_iters': 1000,
  49. 'fg_fraction': 0.25,
  50. 'global_scale': 0.8,
  51. 'init_weights': '/mnt/Install/DLC-GPU/lib/python3.7/site-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_50.ckpt',
  52. 'intermediate_supervision': False,
  53. 'intermediate_supervision_layer': 12,
  54. 'leftwidth': 400,
  55. 'location_refinement': True,
  56. 'locref_huber_loss': True,
  57. 'locref_loss_weight': 0.05,
  58. 'locref_stdev': 7.2801,
  59. 'log_dir': 'log',
  60. 'max_input_size': 1500,
  61. 'mean_pixel': [123.68, 116.779, 103.939],
  62. 'metadataset': 'training-datasets/iteration-0/UnaugmentedDataSet_RotatingBeam3.1Jul12/Documentation_data-RotatingBeam3.1_95shuffle5.pickle',
  63. 'min_input_size': 64,
  64. 'minsize': 100,
  65. 'mirror': False,
  66. 'multi_step': [[0.005, 10000],
  67. [0.02, 430000],
  68. [0.002, 730000],
  69. [0.001, 1030000]],
  70. 'net_type': 'resnet_50',
  71. 'num_joints': 19,
  72. 'optimizer': 'sgd',
  73. 'pairwise_huber_loss': False,
  74. 'pairwise_predict': False,
  75. 'partaffinityfield_predict': False,
  76. 'pos_dist_thresh': 17,
  77. 'project_path': '/mnt/DLC/RotatingBeam3.1-Sebastian_Kloubert-2020-07-12',
  78. 'regularize': False,
  79. 'rightwidth': 400,
  80. 'save_iters': 50000,
  81. 'scale_jitter_lo': 0.5,
  82. 'scale_jitter_up': 1.25,
  83. 'scoremap_dir': 'test',
  84. 'shuffle': True,
  85. 'snapshot_prefix': '/mnt/DLC/RotatingBeam3.1-Sebastian_Kloubert-2020-07-12/dlc-models/iteration-0/RotatingBeam3.1Jul12-trainset95shuffle5/train/snapshot',
  86. 'stride': 8.0,
  87. 'topheight': 400,
  88. 'weigh_negatives': False,
  89. 'weigh_only_present_joints': False,
  90. 'weigh_part_predictions': False,
  91. 'weight_decay': 0.0001}
  92. 2020-11-06 16:42:43 iteration: 1000 loss: 0.0269 lr: 0.005
  93. 2020-11-06 16:44:09 iteration: 2000 loss: 0.0131 lr: 0.005
  94. 2020-11-06 16:45:35 iteration: 3000 loss: 0.0104 lr: 0.005
  95. 2020-11-06 16:47:01 iteration: 4000 loss: 0.0093 lr: 0.005
  96. 2020-11-06 16:48:27 iteration: 5000 loss: 0.0085 lr: 0.005
  97. 2020-11-06 16:49:56 iteration: 6000 loss: 0.0080 lr: 0.005
  98. 2020-11-06 16:51:22 iteration: 7000 loss: 0.0074 lr: 0.005
  99. 2020-11-06 16:52:47 iteration: 8000 loss: 0.0071 lr: 0.005
  100. 2020-11-06 16:54:13 iteration: 9000 loss: 0.0070 lr: 0.005
  101. 2020-11-06 16:55:39 iteration: 10000 loss: 0.0066 lr: 0.005
  102. 2020-11-06 16:57:07 iteration: 11000 loss: 0.0081 lr: 0.02
  103. 2020-11-06 16:58:34 iteration: 12000 loss: 0.0070 lr: 0.02
