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FAT_Net

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Add model sidecars: ACDC.pth.config.json, ACDC.pth.provenance.json, COVIDQUEx.pth.config.json, COVIDQUEx.pth.provenance.json, DRIVE.pth.config.json, DRIVE.pth.provenance.json, ISIC2018.pth.config.json, ISIC2018.pth.provenance.json, KvasirSEG.pth.config.json, KvasirSEG.pth.provenance.json, PROMISE12.pth.config.json, PROMISE12.pth.provenance.json, UWaterlooSkinCancer.pth.config.json, UWaterlooSkinCancer.pth.provenance.json (tools/hf_sidecars.py)

Browse files
Files changed (14) hide show
  1. ACDC.pth.config.json +16 -0
  2. ACDC.pth.provenance.json +43 -0
  3. COVIDQUEx.pth.config.json +30 -0
  4. COVIDQUEx.pth.provenance.json +38 -0
  5. DRIVE.pth.config.json +30 -0
  6. DRIVE.pth.provenance.json +38 -0
  7. ISIC2018.pth.config.json +30 -0
  8. ISIC2018.pth.provenance.json +38 -0
  9. KvasirSEG.pth.config.json +30 -0
  10. KvasirSEG.pth.provenance.json +38 -0
  11. PROMISE12.pth.config.json +30 -0
  12. PROMISE12.pth.provenance.json +38 -0
  13. UWaterlooSkinCancer.pth.config.json +30 -0
  14. UWaterlooSkinCancer.pth.provenance.json +38 -0
ACDC.pth.config.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 4
8
+ }
9
+ },
10
+ "inference": {
11
+ "size": [
12
+ 224,
13
+ 224
14
+ ]
15
+ }
16
+ }
ACDC.pth.provenance.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
5
+ "filename": "ACDC.pth",
6
+ "sha256": "bbd271405b99d5e077f9ecd1e8998f5351a77653a5d3f492d15692559e19e01a",
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+ "size": 115293363,
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+ "upstream": {
9
+ "repo": "FengheTan9/U-Bench",
10
+ "path": "FAT_Net/ACDC/checkpoint_best.pth",
11
+ "sha256_match": true
12
+ },
13
+ "training": {
14
+ "dataset_name": "ACDC",
15
+ "img_size": 224,
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+ "max_epochs": 300,
17
+ "max_iterations": 30000,
18
+ "do_deeps": 0,
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+ "model_id": 32,
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+ "seed": 41,
21
+ "base_lr": 0.01,
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+ "batch_size": 8,
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+ "epoch": 200,
24
+ "best_performance": 0.9150855176999716
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+ },
26
+ "preprocessing_class": "C",
27
+ "intensity_written": false,
28
+ "reason": "class C (ACDC): per-volume min-max to [-1, 1], inexpressible as scale/window; no intensity keys are written (the eval door refuses until declared)",
29
+ "verification": {
30
+ "strict_load": "pass",
31
+ "device": "cpu",
32
+ "torch": "2.13.0+cpu",
33
+ "medotter": "0.1.0",
34
+ "parameters": 28759524,
35
+ "intensity_overridden_for_probe": [
36
+ "input_scale",
37
+ "normalize"
38
+ ],
39
+ "verified_at": "2026-09-06T21:09:23+00:00"
40
+ },
41
+ "generator": "tools/hf_sidecars.py",
42
+ "generated_at": "2026-09-06T21:09:23+00:00"
43
+ }
COVIDQUEx.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
8
+ }
9
+ },
10
+ "inference": {
11
+ "size": [
12
+ 224,
13
+ 224
14
+ ],
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+ "scale": 255,
16
+ "normalize": {
17
+ "mean": [
18
+ 0.485,
19
+ 0.456,
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+ 0.406
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+ ],
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+ "std": [
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+ 58.395,
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+ 57.12,
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+ 57.375
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+ ]
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+ },
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+ "threshold": 0.5
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+ }
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+ }
COVIDQUEx.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
5
+ "filename": "COVIDQUEx.pth",
6
+ "sha256": "5171c78d17a73dc11d312bddcc6ea71f61b8e224f4653efbf7d35bf1d8e1f3a3",
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+ "size": 115289587,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
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+ "path": "FAT_Net/covidquex/checkpoint_best.pth",
11
+ "sha256_match": true
12
+ },
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+ "training": {
14
+ "dataset_name": "covidquex",
15
+ "img_size": 224,
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+ "max_epochs": 300,
17
+ "do_deeps": 0,
18
+ "model_id": 32,
19
+ "seed": 41,
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+ "base_lr": 0.01,
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+ "batch_size": 8,
22
+ "epoch": 118
23
+ },
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+ "preprocessing_class": "A",
25
+ "intensity_written": true,
26
+ "reason": "class A (covidquex) intensity written",
27
+ "verification": {
28
+ "strict_load": "pass",
29
+ "device": "cpu",
30
+ "torch": "2.13.0+cpu",
31
+ "medotter": "0.1.0",
32
+ "parameters": 28758657,
33
+ "intensity_overridden_for_probe": [],
34
+ "verified_at": "2026-09-06T21:09:31+00:00"
35
+ },
36
+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:31+00:00"
38
+ }
DRIVE.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
8
+ }
9
+ },
10
+ "inference": {
11
+ "size": [
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+ 224,
13
+ 224
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+ ],
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+ "scale": 255,
16
+ "normalize": {
17
+ "mean": [
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+ 0.485,
19
+ 0.456,
20
+ 0.406
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+ ],
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+ "std": [
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+ 58.395,
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+ 57.12,
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+ 57.375
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+ ]
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+ },
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+ "threshold": 0.5
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+ }
