diff --git a/src/mednet/libs/classification/scripts/config.py b/src/mednet/libs/classification/scripts/config.py
index 9a41ea8330e9007584ff33f3b179f66fe5f0de4c..7d32cc1c69800861fd95e3324c48b2e915e28c71 100644
--- a/src/mednet/libs/classification/scripts/config.py
+++ b/src/mednet/libs/classification/scripts/config.py
@@ -27,7 +27,7 @@ def config():
.. code:: sh
- mednet config list
+ mednet classification config list
\b
@@ -36,7 +36,7 @@ def config():
.. code:: sh
- mednet config list -v
+ mednet classification config list -v
""",
)
@@ -54,7 +54,7 @@ def list_(verbose) -> None: # numpydoc ignore=PR01
.. code:: sh
- mednet config describe montgomery
+ mednet classification config describe montgomery
\b
@@ -63,7 +63,7 @@ def list_(verbose) -> None: # numpydoc ignore=PR01
.. code:: sh
- mednet config describe montgomery -v
+ mednet classification config describe montgomery -v
""",
)
@@ -87,7 +87,7 @@ def describe(name, verbose) -> None: # numpydoc ignore=PR01
.. code:: sh
- $ mednet config copy montgomery -vvv newdataset.py
+ $ mednet classification config copy montgomery -vvv newdataset.py
""",
)
diff --git a/src/mednet/libs/classification/scripts/database.py b/src/mednet/libs/classification/scripts/database.py
index 974bf426ade241b4c02c2c224ebfa9e66c0e8101..4cd6a4145fe54c4cbb0c924ace82f607a602cf7f 100644
--- a/src/mednet/libs/classification/scripts/database.py
+++ b/src/mednet/libs/classification/scripts/database.py
@@ -89,7 +89,7 @@ def database() -> None:
.. code:: sh
- $ mednet database list
+ $ mednet classification database list
""",
)
@@ -108,7 +108,7 @@ def list_():
.. code:: sh
- mednet datamodule check -vv montgomery-f0
+ mednet classification datamodule check -vv montgomery-f0
""",
)
diff --git a/src/mednet/libs/classification/scripts/evaluate.py b/src/mednet/libs/classification/scripts/evaluate.py
index eb7970c9f8ad8eae45ff647d066f204a54ccf9cd..50c2e56a7dcb37051a78265ef27eb33bec9fd442 100644
--- a/src/mednet/libs/classification/scripts/evaluate.py
+++ b/src/mednet/libs/classification/scripts/evaluate.py
@@ -24,13 +24,13 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
.. code:: sh
- mednet evaluate -vv --predictions=path/to/predictions.json
+ mednet classification evaluate -vv --predictions=path/to/predictions.json
2. Run evaluation on an existing prediction output, tune threshold a priori on the `validation` set:
.. code:: sh
- mednet evaluate -vv --predictions=path/to/predictions.json --threshold=validation
+ mednet classification evaluate -vv --predictions=path/to/predictions.json --threshold=validation
""",
)
@click.option(
diff --git a/src/mednet/libs/classification/scripts/experiment.py b/src/mednet/libs/classification/scripts/experiment.py
index 3a469a8c3a59458befbd9d4f64afda7b429e3ab6..5dcfe0c9d400117178d2f314c23fc083fe24b0c7 100644
--- a/src/mednet/libs/classification/scripts/experiment.py
+++ b/src/mednet/libs/classification/scripts/experiment.py
@@ -28,7 +28,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
.. code:: sh
- $ mednet experiment -vv pasa montgomery --epochs=2
+ $ mednet classification experiment -vv pasa montgomery --epochs=2
""",
)
@training_options
@@ -60,7 +60,6 @@ def experiment(
.. code::
└─ <output-folder>/
- ├── command.sh
├── model/ # the generated model will be here
├── predictions.json # the prediction outputs for the sets
└── evaluation/ # the outputs of the evaluations for the sets
diff --git a/src/mednet/libs/classification/scripts/predict.py b/src/mednet/libs/classification/scripts/predict.py