  104. 2020-11-06 17:00:00 iteration: 13000 loss: 0.0068 lr: 0.02
  105. 2020-11-06 17:01:27 iteration: 14000 loss: 0.0059 lr: 0.02
  106. 2020-11-06 17:02:56 iteration: 15000 loss: 0.0056 lr: 0.02
  107. 2020-11-06 17:04:25 iteration: 16000 loss: 0.0057 lr: 0.02
  108. 2020-11-06 17:05:53 iteration: 17000 loss: 0.0053 lr: 0.02
  109. 2020-11-06 17:07:20 iteration: 18000 loss: 0.0052 lr: 0.02
  110. 2020-11-06 17:08:48 iteration: 19000 loss: 0.0049 lr: 0.02
  111. 2020-11-06 17:10:14 iteration: 20000 loss: 0.0048 lr: 0.02
  112. 2020-11-06 17:11:42 iteration: 21000 loss: 0.0047 lr: 0.02
  113. 2020-11-06 17:13:09 iteration: 22000 loss: 0.0046 lr: 0.02
  114. 2020-11-06 17:14:36 iteration: 23000 loss: 0.0045 lr: 0.02
  115. 2020-11-06 17:16:02 iteration: 24000 loss: 0.0046 lr: 0.02
  116. 2020-11-06 17:17:29 iteration: 25000 loss: 0.0044 lr: 0.02
  117. 2020-11-06 17:18:55 iteration: 26000 loss: 0.0043 lr: 0.02
  118. 2020-11-06 17:20:21 iteration: 27000 loss: 0.0043 lr: 0.02
  119. 2020-11-06 17:21:47 iteration: 28000 loss: 0.0044 lr: 0.02
  120. 2020-11-06 17:23:14 iteration: 29000 loss: 0.0041 lr: 0.02
  121. 2020-11-06 17:24:43 iteration: 30000 loss: 0.0042 lr: 0.02
  122. 2020-11-06 17:26:09 iteration: 31000 loss: 0.0041 lr: 0.02
  123. 2020-11-06 17:27:37 iteration: 32000 loss: 0.0039 lr: 0.02
  124. 2020-11-06 17:29:04 iteration: 33000 loss: 0.0040 lr: 0.02
  125. 2020-11-06 17:30:31 iteration: 34000 loss: 0.0039 lr: 0.02
  126. 2020-11-06 17:31:57 iteration: 35000 loss: 0.0039 lr: 0.02
  127. 2020-11-06 17:33:24 iteration: 36000 loss: 0.0039 lr: 0.02
  128. 2020-11-06 17:34:52 iteration: 37000 loss: 0.0039 lr: 0.02
  129. 2020-11-06 17:36:19 iteration: 38000 loss: 0.0037 lr: 0.02
  130. 2020-11-06 17:37:45 iteration: 39000 loss: 0.0037 lr: 0.02
  131. 2020-11-06 17:39:12 iteration: 40000 loss: 0.0038 lr: 0.02
  132. 2020-11-06 17:40:38 iteration: 41000 loss: 0.0037 lr: 0.02
  133. 2020-11-06 17:42:06 iteration: 42000 loss: 0.0037 lr: 0.02
  134. 2020-11-06 17:43:34 iteration: 43000 loss: 0.0035 lr: 0.02
  135. 2020-11-06 17:45:00 iteration: 44000 loss: 0.0035 lr: 0.02
  136. 2020-11-06 17:46:28 iteration: 45000 loss: 0.0035 lr: 0.02
  137. 2020-11-06 17:47:55 iteration: 46000 loss: 0.0034 lr: 0.02
  138. 2020-11-06 17:49:23 iteration: 47000 loss: 0.0034 lr: 0.02
  139. 2020-11-06 17:50:50 iteration: 48000 loss: 0.0035 lr: 0.02
  140. 2020-11-06 17:52:16 iteration: 49000 loss: 0.0034 lr: 0.02
  141. 2020-11-06 17:53:41 iteration: 50000 loss: 0.0033 lr: 0.02