30
+ }
DRIVE.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
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+ "filename": "DRIVE.pth",
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+ "sha256": "e09aeaf1242b42bf6e4acdee9516b799d2f9e8b272b8c526d3a39bb8a40bd532",
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+ "size": 115289587,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
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+ "path": "FAT_Net/DRIVE/checkpoint_best.pth",
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+ "sha256_match": true
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+ },
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+ "training": {
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+ "dataset_name": "DRIVE",
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+ "img_size": 224,
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+ "max_epochs": 300,
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+ "do_deeps": 0,
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+ "model_id": 32,
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+ "seed": 41,
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+ "base_lr": 0.01,
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+ "batch_size": 8,
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+ "epoch": 292
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+ },
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+ "preprocessing_class": "A",
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+ "intensity_written": true,
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+ "reason": "class A (DRIVE) intensity written",
27
+ "verification": {
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+ "strict_load": "pass",
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+ "device": "cpu",
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+ "torch": "2.13.0+cpu",
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+ "medotter": "0.1.0",
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+ "parameters": 28758657,
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+ "intensity_overridden_for_probe": [],
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+ "verified_at": "2026-09-06T21:09:36+00:00"
35
+ },
36
+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:36+00:00"
38
+ }
ISIC2018.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
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+ }
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+ },
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+ "inference": {
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+ "size": [
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+ 224,
13
+ 224
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+ ],
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+ "scale": 255,
16
+ "normalize": {
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+ "mean": [
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+ 0.485,
19
+ 0.456,
20
+ 0.406
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+ ],
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+ "std": [
23
+ 58.395,
24
+ 57.12,
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+ 57.375
26
+ ]
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+ },
28
+ "threshold": 0.5
29
+ }
30
+ }
ISIC2018.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
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+ "filename": "ISIC2018.pth",
6
+ "sha256": "96a26cb61b7a348e5f5c15bafa2071ad3acfcc11f3db3b81749edb9db5276bdc",
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+ "size": 115289587,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
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+ "path": "FAT_Net/isic18/checkpoint_best.pth",
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+ "sha256_match": true
12
+ },
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+ "training": {
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+ "dataset_name": "isic18",
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+ "img_size": 224,
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+ "max_epochs": 300,
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+ "do_deeps": 0,
18
+ "model_id": 32,
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+ "seed": 41,
20
+ "base_lr": 0.01,
21
+ "batch_size": 8,
22
+ "epoch": 225
23
+ },
24
+ "preprocessing_class": "A",
25
+ "intensity_written": true,
26
+ "reason": "class A (isic18) intensity written",
27
+ "verification": {
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+ "strict_load": "pass",
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+ "device": "cpu",
30
+ "torch": "2.13.0+cpu",
31
+ "medotter": "0.1.0",
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+ "parameters": 28758657,
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+ "intensity_overridden_for_probe": [],
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+ "verified_at": "2026-09-06T21:09:42+00:00"
35
+ },
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+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:42+00:00"
38
+ }
KvasirSEG.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
8
+ }
9
+ },
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+ "inference": {
11
+ "size": [
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+ 224,
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+ 224
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+ ],
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+ "scale": 255,
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+ "normalize": {
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+ "mean": [
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+ 0.485,
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+ 0.456,
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+ 0.406
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+ ],
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+ "std": [
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+ 0.229,
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+ 0.224,
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+ 0.225
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+ ]
