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dvc.lock
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schema: '2.0'
stages:
download_data:
cmd: python src/pipeline/download_data.py
deps:
- path: src/pipeline/download_data.py
md5: a253f2456a52024015034e909fcddbb0
size: 809
outs:
- path: data/raw/annotations.csv
md5: e16179b0438f32222098fa82261cc1e7
size: 15787
- path: data/raw/images
md5: a9a25050ebbf88b8188d804e54c27600.dir
size: 12808659
nfiles: 433
- path: data/raw/plates.csv
md5: 230a14f00bece9df11719b3e04ac8210
size: 7380
make_dataset:
cmd: python src/pipeline/make_dataset.py
deps:
- path: data/raw/annotations.csv
md5: e16179b0438f32222098fa82261cc1e7
size: 15787
- path: data/raw/images
md5: a9a25050ebbf88b8188d804e54c27600.dir
size: 12808659
nfiles: 433
- path: data/raw/plates.csv
md5: 230a14f00bece9df11719b3e04ac8210
size: 7380
- path: src/pipeline/make_dataset.py
md5: e1101cf189d047149df3e0bd1970088f
size: 3052
params:
params.yaml:
random_state: 42
outs:
- path: data/processed/test
md5: 22a16789f61f67221776c4805359f398.dir
size: 2584110
nfiles: 88
- path: data/processed/train
md5: 052c35f5225bdc40392f1e782789e01b.dir
size: 9000032
nfiles: 305
- path: data/processed/validation
md5: 95a74dab37061a91ea7f893d4bfae23b.dir
size: 1238510
nfiles: 43
train_model:
cmd: python src/pipeline/train_model.py
deps:
- path: data/processed
md5: 8c045e5acc5c24df4069d918b1f6489f.dir
size: 12822673
nfiles: 437
- path: reports/great_expectations/test_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
- path: reports/great_expectations/train_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
- path: reports/great_expectations/validation_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
- path: src/models/fetch_model.py
md5: cf76fc8318ef933baf2d089fec9425f7
size: 653
- path: src/models/model_builder.py
md5: 2295f4b2b811389f852a3619ac319ed5
size: 1834
- path: src/pipeline/train_model.py
md5: 2a1be97db3858c4e846d594288e70276
size: 2091
params:
params.yaml:
random_state: 42
train:
fit:
epochs: 10
model:
model_name: teste
model_version: 1
dropout: 0.4
cnn_blocks: 6
filters_num: 32
filters_kernel_size: 3
outs:
- path: reports/train/history.json
md5: 91dacccb1434d85088de009945f4155a
size: 1170
predict_model:
cmd: python src/pipeline/test_model.py
deps:
- path: src/pipeline/test_model.py
md5: a8b788e2cc9f394d8a65fca3f6e941cb
size: 3328
params:
params.yaml:
test:
model:
model_name: test
model_version: 1
tr_ocr_processor: microsoft/trocr-small-printed
tr_ocr_model: microsoft/trocr-small-printed
data_expectations:
cmd: python src/pipeline/data_expectations.py
deps:
- path: data/processed
md5: 8c045e5acc5c24df4069d918b1f6489f.dir
size: 12822673
nfiles: 437
outs:
- path: reports/great_expectations/test_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
- path: reports/great_expectations/train_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
- path: reports/great_expectations/validation_annotations.json
md5: fb68c09946cbc73175ee3cc1230f50e7
size: 741
test_model:
cmd: python src/pipeline/test_model.py
deps:
- path: reports/train/history.json
md5: 91dacccb1434d85088de009945f4155a
size: 1170
- path: src/pipeline/test_model.py
md5: 9618d369cb959b49888148f39da0be3b
size: 3477
params:
params.yaml:
test:
model:
model_name: test
model_version: 1
tr_ocr_processor: microsoft/trocr-small-printed
tr_ocr_model: microsoft/trocr-small-printed