  142. 2020-11-06 17:55:07 iteration: 51000 loss: 0.0033 lr: 0.02
  143. 2020-11-06 17:56:31 iteration: 52000 loss: 0.0032 lr: 0.02
  144. 2020-11-06 17:57:55 iteration: 53000 loss: 0.0032 lr: 0.02
  145. 2020-11-06 17:59:19 iteration: 54000 loss: 0.0032 lr: 0.02
  146. 2020-11-06 18:00:42 iteration: 55000 loss: 0.0032 lr: 0.02
  147. 2020-11-06 18:02:04 iteration: 56000 loss: 0.0032 lr: 0.02
  148. 2020-11-06 18:03:30 iteration: 57000 loss: 0.0032 lr: 0.02
  149. 2020-11-06 18:04:56 iteration: 58000 loss: 0.0030 lr: 0.02
  150. 2020-11-06 18:06:23 iteration: 59000 loss: 0.0030 lr: 0.02
  151. 2020-11-06 18:07:49 iteration: 60000 loss: 0.0031 lr: 0.02
  152. 2020-11-06 18:09:16 iteration: 61000 loss: 0.0031 lr: 0.02
  153. 2020-11-06 18:10:42 iteration: 62000 loss: 0.0030 lr: 0.02
  154. 2020-11-06 18:12:10 iteration: 63000 loss: 0.0030 lr: 0.02
  155. 2020-11-06 18:13:38 iteration: 64000 loss: 0.0030 lr: 0.02
  156. 2020-11-06 18:15:06 iteration: 65000 loss: 0.0030 lr: 0.02
  157. 2020-11-06 18:16:32 iteration: 66000 loss: 0.0029 lr: 0.02
  158. 2020-11-06 18:17:59 iteration: 67000 loss: 0.0030 lr: 0.02
  159. 2020-11-06 18:19:25 iteration: 68000 loss: 0.0029 lr: 0.02
  160. 2020-11-06 18:20:52 iteration: 69000 loss: 0.0029 lr: 0.02
  161. 2020-11-06 18:22:19 iteration: 70000 loss: 0.0028 lr: 0.02
  162. 2020-11-06 18:23:47 iteration: 71000 loss: 0.0028 lr: 0.02
  163. 2020-11-06 18:25:13 iteration: 72000 loss: 0.0028 lr: 0.02
  164. 2020-11-06 18:26:38 iteration: 73000 loss: 0.0028 lr: 0.02
  165. 2020-11-06 18:28:05 iteration: 74000 loss: 0.0029 lr: 0.02
  166. 2020-11-06 18:29:32 iteration: 75000 loss: 0.0028 lr: 0.02
  167. 2020-11-06 18:31:02 iteration: 76000 loss: 0.0028 lr: 0.02
  168. 2020-11-06 18:32:29 iteration: 77000 loss: 0.0028 lr: 0.02
  169. 2020-11-06 18:33:55 iteration: 78000 loss: 0.0028 lr: 0.02
  170. 2020-11-06 18:35:24 iteration: 79000 loss: 0.0027 lr: 0.02
  171. 2020-11-06 18:36:51 iteration: 80000 loss: 0.0027 lr: 0.02
  172. 2020-11-06 18:38:19 iteration: 81000 loss: 0.0028 lr: 0.02
  173. 2020-11-06 18:39:45 iteration: 82000 loss: 0.0026 lr: 0.02
  174. 2020-11-06 18:41:11 iteration: 83000 loss: 0.0027 lr: 0.02
  175. 2020-11-06 18:42:37 iteration: 84000 loss: 0.0027 lr: 0.02
  176. 2020-11-06 18:44:03 iteration: 85000 loss: 0.0027 lr: 0.02
  177. 2020-11-06 18:45:29 iteration: 86000 loss: 0.0026 lr: 0.02
  178. 2020-11-06 18:46:56 iteration: 87000 loss: 0.0027 lr: 0.02
  179. 2020-11-06 18:48:23 iteration: 88000 loss: 0.0027 lr: 0.02
