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mozhi commited on
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1 Parent(s): 98b8327

Add application files/ Add lfs tracker

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  1. .gitattributes +1 -0
  2. README.md +0 -0
  3. app.py +121 -0
  4. cfa/mvtec/bottle/run/config.yaml +109 -0
  5. cfa/mvtec/bottle/run/config_original.yaml +100 -0
  6. cfa/mvtec/bottle/run/weights/openvino/metadata.json +52 -0
  7. cfa/mvtec/bottle/run/weights/openvino/model.mapping +1207 -0
  8. cfa/mvtec/bottle/run/weights/openvino/model.onnx +3 -0
  9. cfa/mvtec/bottle/run/weights/openvino/model.xml +0 -0
  10. cfa/mvtec/cable/run/config.yaml +109 -0
  11. cfa/mvtec/cable/run/config_original.yaml +100 -0
  12. cfa/mvtec/cable/run/weights/openvino/metadata.json +52 -0
  13. cfa/mvtec/cable/run/weights/openvino/model.mapping +1207 -0
  14. cfa/mvtec/cable/run/weights/openvino/model.onnx +3 -0
  15. cfa/mvtec/cable/run/weights/openvino/model.xml +0 -0
  16. cfa/mvtec/capsule/run/config.yaml +109 -0
  17. cfa/mvtec/capsule/run/config_original.yaml +100 -0
  18. cfa/mvtec/capsule/run/weights/openvino/metadata.json +52 -0
  19. cfa/mvtec/capsule/run/weights/openvino/model.mapping +1207 -0
  20. cfa/mvtec/capsule/run/weights/openvino/model.onnx +3 -0
  21. cfa/mvtec/capsule/run/weights/openvino/model.xml +0 -0
  22. cfa/mvtec/carpet/run/config.yaml +109 -0
  23. cfa/mvtec/carpet/run/config_original.yaml +100 -0
  24. cfa/mvtec/carpet/run/weights/openvino/metadata.json +52 -0
  25. cfa/mvtec/carpet/run/weights/openvino/model.mapping +1207 -0
  26. cfa/mvtec/carpet/run/weights/openvino/model.onnx +3 -0
  27. cfa/mvtec/carpet/run/weights/openvino/model.xml +0 -0
  28. cfa/mvtec/grid/run/config.yaml +109 -0
  29. cfa/mvtec/grid/run/config_original.yaml +100 -0
  30. cfa/mvtec/grid/run/weights/openvino/metadata.json +52 -0
  31. cfa/mvtec/grid/run/weights/openvino/model.mapping +1207 -0
  32. cfa/mvtec/grid/run/weights/openvino/model.onnx +3 -0
  33. cfa/mvtec/grid/run/weights/openvino/model.xml +0 -0
  34. cfa/mvtec/hazelnut/run/config.yaml +109 -0
  35. cfa/mvtec/hazelnut/run/config_original.yaml +100 -0
  36. cfa/mvtec/hazelnut/run/weights/openvino/metadata.json +52 -0
  37. cfa/mvtec/hazelnut/run/weights/openvino/model.mapping +1207 -0
  38. cfa/mvtec/hazelnut/run/weights/openvino/model.onnx +3 -0
  39. cfa/mvtec/hazelnut/run/weights/openvino/model.xml +0 -0
  40. cfa/mvtec/leather/run/config.yaml +109 -0
  41. cfa/mvtec/leather/run/config_original.yaml +100 -0
  42. cfa/mvtec/leather/run/weights/openvino/metadata.json +52 -0
  43. cfa/mvtec/leather/run/weights/openvino/model.mapping +1207 -0
  44. cfa/mvtec/leather/run/weights/openvino/model.onnx +3 -0
  45. cfa/mvtec/leather/run/weights/openvino/model.xml +0 -0
  46. cfa/mvtec/metal_nut/run/config.yaml +109 -0
  47. cfa/mvtec/metal_nut/run/config_original.yaml +100 -0
  48. cfa/mvtec/metal_nut/run/weights/openvino/metadata.json +52 -0
  49. cfa/mvtec/metal_nut/run/weights/openvino/model.mapping +1207 -0
  50. cfa/mvtec/metal_nut/run/weights/openvino/model.onnx +3 -0
.gitattributes CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
32
  *.zip filter=lfs diff=lfs merge=lfs -text
33
  *.zst filter=lfs diff=lfs merge=lfs -text
34
  *tfevents* filter=lfs diff=lfs merge=lfs -text
35
+ *.png filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
File without changes
app.py ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from __future__ import annotations
2
+
3
+ from argparse import ArgumentParser
4
+ from importlib import import_module
5
+ from pathlib import Path
6
+
7
+ import gradio as gr
8
+ import gradio.inputs
9
+ import gradio.outputs
10
+ import numpy as np
11
+ import os
12
+ from anomalib.deploy import Inferencer
13
+
14
+
15
+ def get_inferencer(weight_path: Path, metadata_path: Path | None = None) -> Inferencer:
16
+ """Parse args and open inferencer.