index 2691727d6176bb17b618f900ca75a76b885faf36..a6f45a113fda61bc73a54ce4e95ef3f72dfdb772 100644
--- a/src/mednet/libs/classification/scripts/predict.py
+++ b/src/mednet/libs/classification/scripts/predict.py
@@ -21,13 +21,13 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
.. code:: sh
- mednet predict -vv pasa montgomery --weight=path/to/model.ckpt --output=path/to/predictions.json
+ mednet classification predict -vv pasa montgomery --weight=path/to/model.ckpt --output=path/to/predictions.json
2. Enable multi-processing data loading with 6 processes:
.. code:: sh
- mednet predict -vv pasa montgomery --parallel=6 --weight=path/to/model.ckpt --output=path/to/predictions.json
+ mednet classification predict -vv pasa montgomery --parallel=6 --weight=path/to/model.ckpt --output=path/to/predictions.json
""",
)
diff --git a/src/mednet/libs/classification/scripts/train.py b/src/mednet/libs/classification/scripts/train.py
index 9374afad382bf91f2ec2e0cdd266eafdbf187a24..58c99cad6c1477e336544ebd9bc25fc197c3aa3a 100644
--- a/src/mednet/libs/classification/scripts/train.py
+++ b/src/mednet/libs/classification/scripts/train.py
@@ -23,7 +23,7 @@ logger = setup("mednet", format="%(levelname)s: %(message)s")
.. code:: sh
- mednet train -vv pasa elastic montgomery --batch-size=4 --device="cuda:0"
+ mednet classification train -vv pasa elastic montgomery --batch-size=4 --device="cuda:0"
""",
)
@reusable_options
diff --git a/src/mednet/libs/segmentation/scripts/config.py b/src/mednet/libs/segmentation/scripts/config.py
index b900ba866fd78fe24bc2f834525f16938178f1f1..8fef1df9ee64b30e54c3437f46848457caa8079e 100644
--- a/src/mednet/libs/segmentation/scripts/config.py
+++ b/src/mednet/libs/segmentation/scripts/config.py
@@ -23,11 +23,11 @@ def config():
epilog="""Examples:
\b
- 1. Lists all configuration resources (type: mednet.libs.classification.config) installed:
+ 1. Lists all configuration resources (type: mednet.libs.segmentation.config) installed:
.. code:: sh
- mednet config list
+ mednet segmentation config list
\b
@@ -36,7 +36,7 @@ def config():
.. code:: sh
- mednet config list -v
+ mednet segmentation config list -v
""",
)
@@ -50,20 +50,20 @@ def list_(verbose) -> None: # numpydoc ignore=PR01
epilog="""Examples:
\b
- 1. Describe the Montgomery dataset configuration:
+ 1. Describe the Drive dataset configuration:
.. code:: sh
- mednet config describe montgomery
+ mednet segmentation config describe drive
\b
- 2. Describe the Montgomery dataset configuration and lists its
+ 2. Describe the Drive dataset configuration and lists its
contents:
.. code:: sh
- mednet config describe montgomery -v
+ mednet segmentation config describe deive -v
""",
)
@@ -87,7 +87,7 @@ def describe(name, verbose) -> None: # numpydoc ignore=PR01
.. code:: sh
- $ mednet config copy montgomery -vvv newdataset.py
+ $ mednet segmentation config copy drive -vvv newdataset.py
""",
)
diff --git a/src/mednet/libs/segmentation/scripts/database.py b/src/mednet/libs/segmentation/scripts/database.py
index 1610c16c8b2c958b9d3dae903e5c554d5289e048..272d4a0989678b16f6fee206cd91a3affd565d49 100644
--- a/src/mednet/libs/segmentation/scripts/database.py
+++ b/src/mednet/libs/segmentation/scripts/database.py
@@ -21,7 +21,7 @@ def _get_raw_databases() -> dict[str, dict[str, str]]:
containing two string keys:
* ``module``: the full Pythonic module name (e.g.
- ``mednet.libs.classification.data.montgomery``).
+ ``mednet.libs.segmentation.data.drive``).
* ``datadir``: points to the user-configured data directory for the
current dataset, if set, or ``None`` otherwise.
