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🚀 Add PreProcessor to AnomalyModule #2358

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🚀 Add PreProcessor to AnomalyModule #2358

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5338afa
Created pre-processor
samet-akcay Oct 9, 2024
180c22f
Rename transforms to transform in pre-processor
samet-akcay Oct 9, 2024
7738e38
Remove transforms from datamodules
samet-akcay Oct 9, 2024
a133048
Remove transforms from datasets
samet-akcay Oct 9, 2024
c748a0d
Remove setup_transforms from Engine
samet-akcay Oct 9, 2024
03a2a2e
Add preprocessor to AnomalyModule and models
samet-akcay Oct 9, 2024
6f7399a
Fix tests
samet-akcay Oct 10, 2024
cc5f559
Remove self._transform from AnomalyModule
samet-akcay Oct 10, 2024
4d2e110
revert transforms in datasets
samet-akcay Oct 11, 2024
1e83e57
fix efficient_ad and engine.config tests
samet-akcay Oct 11, 2024
1e05349
Update the upgrade tests
samet-akcay Oct 11, 2024
785d64f
Revert on_load_checkpoint hook to AnomalyModule
samet-akcay Oct 11, 2024
b798243
Remove exportable transform from anomaly module and move to pre-proce…
samet-akcay Oct 15, 2024
4bf6187
Merge branch 'feature/design-simplifications' of github.com:openvinot…
samet-akcay Oct 15, 2024
c942604
Merge main
samet-akcay Oct 16, 2024
ea28833
Add pre-processor to the model graph
samet-akcay Oct 17, 2024
78cf516
Add docstring to pre-processor class
samet-akcay Oct 17, 2024
46fe7e5
Fix win-clip tests
samet-akcay Oct 17, 2024
f058fbb
Update notebooks
samet-akcay Oct 17, 2024
84c39cd
Split the forward logic and move the training to model hooks
samet-akcay Oct 21, 2024
6ebbb23
Set data transforms from preprocessor
samet-akcay Oct 21, 2024
1b0483a
Update the docstrings
samet-akcay Oct 21, 2024
a503be1
Get stage transforms in setup of pre-processor
samet-akcay Oct 22, 2024
427f680
Revert data config yaml files
samet-akcay Oct 23, 2024
2ee60ee
Revert datamodules
samet-akcay Oct 23, 2024
138c7e3
Revert datasets
samet-akcay Oct 23, 2024
2e9a544
Revert notebooks
samet-akcay Oct 23, 2024
cd524b5
remove padim preprocessor
samet-akcay Oct 23, 2024
8cd8f7f
Update the setup logic in pre-processor
samet-akcay Oct 23, 2024
f841150
Update the setup logic in pre-processor
samet-akcay Oct 23, 2024
d07f0b9
Revert datamodules
samet-akcay Oct 23, 2024
760d5e5
Set datamodule transforms property from preprocessor
samet-akcay Oct 24, 2024
83c2084
Revert v1 upgrade tool
samet-akcay Oct 24, 2024
e83f9cf
Fix aupimo notebooks
samet-akcay Oct 24, 2024
721e11f
Add pre-processor unit tests
samet-akcay Oct 24, 2024
f937abf
Increase the test coverage for PreProcessor
samet-akcay Oct 24, 2024
ec3e97c
Add option to disable pre-processor
samet-akcay Oct 25, 2024
9b42d5d
Split setup_transforms to setup_datamodule_transforms and setup_datal…
samet-akcay Oct 25, 2024
8c379c0
Replace batch.update with in-place batch transforms
samet-akcay Oct 25, 2024
db1d543
Remove logger.warning when the default pre-processor is used
samet-akcay Oct 25, 2024
9ec2547
Use predict-transforms explicitly
samet-akcay Oct 25, 2024
ba240be
remove pre-processor and configure_transforms from export mixin
samet-akcay Oct 25, 2024
6ea5369
Rename set_datamodule_transform to set_datamodule_stage_transform
samet-akcay Oct 26, 2024
c71e41c
Remove transforms from datamodules
samet-akcay Oct 29, 2024
b9bb700
Remove transforms from datamodules
samet-akcay Oct 29, 2024
185fec8
Remove transforms from datamodules
samet-akcay Oct 29, 2024
06fd947
Remove transforms from datamodules
samet-akcay Oct 29, 2024
079168e
Remove transforms from datamodules
samet-akcay Oct 29, 2024
1f6555c
Remove transform related keys from data configs
samet-akcay Oct 29, 2024
03196fa
update preprocessor tests
samet-akcay Oct 29, 2024
d579312
Remove setup method from the model implementations
samet-akcay Oct 29, 2024
5e82c34
Remove image size from datamodules in jupyter notebooks
samet-akcay Oct 29, 2024
a1a0548
Modify folder notebook to acccess the batch from dataset not dataloader
samet-akcay Oct 30, 2024
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3 changes: 0 additions & 3 deletions configs/data/avenue.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,9 +8,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
val_split_mode: from_test
val_split_ratio: 0.5
seed: null
3 changes: 0 additions & 3 deletions configs/data/btech.yaml
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Expand Up @@ -5,9 +5,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
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3 changes: 0 additions & 3 deletions configs/data/folder.yaml