  180. 2020-11-06 18:49:48 iteration: 89000 loss: 0.0026 lr: 0.02
  181. 2020-11-06 18:51:15 iteration: 90000 loss: 0.0026 lr: 0.02
  182. 2020-11-06 18:52:42 iteration: 91000 loss: 0.0026 lr: 0.02
  183. 2020-11-06 18:54:10 iteration: 92000 loss: 0.0026 lr: 0.02
  184. 2020-11-06 18:55:38 iteration: 93000 loss: 0.0026 lr: 0.02
  185. 2020-11-06 18:57:04 iteration: 94000 loss: 0.0025 lr: 0.02
  186. 2020-11-06 18:58:31 iteration: 95000 loss: 0.0026 lr: 0.02
  187. 2020-11-06 18:59:57 iteration: 96000 loss: 0.0026 lr: 0.02
  188. 2020-11-06 19:01:23 iteration: 97000 loss: 0.0026 lr: 0.02
  189. 2020-11-06 19:02:51 iteration: 98000 loss: 0.0027 lr: 0.02
  190. 2020-11-06 19:04:18 iteration: 99000 loss: 0.0026 lr: 0.02
  191. 2020-11-06 19:05:45 iteration: 100000 loss: 0.0026 lr: 0.02
  192. 2020-11-06 19:07:12 iteration: 101000 loss: 0.0026 lr: 0.02
  193. 2020-11-06 19:08:40 iteration: 102000 loss: 0.0025 lr: 0.02
  194. 2020-11-06 19:10:07 iteration: 103000 loss: 0.0025 lr: 0.02
  195. 2020-11-06 19:11:33 iteration: 104000 loss: 0.0025 lr: 0.02
  196. 2020-11-06 19:13:00 iteration: 105000 loss: 0.0025 lr: 0.02
  197. 2020-11-06 19:14:27 iteration: 106000 loss: 0.0024 lr: 0.02
  198. 2020-11-06 19:15:54 iteration: 107000 loss: 0.0025 lr: 0.02
  199. 2020-11-06 19:17:21 iteration: 108000 loss: 0.0025 lr: 0.02
  200. 2020-11-06 19:18:50 iteration: 109000 loss: 0.0025 lr: 0.02
  201. 2020-11-06 19:20:17 iteration: 110000 loss: 0.0025 lr: 0.02
  202. 2020-11-06 19:21:45 iteration: 111000 loss: 0.0025 lr: 0.02
  203. 2020-11-06 19:23:13 iteration: 112000 loss: 0.0025 lr: 0.02
  204. 2020-11-06 19:24:38 iteration: 113000 loss: 0.0024 lr: 0.02
  205. 2020-11-06 19:26:04 iteration: 114000 loss: 0.0024 lr: 0.02
  206. 2020-11-06 19:27:29 iteration: 115000 loss: 0.0025 lr: 0.02
  207. 2020-11-06 19:28:56 iteration: 116000 loss: 0.0025 lr: 0.02
  208. 2020-11-06 19:30:22 iteration: 117000 loss: 0.0024 lr: 0.02
  209. 2020-11-06 19:31:49 iteration: 118000 loss: 0.0024 lr: 0.02
  210. 2020-11-06 19:33:16 iteration: 119000 loss: 0.0024 lr: 0.02
  211. 2020-11-06 19:34:42 iteration: 120000 loss: 0.0025 lr: 0.02
  212. 2020-11-06 19:36:09 iteration: 121000 loss: 0.0024 lr: 0.02
  213. 2020-11-06 19:37:34 iteration: 122000 loss: 0.0024 lr: 0.02
  214. 2020-11-06 19:39:02 iteration: 123000 loss: 0.0024 lr: 0.02
  215. 2020-11-06 19:40:29 iteration: 124000 loss: 0.0024 lr: 0.02
  216. 2020-11-06 19:41:58 iteration: 125000 loss: 0.0024 lr: 0.02