"""
@@ -71,14 +71,14 @@ def database() -> None:
\b
1. To install a database, set up its data directory ("datadir"). For
- example, to setup access to Montgomery files you downloaded locally at
- the directory "/path/to/montgomery/files", edit the RC file (typically
- ``$HOME/.config/mednet.libs.classification.toml``), and add a line like the following:
+ example, to setup access to Drive files you downloaded locally at
+ the directory "/path/to/drive/files", edit the RC file (typically
+ ``$HOME/.config/mednet.toml``), and add a line like the following:
.. code:: toml
[datadir]
- montgomery = "/path/to/montgomery/files"
+ drive = "/path/to/drive/files"
.. note::
@@ -89,7 +89,7 @@ def database() -> None:
.. code:: sh
- $ mednet database list
+ $ mednet segmentation database list
""",
)
@@ -102,12 +102,12 @@ def list_():
@database.command(
epilog="""Examples:
- 1. Check if all files from the fold 'montgomery-f0' of the Montgomery
+ 1. Check if all files from the fold 'default' of the Drive
database can be loaded:
.. code:: sh
- mednet datamodule check -vv montgomery-f0
+ mednet segmentation database check -vv drive
""",
)
diff --git a/src/mednet/libs/segmentation/scripts/experiment.py b/src/mednet/libs/segmentation/scripts/experiment.py
index 4c906c023f6e2d6e4e63f3973bb7c676b73040f6..a912559bc2e5da79f435f863ea1a4bc213ebde51 100644
--- a/src/mednet/libs/segmentation/scripts/experiment.py
+++ b/src/mednet/libs/segmentation/scripts/experiment.py
@@ -23,13 +23,13 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
epilog="""Examples:
\b
- 1. Train a pasa model with montgomery dataset, on the CPU, for only two
+ 1. Train a lwnet model with drive dataset, on the CPU, for only two
epochs, then runs inference and evaluation on stock datasets, report
performance as a table and figures:
.. code:: sh
- $ mednet experiment -vv pasa montgomery --epochs=2
+ $ mednet segmentation experiment -vv lwnet drive --epochs=2
""",
)
@training_options
@@ -59,9 +59,8 @@ def experiment(
\b
└─ <output-folder>/
- ├── command.sh
├── model/ # the generated model will be here
- ├── predictions.json # the prediction outputs for the sets
+ ├── predictions # the prediction outputs for the sets
└── evaluation/ # the outputs of the evaluations for the sets
"""
diff --git a/src/mednet/libs/segmentation/scripts/predict.py b/src/mednet/libs/segmentation/scripts/predict.py
index 84449741c95f9ab51305cd4820e0b23a622dd5d9..e96d25a3b905967b5497fd15df2773366b2f08e3 100644
--- a/src/mednet/libs/segmentation/scripts/predict.py
+++ b/src/mednet/libs/segmentation/scripts/predict.py
@@ -69,13 +69,13 @@ def _save_hdf5(
.. code:: sh
- mednet predict -vv pasa montgomery --weight=path/to/model.ckpt --output=path/to/predictions.json
+ mednet segmentation predict -vv lwnet drive --weight=path/to/model.ckpt --output=path/to/predictions.json
2. Enable multi-processing data loading with 6 processes:
.. code:: sh
- mednet predict -vv pasa montgomery --parallel=6 --weight=path/to/model.ckpt --output=path/to/predictions.json
+ mednet segmentation predict -vv lwnet drive --parallel=6 --weight=path/to/model.ckpt --output=path/to/predictions.json
""",
)
diff --git a/src/mednet/libs/segmentation/scripts/train.py b/src/mednet/libs/segmentation/scripts/train.py
index ac3813280a6c2bb6e28c246a1c1a1b28cb6600d5..5089ccab1d865ae8465e26686c7eec290a80c26f 100644
--- a/src/mednet/libs/segmentation/scripts/train.py
+++ b/src/mednet/libs/segmentation/scripts/train.py
@@ -18,11 +18,11 @@ logger = setup("mednet", format="%(levelname)s: %(message)s")
cls=ConfigCommand,
epilog="""Examples:
-1. Train a pasa model with the montgomery dataset, on a GPU (``cuda:0``):
+1. Train a lwnet model with the frive dataset, on a GPU (``cuda:0``):
.. code:: sh
- mednet train -vv pasa montgomery --batch-size=4 --device="cuda:0"
+ mednet segmentation train -vv lwnet drive --batch-size=4 --device="cuda:0"
""",
)
@reusable_options
@@ -44,7 +44,7 @@ def train(
augmentations,
**_,
) -> None: # numpydoc ignore=PR01
- """Train an CNN to perform image classification.
+ """Train an CNN to perform image segmentation.
Training is performed for a configurable number of epochs, and
generates checkpoints. Checkpoints are model files with a .ckpt