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+ },
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+ "threshold": 0.5
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+ }
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+ }
KvasirSEG.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "schema": "medotter/hf-sidecars-provenance/v1",
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+ "repo": "MedOtter/FAT_Net",
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+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
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+ "filename": "KvasirSEG.pth",
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+ "sha256": "1d6f60d0234780f82464dabb4a2b39cb18dcaba4aab0e0056ba82186c6bef496",
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+ "size": 115289651,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
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+ "path": "FAT_Net/Kvasir-SEG/checkpoint_best.pth",
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+ "sha256_match": true
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+ },
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+ "training": {
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+ "dataset_name": "Kvasir-SEG",
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+ "img_size": 224,
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+ "max_epochs": 300,
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+ "do_deeps": 0,
18
+ "model_id": 32,
19
+ "seed": 41,
20
+ "base_lr": 0.01,
21
+ "batch_size": 8,
22
+ "epoch": 198
23
+ },
24
+ "preprocessing_class": "B",
25
+ "intensity_written": true,
26
+ "reason": "class B (Kvasir-SEG) intensity written",
27
+ "verification": {
28
+ "strict_load": "pass",
29
+ "device": "cpu",
30
+ "torch": "2.13.0+cpu",
31
+ "medotter": "0.1.0",
32
+ "parameters": 28758657,
33
+ "intensity_overridden_for_probe": [],
34
+ "verified_at": "2026-09-06T21:09:48+00:00"
35
+ },
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+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:48+00:00"
38
+ }
PROMISE12.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
8
+ }
9
+ },
10
+ "inference": {
11
+ "size": [
12
+ 224,
13
+ 224
14
+ ],
15
+ "scale": 255,
16
+ "normalize": {
17
+ "mean": [
18
+ 0.485,
19
+ 0.456,
20
+ 0.406
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+ ],
22
+ "std": [
23
+ 58.395,
24
+ 57.12,
25
+ 57.375
26
+ ]
27
+ },
28
+ "threshold": 0.5
29
+ }
30
+ }
PROMISE12.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
5
+ "filename": "PROMISE12.pth",
6
+ "sha256": "5206cd82eaf562b94807c4ca420198862fbe450884dca938eba8a4017e0a0eb2",
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+ "size": 115289174,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
10
+ "path": "FAT_Net/promise12/checkpoint_best.pth",
11
+ "sha256_match": true
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+ },
13
+ "training": {
14
+ "dataset_name": "promise12",
15
+ "img_size": 224,
16
+ "max_epochs": 300,
17
+ "do_deeps": 0,
18
+ "model_id": 32,
19
+ "seed": 41,
20
+ "base_lr": 0.01,
21
+ "batch_size": 8,
22
+ "epoch": 149
23
+ },
24
+ "preprocessing_class": "A",
25
+ "intensity_written": true,
26
+ "reason": "class A (promise12) intensity written",
27
+ "verification": {
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+ "strict_load": "pass",
29
+ "device": "cpu",
30
+ "torch": "2.13.0+cpu",
31
+ "medotter": "0.1.0",
32
+ "parameters": 28758657,
33
+ "intensity_overridden_for_probe": [],
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+ "verified_at": "2026-09-06T21:09:52+00:00"
35
+ },
36
+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:52+00:00"
38
+ }
UWaterlooSkinCancer.pth.config.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/model-sidecar/v1",
3
+ "model": {
4
+ "name": "FAT_Net",
5
+ "args": {
6
+ "input_channel": 3,
7
+ "num_classes": 1
8
+ }
9
+ },
10
+ "inference": {
11
+ "size": [
12
+ 224,
13
+ 224
14
+ ],
15
+ "scale": 255,
16
+ "normalize": {
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+ "mean": [
18
+ 0.485,
19
+ 0.456,
20
+ 0.406
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+ ],
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+ "std": [
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+ 58.395,
24
+ 57.12,
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+ 57.375
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+ ]
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+ },
28
+ "threshold": 0.5
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+ }
30
+ }
UWaterlooSkinCancer.pth.provenance.json ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "schema": "medotter/hf-sidecars-provenance/v1",
3
+ "repo": "MedOtter/FAT_Net",
4
+ "revision": "87ece27e66146191b0e29c28357a105a7d0a6b31",
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+ "filename": "UWaterlooSkinCancer.pth",
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+ "sha256": "dd27470fae880bd44c029ad325d13d2688c948e127722648496d442ed9a70202",
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+ "size": 115289174,
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+ "upstream": {
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+ "repo": "FengheTan9/U-Bench",
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+ "path": "FAT_Net/uwaterlooskincancer/checkpoint_best.pth",
11
+ "sha256_match": true
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+ },
13
+ "training": {
14
+ "dataset_name": "uwaterlooskincancer",
15
+ "img_size": 224,
16
+ "max_epochs": 300,
17
+ "do_deeps": 0,
18
+ "model_id": 32,
19
+ "seed": 41,
20
+ "base_lr": 0.01,
21
+ "batch_size": 8,
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+ "epoch": 69
23
+ },
24
+ "preprocessing_class": "A",
25
+ "intensity_written": true,
26
+ "reason": "class A (uwaterlooskincancer) intensity written",
27
+ "verification": {
28
+ "strict_load": "pass",
29
+ "device": "cpu",
30
+ "torch": "2.13.0+cpu",
31
+ "medotter": "0.1.0",
32
+ "parameters": 28758657,
33
+ "intensity_overridden_for_probe": [],
34
+ "verified_at": "2026-09-06T21:09:57+00:00"
35
+ },
36
+ "generator": "tools/hf_sidecars.py",
37
+ "generated_at": "2026-09-06T21:09:57+00:00"
38
+ }