17
+
18
+ Args:
19
+ weight_path (Path): Path to model weights.
20
+ metadata_path (Path | None, optional): Metadata is required for OpenVINO models. Defaults to None.
21
+
22
+ Raises:
23
+ ValueError: If unsupported model weight is passed.
24
+
25
+ Returns:
26
+ Inferencer: Torch or OpenVINO inferencer.
27
+ """
28
+
29
+ inferencer: Inferencer
30
+ module = import_module("anomalib.deploy")
31
+
32
+ openvino_inferencer = getattr(module, "OpenVINOInferencer")
33
+ print(f"weight path: {weight_path}")
34
+ print(f"metadata path: {metadata_path}")
35
+ inferencer = openvino_inferencer(path=weight_path, metadata_path=metadata_path)
36
+
37
+
38
+ return inferencer
39
+
40
+
41
+ def infer(radio: str, image: np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
42
+ """Inference function, return anomaly map, score, heat map, prediction mask ans visualisation.
43
+
44
+ Args:
45
+ image (np.ndarray): image to compute
46
+ inferencer (Inferencer): model inferencer
47
+
48
+ Returns:
49
+ tuple[np.ndarray, float, np.ndarray, np.ndarray, np.ndarray]:
50
+ heat_map, pred_mask, segmentation result.
51
+ """
52
+ # Perform inference for the given image.
53
+ print(f"Radio Value: {radio.lower()}")
54
+ print(f"{os.getcwd()}")
55
+ weight_path = f"cfa/mvtec/{radio.lower()}/run/weights/openvino/model.onnx"
56
+ metadata_path = f"cfa/mvtec/{radio.lower()}/run/weights/openvino/metadata.json"
57
+ inferencer = get_inferencer(weight_path, metadata_path)
58
+
59
+ predictions = inferencer.predict(image=image)
60
+ return (predictions.heat_map, predictions.pred_mask, predictions.segmentations)
61
+
62
+
63
+ if __name__ == "__main__":
64
+
65
+ interface = gr.Interface(
66
+ fn=lambda radio, image: infer(radio, image),
67
+ inputs=[
68
+ gr.Radio(
69
+ [
70
+ "Bottle",
71
+ "Cable",
72
+ "Capsule",
73
+ "Carpet",
74
+ "Grid",
75
+ "Hazelnut",
76
+ "Leather",
77
+ "Metal_nut",
78
+ "Pill",
79
+ "Screw",
80
+ "Tile",
81
+ "Toothbrush",
82
+ "Transistor",
83
+ "Wood",
84
+ "Zipper",
85
+ ],
86
+ label="MVTEC Class Name",
87
+ value="Bottle",
88
+ ).style(height=400),
89
+ gradio.inputs.Image(
90
+ shape=None, image_mode="RGB", source="upload", tool="editor", type="numpy", label="Image"
91
+ ).style(height=350),
92
+ ],
93
+ outputs=[
94
+ gradio.outputs.Image(type="numpy", label="Predicted Heat Map").style(height=200),
95
+ gradio.outputs.Image(type="numpy", label="Predicted Mask").style(height=200),
96
+ gradio.outputs.Image(type="numpy", label="Segmentation Result").style(height=200),
97
+ ],
98
+ examples=[
99
+ ["Bottle", "sample_images/bottle.png"],
100
+ ["Cable", "sample_images/cable.png"],
101
+ ["Capsule", "sample_images/capsule.png"],
102
+ ["Carpet", "sample_images/carpet.png"],
103
+ ["Grid", "sample_images/grid.png"],
104
+ ["Hazelnut", "sample_images/hazelnut.png"],
105
+ ["Leather", "sample_images/leather.png"],
106
+ ["Metal_nut", "sample_images/metal_nut.png"],
107
+ ["Pill", "sample_images/pill.png"],
108
+ ["Screw", "sample_images/screw.png"],
109
+ ["Tile", "sample_images/tile.png"],
110
+ ["Toothbrush", "sample_images/toothbrush.png"],
111
+ ["Transistor", "sample_images/transistor.png"],
112
+ ["Wood", "sample_images/wood.png"],
113
+ ["Zipper", "sample_images/zipper.png"],
114
+ ],
115
+ title="Anomaly Detection",
116
+ description="Anomlay Detection on Industrial Images",
117
+ css=".output-image, .image-preview {height: 300px !important}",
118