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Expand Up @@ -12,9 +12,6 @@ init_args:
eval_batch_size: 32
num_workers: 8
task: segmentation
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
Expand Down
3 changes: 0 additions & 3 deletions configs/data/kolektor.yaml
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Expand Up @@ -4,9 +4,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
Expand Down
3 changes: 0 additions & 3 deletions configs/data/mvtec.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,6 @@ init_args:
eval_batch_size: 32
num_workers: 8
task: segmentation
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
Expand Down
3 changes: 0 additions & 3 deletions configs/data/mvtec_3d.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
Expand Down
3 changes: 0 additions & 3 deletions configs/data/shanghaitech.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,9 +8,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
val_split_mode: FROM_TEST
val_split_ratio: 0.5
seed: null
3 changes: 0 additions & 3 deletions configs/data/ucsd_ped.yaml
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Expand Up @@ -8,9 +8,6 @@ init_args:
train_batch_size: 8
eval_batch_size: 1
num_workers: 8
transform: null
train_transform: null
eval_transform: null
val_split_mode: FROM_TEST
val_split_ratio: 0.5
seed: null
3 changes: 0 additions & 3 deletions configs/data/visa.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,6 @@ init_args:
train_batch_size: 32
eval_batch_size: 32
num_workers: 8
transform: null
train_transform: null
eval_transform: null
test_split_mode: from_dir
test_split_ratio: 0.2
val_split_mode: same_as_test
Expand Down
5 changes: 2 additions & 3 deletions notebooks/100_datamodules/101_btech.ipynb
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Expand Up @@ -48,7 +48,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"BTech\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"BTech\""
]
},
{
Expand Down Expand Up @@ -106,7 +106,6 @@
"btech_datamodule = BTech(\n",
" root=dataset_root,\n",
" category=\"01\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=0,\n",
Expand Down Expand Up @@ -378,7 +377,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
},
"orig_nbformat": 4,
"vscode": {
Expand Down
5 changes: 2 additions & 3 deletions notebooks/100_datamodules/102_mvtec.ipynb
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Expand Up @@ -58,7 +58,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"MVTec\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"MVTec\""
]
},
{
Expand All @@ -84,7 +84,6 @@
"mvtec_datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"bottle\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=0,\n",
Expand Down Expand Up @@ -345,7 +344,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
},
"orig_nbformat": 4,
"vscode": {
Expand Down
21 changes: 10 additions & 11 deletions notebooks/100_datamodules/103_folder.ipynb
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Expand Up @@ -33,7 +33,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -42,7 +42,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"hazelnut_toy\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"hazelnut_toy\""
]
},
{
Expand All @@ -63,7 +63,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -91,7 +91,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -102,7 +102,6 @@
" abnormal_dir=\"crack\",\n",
" task=TaskType.SEGMENTATION,\n",
" mask_dir=dataset_root / \"mask\" / \"crack\",\n",
" image_size=(256, 256),\n",
")\n",
"folder_datamodule.setup()"
]
Expand All @@ -114,7 +113,7 @@
"outputs": [],
"source": [
"# Train images\n",
"i, data = next(enumerate(folder_datamodule.train_dataloader()))\n",
"data = next(iter(folder_datamodule.train_data))\n",
"print(data.image.shape)"
]
},
Expand All @@ -125,7 +124,7 @@
"outputs": [],
"source": [
"# Test images\n",
"i, data = next(enumerate(folder_datamodule.test_dataloader()))\n",
"data = next(iter(folder_datamodule.test_data))\n",
"print(data.image.shape, data.gt_mask.shape)"
]
},
Expand All @@ -143,8 +142,8 @@
"metadata": {},
"outputs": [],
"source": [
"img = to_pil_image(data.image[0].clone())\n",
"msk = to_pil_image(data.gt_mask[0].int() * 255).convert(\"RGB\")\n",
"img = to_pil_image(data.image.clone())\n",
"msk = to_pil_image(data.gt_mask.int() * 255).convert(\"RGB\")\n",
"\n",
"Image.fromarray(np.hstack((np.array(img), np.array(msk))))"
]
Expand Down Expand Up @@ -187,7 +186,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -369,7 +368,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
