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produdez
/
kangaroo-detection
connected to https://github.com/produdez/kangaroo-detection.git

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   environment-check:
    4. 

  4.     cmd: "python -m src.pipeline.environment_check\n"
    5. 

  5.     deps:
    6. 

  6.     - path: src/pipeline/environment_check.py
    7. 

  7.       md5: 5f2f2cdc83c8bb4023ab08b15907b0cd
    8. 

  8.       size: 636
    9. 

  9.     params:
    10. 

  10.       params.yaml:
    11. 

  11.         environment-check:
    12. 

  12.           environment-name: kangaroo
    13. 

  13.           output: out/environment-check.out.json
    14. 

  14.     outs:
    15. 

  15.     - path: out/environment-check.out.json
    16. 

  16.       md5: 367ad52e2a3039d04f2dc57bbd7b5e6e
    17. 

  17.       size: 374
    18. 

  18.   activate-environment:
    19. 

  19.     cmd:
    20. 

  20.     - conda activate kangaroo
    21. 

  21.     - echo %CONDA_DEFAULT_ENV% > out/activate-environment.out.log
    22. 

  22.     outs:
    23. 

  23.     - path: out/activate-environment.out.log
    24. 

  24.       md5: ee9e762dca463f22b5e8ec0f982f5b63
    25. 

  25.       size: 22
    26. 

  26.   activate:
    27. 

  27.     cmd: conda activate kangaroo > out/activate-environment.out.log
    28. 

  28.     outs:
    29. 

  29.     - path: out/activate-environment.out.log
    30. 

  30.       md5: d41d8cd98f00b204e9800998ecf8427e
    31. 

  31.       size: 0
    32. 

  32.   train-model:
    33. 

  33.     cmd: "python -u -m src.pipeline.train_model | tee out/model-train.output.log\n"
    34. 

  34.     deps:
    35. 

  35.     - path: data/sample
    36. 

  36.       md5: 168cfd022598b30c5f1981bec5ac18ec.dir
    37. 

  37.       size: 635162
    38. 

  38.       nfiles: 18
    39. 

  39.     - path: model/transfer/mask_rcnn_coco.h5
    40. 

  40.       md5: e98aaff6f99e307b5e2a8a3ff741a518
    41. 

  41.       size: 257557808
    42. 

  42.     - path: out/environment-check.out.json
    43. 

  43.       md5: 367ad52e2a3039d04f2dc57bbd7b5e6e
    44. 

  44.       size: 374
    45. 

  45.     - path: src/pipeline/train_model.py
    46. 

  46.       md5: 2f97764fff9057dd92413a1758e101fb
    47. 

  47.       size: 2102
    48. 

  48.     params:
    49. 

  49.       params.yaml:
    50. 

  50.         train-pipeline:
    51. 

  51.           data:
    52. 

  52.             path: data/sample
    53. 

  53.             size: 10
    54. 

  54.             train_size: 5
    55. 

  55.           train_dir: model/training
    56. 

  56.           output:
    57. 

  57.             model: out/current-model.h5
    58. 

  58.             log: out/model-train.output.log
    59. 

  59.             metric:
    60. 

  60.               folder: out/train.metrics/
    61. 

  61.               general: general.json
    62. 

  62.               others:
    63. 

  63.               - epoch_mrcnn_bbox_loss
    64. 

  64.               - epoch_val_mrcnn_bbox_loss
    65. 

  65.           summary: out/model-train.summary.txt
    66. 

  66.       model.hyper.yaml:
    67. 

  67.         train:
    68. 

  68.           epochs: 10
    69. 

  69.           layers: heads
    70. 

  70.           configs:
    71. 

  71.             NAME: kangaroo_cfg
    72. 

  72.             NUM_CLASSES: 2
    73. 

  73.             STEPS_PER_EPOCH: 5
    74. 

  74.             BACKBONE: resnet101
    75. 

  75.             IMAGES_PER_GPU: 2
    76. 

  76.             GPU_COUNT: 1
    77. 

  77.           weights:
    78. 