+ allow_flagging="never",
119
+ )
120
+
121
+ interface.launch(share=True)
cfa/mvtec/bottle/run/config.yaml ADDED
@@ -0,0 +1,109 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset:
2
+ name: mvtec
3
+ format: mvtec
4
+ path: ./datasets/MVTec
5
+ category: bottle
6
+ task: segmentation
7
+ train_batch_size: 4
8
+ eval_batch_size: 4
9
+ inference_batch_size: 4
10
+ num_workers: 8
11
+ image_size:
12
+ - 224
13
+ - 224
14
+ center_crop: null
15
+ normalization: imagenet
16
+ transform_config:
17
+ train: null
18
+ eval: null
19
+ test_split_mode: from_dir
20
+ test_split_ratio: 0.2
21
+ val_split_mode: same_as_test
22
+ val_split_ratio: 0.5
23
+ model:
24
+ name: cfa
25
+ backbone: wide_resnet50_2
26
+ gamma_c: 1
27
+ gamma_d: 1
28
+ num_nearest_neighbors: 3
29
+ num_hard_negative_features: 3
30
+ radius: 1.0e-05
31
+ lr: 0.001
32
+ weight_decay: 0.0005
33
+ amsgrad: true
34
+ early_stopping:
35
+ patience: 5
36
+ metric: pixel_AUROC
37
+ mode: max
38
+ normalization_method: min_max
39
+ input_size:
40
+ - 224
41
+ - 224
42
+ metrics:
43
+ image:
44
+ - AUROC
45
+ pixel:
46
+ - AUROC
47
+ threshold:
48
+ adaptive: true
49
+ image_default: null
50
+ pixel_default: null
51
+ method: adaptive
52
+ manual_image: null
53
+ manual_pixel: null
54
+ visualization:
55
+ show_images: false
56
+ save_images: true
57
+ log_images: true
58
+ image_save_path: null
59
+ mode: full
60
+ project:
61
+ seed: 0
62
+ path: results/cfa/mvtec/bottle/run
63
+ unique_dir: false
64
+ logging:
65
+ logger: []
66
+ log_graph: false
67
+ optimization:
68
+ export_mode: null
69
+ trainer:
70
+ enable_checkpointing: true
71
+ default_root_dir: results/cfa/mvtec/bottle/run
72
+ gradient_clip_val: 0
73
+ gradient_clip_algorithm: norm
74
+ num_nodes: 1
75
+ devices: 1
76
+ enable_progress_bar: true
77
+ overfit_batches: 0.0
78
+ track_grad_norm: -1
79
+ check_val_every_n_epoch: 1
80
+ fast_dev_run: false
81
+ accumulate_grad_batches: 1
82
+ max_epochs: 30
83
+ min_epochs: null
84
+ max_steps: -1
85
+ min_steps: null
86
+ max_time: null
87
+ limit_train_batches: 1.0
88
+ limit_val_batches: 1.0
89
+ limit_test_batches: 1.0
90
+ limit_predict_batches: 1.0
91
+ val_check_interval: 1.0
92
+ log_every_n_steps: 50
93
+ accelerator: auto
94
+ strategy: null
95
+ sync_batchnorm: false
96
+ precision: 32
97
+ enable_model_summary: true
98
+ num_sanity_val_steps: 0
99
+ profiler: null
100
+ benchmark: false
101
+ deterministic: false
102
+ reload_dataloaders_every_n_epochs: 0
103
+ auto_lr_find: false
104
+ replace_sampler_ddp: true
105
+ detect_anomaly: false
106
+ auto_scale_batch_size: false
107
+ plugins: null
108
+ move_metrics_to_cpu: false
109
+ multiple_trainloader_mode: max_size_cycle
cfa/mvtec/bottle/run/config_original.yaml ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset:
2
+ name: mvtec
3
+ format: mvtec
4
+ path: ./datasets/MVTec
5
+ category: bottle
6
+ task: segmentation
7
+ train_batch_size: 4
8
+ eval_batch_size: 4
9
+ inference_batch_size: 4
10
+ num_workers: 8
11
+ image_size: 224
12
+ center_crop: null
13
+ normalization: imagenet
14
+ transform_config:
15
+ train: null
16
+ eval: null
17
+ test_split_mode: from_dir
18
+ test_split_ratio: 0.2
19
+ val_split_mode: same_as_test
20
+ val_split_ratio: 0.5
21
+ model:
22
+ name: cfa
23
+ backbone: wide_resnet50_2
24
+ gamma_c: 1
25
+ gamma_d: 1
26
+ num_nearest_neighbors: 3
27
+ num_hard_negative_features: 3
28
+ radius: 1.0e-05
29
+ lr: 0.001