},
"orig_nbformat": 4,
"vscode": {
Expand Down
2 changes: 1 addition & 1 deletion notebooks/100_datamodules/104_tiling.ipynb
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Expand Up @@ -44,7 +44,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"MVTec\" / \"transistor\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"MVTec\" / \"transistor\""
]
},
{
Expand Down
5 changes: 2 additions & 3 deletions notebooks/200_models/201_fastflow.ipynb
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Expand Up @@ -44,7 +44,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"MVTec\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"MVTec\""
]
},
{
Expand Down Expand Up @@ -120,7 +120,6 @@
"datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"bottle\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=0,\n",
Expand Down Expand Up @@ -555,7 +554,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
},
"orig_nbformat": 4,
"vscode": {
Expand Down
5 changes: 2 additions & 3 deletions notebooks/600_loggers/601_mlflow_logging.ipynb
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Expand Up @@ -135,7 +135,7 @@
"# NOTE: Provide the path to the dataset root directory.\n",
"# If the datasets is not downloaded, it will be downloaded\n",
"# to this directory.\n",
"dataset_root = Path.cwd().parent / \"datasets\" / \"MVTec\""
"dataset_root = Path.cwd().parent.parent / \"datasets\" / \"MVTec\""
]
},
{
Expand Down Expand Up @@ -197,7 +197,6 @@
"datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"bottle\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=24,\n",
Expand Down Expand Up @@ -421,7 +420,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
}
},
"nbformat": 4,
Expand Down
7 changes: 2 additions & 5 deletions notebooks/700_metrics/701a_aupimo.ipynb
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Expand Up @@ -140,7 +140,6 @@
"datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"leather\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=8,\n",
Expand Down Expand Up @@ -357,9 +356,7 @@
")\n",
"\n",
"for batch in predictions:\n",
" anomaly_maps = batch[\"anomaly_maps\"].squeeze(dim=1)\n",
" masks = batch[\"mask\"]\n",
" aupimo.update(anomaly_maps=anomaly_maps, masks=masks)"
" aupimo.update(anomaly_maps=batch.anomaly_map, masks=batch.gt_mask)"
]
},
{
Expand Down Expand Up @@ -534,7 +531,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
"version": "3.11.8"
},
"orig_nbformat": 4
},
Expand Down
9 changes: 4 additions & 5 deletions notebooks/700_metrics/701b_aupimo_advanced_i.ipynb
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Expand Up @@ -164,7 +164,6 @@
"datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"leather\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=8,\n",
Expand Down Expand Up @@ -219,10 +218,10 @@
"labels = []\n",
"image_paths = []\n",
"for batch in predictions:\n",
" anomaly_maps.append(batch_anomaly_maps := batch[\"anomaly_maps\"].squeeze(dim=1))\n",
" masks.append(batch_masks := batch[\"mask\"])\n",
" labels.append(batch[\"label\"])\n",
" image_paths.append(batch[\"image_path\"])\n",
" anomaly_maps.append(batch_anomaly_maps := batch.anomaly_map)\n",
" masks.append(batch_masks := batch.gt_mask)\n",
" labels.append(batch.gt_label)\n",
" image_paths.append(batch.image_path)\n",
" aupimo.update(anomaly_maps=batch_anomaly_maps, masks=batch_masks)\n",
"\n",
"# list[list[str]] -> list[str]\n",
Expand Down
9 changes: 4 additions & 5 deletions notebooks/700_metrics/701c_aupimo_advanced_ii.ipynb
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Expand Up @@ -158,7 +158,6 @@
"datamodule = MVTec(\n",
" root=dataset_root,\n",
" category=\"leather\",\n",
" image_size=256,\n",
" train_batch_size=32,\n",
" eval_batch_size=32,\n",
" num_workers=8,\n",
Expand Down Expand Up @@ -213,10 +212,10 @@
"labels = []\n",
"image_paths = []\n",
"for batch in predictions:\n",
" anomaly_maps.append(batch_anomaly_maps := batch[\"anomaly_maps\"].squeeze(dim=1))\n",
" masks.append(batch_masks := batch[\"mask\"])\n",
" labels.append(batch[\"label\"])\n",
" image_paths.append(batch[\"image_path\"])\n",
" anomaly_maps.append(batch_anomaly_maps := batch.anomaly_map)\n",
" masks.append(batch_masks := batch.gt_mask)\n",
" labels.append(batch.gt_label)\n",
" image_paths.append(batch.image_path)\n",
" aupimo.update(anomaly_maps=batch_anomaly_maps, masks=batch_masks)\n",
"\n",
"# list[list[str]] -> list[str]\n",
Expand Down
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