  78.             init: model/transfer/mask_rcnn_coco.h5
    79. 

  79.             exclude:
    80. 

  80.             - mrcnn_class_logits
    81. 

  81.             - mrcnn_bbox_fc
    82. 

  82.             - mrcnn_bbox
    83. 

  83.             - mrcnn_mask
    84. 

  84.     outs:
    85. 

  85.     - path: out/current-model.h5
    86. 

  86.       md5: 866796d1c58130aba666ed5fde48f208
    87. 

  87.       size: 264294536
    88. 

  88.     - path: out/model-train.output.log
    89. 

  89.       md5: 814c43462efcc83c5692f34f9dfb0f71
    90. 

  90.       size: 6331
    91. 

  91.     - path: out/model-train.summary.txt
    92. 

  92.       md5: 28e1cb65aaa55d3cdb0e97a96ddd97cf
    93. 

  93.       size: 89607
    94. 

  94.     - path: out/train.metrics/general.json
    95. 

  95.       md5: 706da4354000f6504321e70fa84d6dd1
    96. 

  96.       size: 26
    97. 

  97.   evaluate:
    98. 

  98.     cmd: "python -u -m src.pipeline.evaluate | tee out/evaluate.output.log\n"
    99. 

  99.     deps:
    100. 

  100.     - path: data/sample
    101. 

  101.       md5: 168cfd022598b30c5f1981bec5ac18ec.dir
    102. 

  102.       size: 635162
    103. 

  103.       nfiles: 18
    104. 

  104.     - path: out/current-model.h5
    105. 

  105.       md5: 866796d1c58130aba666ed5fde48f208
    106. 

  106.       size: 264294536
    107. 

  107.     - path: out/environment-check.out.json
    108. 

  108.       md5: 367ad52e2a3039d04f2dc57bbd7b5e6e
    109. 

  109.       size: 374
    110. 

  110.     - path: src/pipeline/evaluate.py
    111. 

  111.       md5: f91d103ab96efceeacd2bd123444073b
    112. 

  112.       size: 1216
    113. 

  113.     params:
    114. 

  114.       params.yaml:
    115. 

  115.         evaluate:
    116. 

  116.           data:
    117. 

  117.             path: data/sample
    118. 

  118.             size: 10
    119. 

  119.             train_size: 5
    120. 

  120.           model-weight: out/current-model.h5
    121. 

  121.           evaluate_dir: model/evaluate
    122. 

  122.           output:
    123. 

  123.             metric: out/evaluate.json
    124. 

  124.             log: out/evaluate.output.log
    125. 

  125.       model.hyper.yaml:
    126. 

  126.         inference:
    127. 

  127.           configs:
    128. 

  128.             NAME: kangaroo_cfg
    129. 

  129.             NUM_CLASSES: 2
    130. 

  130.             STEPS_PER_EPOCH: 5
    131. 

  131.             BACKBONE: resnet101
    132. 

  132.             IMAGES_PER_GPU: 1
    133. 

  133.             GPU_COUNT: 1
    134. 

  134.             USE_MINI_MASK: false
    135. 

  135.     outs:
    136. 

  136.     - path: out/evaluate.json
    137. 

  137.       md5: 2dd3f52bc0bf37053c999b0550190b2d
    138. 

  138.       size: 178
    139. 

  139.   gen-dag:
    140. 

  140.     cmd:
    141. 

  141.     - dvc dag --full --md >> out/dependency_diagram.md
    142. 

  142.     - dvc dag -o --md >> out/dependency_diagram.md
    143. 

  143.     outs:
    144. 

  144.     - path: out/dependency_diagram.md
    145. 

  145.       md5: 787a06c15b8649bfd81d33179f067ef2
    146. 

  146.       size: 1069
    147.
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