30
+ weight_decay: 0.0005
31
+ amsgrad: true
32
+ early_stopping:
33
+ patience: 5
34
+ metric: pixel_AUROC
35
+ mode: max
36
+ normalization_method: min_max
37
+ metrics:
38
+ image:
39
+ - AUROC
40
+ pixel:
41
+ - AUROC
42
+ threshold:
43
+ adaptive: true
44
+ image_default: null
45
+ pixel_default: null
46
+ visualization:
47
+ show_images: false
48
+ save_images: true
49
+ log_images: true
50
+ image_save_path: null
51
+ mode: full
52
+ project:
53
+ seed: 0
54
+ path: ./results
55
+ logging:
56
+ logger: []
57
+ log_graph: false
58
+ optimization:
59
+ export_mode: null
60
+ trainer:
61
+ enable_checkpointing: true
62
+ default_root_dir: null
63
+ gradient_clip_val: 0
64
+ gradient_clip_algorithm: norm
65
+ num_nodes: 1
66
+ devices: 1
67
+ enable_progress_bar: true
68
+ overfit_batches: 0.0
69
+ track_grad_norm: -1
70
+ check_val_every_n_epoch: 1
71
+ fast_dev_run: false
72
+ accumulate_grad_batches: 1
73
+ max_epochs: 30
74
+ min_epochs: null
75
+ max_steps: -1
76
+ min_steps: null
77
+ max_time: null
78
+ limit_train_batches: 1.0
79
+ limit_val_batches: 1.0
80
+ limit_test_batches: 1.0
81
+ limit_predict_batches: 1.0
82
+ val_check_interval: 1.0
83
+ log_every_n_steps: 50
84
+ accelerator: auto
85
+ strategy: null
86
+ sync_batchnorm: false
87
+ precision: 32
88
+ enable_model_summary: true
89
+ num_sanity_val_steps: 0
90
+ profiler: null
91
+ benchmark: false
92
+ deterministic: false
93
+ reload_dataloaders_every_n_epochs: 0
94
+ auto_lr_find: false
95
+ replace_sampler_ddp: true
96
+ detect_anomaly: false
97
+ auto_scale_batch_size: false
98
+ plugins: null
99
+ move_metrics_to_cpu: false
100
+ multiple_trainloader_mode: max_size_cycle
cfa/mvtec/bottle/run/weights/openvino/metadata.json ADDED
@@ -0,0 +1,52 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "task": "segmentation",
3
+ "transform": {
4
+ "__version__": "1.3.0",
5
+ "transform": {
6
+ "__class_fullname__": "Compose",
7
+ "p": 1.0,
8
+ "transforms": [
9
+ {
10
+ "__class_fullname__": "Resize",
11
+ "always_apply": true,
12
+ "p": 1,
13
+ "height": 224,
14
+ "width": 224,
15
+ "interpolation": 1
16
+ },
17
+ {
18
+ "__class_fullname__": "Normalize",
19
+ "always_apply": false,
20
+ "p": 1.0,
21
+ "mean": [
22
+ 0.485,
23
+ 0.456,
24
+ 0.406
25
+ ],
26
+ "std": [
27
+ 0.229,
28
+ 0.224,
29
+ 0.225
30
+ ],
31
+ "max_pixel_value": 255.0
32
+ },
33
+ {
34
+ "__class_fullname__": "ToTensorV2",
35
+ "always_apply": true,
36
+ "p": 1.0,
37
+ "transpose_mask": false
38
+ }
39
+ ],
40
+ "bbox_params": null,
41
+ "keypoint_params": null,
42
+ "additional_targets": {
43
+ "image": "image",
44
+ "depth_image": "image"
45
+ }
46
+ }
47
+ },
48
+ "image_threshold": 0.363699346780777,
49
+ "pixel_threshold": 0.32865220308303833,
50
+ "min": 0.039844684302806854,
51
+ "max": 1.0947744846343994
52
+ }
cfa/mvtec/bottle/run/weights/openvino/model.mapping ADDED
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cfa/mvtec/cable/run/config_original.yaml ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ name: mvtec
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+ format: mvtec
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@@ -0,0 +1,1207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <?xml version="1.0"?>
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+ <mapping>
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+ </map>
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