Add model sidecars: BUSI.pth.config.json, BUSI.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, PROMISE12.pth.config.json, PROMISE12.pth.provenance.json, UWaterlooSkinCancer.pth.config.json, UWaterlooSkinCancer.pth.provenance.json (tools/hf_sidecars.py)

BUSI.pth.config.json

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+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

BUSI.pth.provenance.json

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+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "BUSI.pth",
+ "sha256": "16590242536911e71d6beb60e00f9a63db20ddf716752d047f85131b5bb24a71",
+ "size": 209213935,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/busi/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "busi",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 75
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (busi) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:09+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:09+00:00"
+}

COVIDQUEx.pth.config.json

@@ -0,0 +1,31 @@
+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

COVIDQUEx.pth.provenance.json

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+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "COVIDQUEx.pth",
+ "sha256": "f467abed5ee1d95199c8775279c1e970ce4473ae2ffea8153b0e07cc755897d0",
+ "size": 209213935,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/covidquex/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "covidquex",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 163
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (covidquex) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:10+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:10+00:00"
+}

DRIVE.pth.config.json

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+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

DRIVE.pth.provenance.json

@@ -0,0 +1,38 @@
+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "DRIVE.pth",
+ "sha256": "06c2251d220de354106d74d1734bd836c8b940d0b7e5960c4c9bf6f4de526177",
+ "size": 209213935,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/DRIVE/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "DRIVE",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 284
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (DRIVE) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:16+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:16+00:00"
+}

ISIC2018.pth.config.json

@@ -0,0 +1,31 @@
+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

ISIC2018.pth.provenance.json

@@ -0,0 +1,38 @@
+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "ISIC2018.pth",
+ "sha256": "4c0b84059c95aaf1b840f470bc40fafe1f80882346d9be9bbb0bdaadcabc4be5",
+ "size": 209213935,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/isic18/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "isic18",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 264
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (isic18) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:21+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:21+00:00"
+}

PROMISE12.pth.config.json

@@ -0,0 +1,31 @@
+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

PROMISE12.pth.provenance.json

@@ -0,0 +1,38 @@
+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "PROMISE12.pth",
+ "sha256": "2059ba15fff0afa56f3b7e06df5be8d19d6b8cf0fe28b0a0806fc1ddaa4fbc9b",
+ "size": 209213458,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/promise12/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "promise12",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 218
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (promise12) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:28+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:28+00:00"
+}

UWaterlooSkinCancer.pth.config.json

@@ -0,0 +1,31 @@
+{
+ "schema": "medotter/model-sidecar/v1",
+ "model": {
+  "name": "PraNet",
+  "args": {
+   "input_channel": 3,
+   "num_classes": 1
+  }
+ },
+ "inference": {
+  "size": [
+   256,
+   256
+  ],
+  "scale": 255,
+  "normalize": {
+   "mean": [
+    0.485,
+    0.456,
+    0.406
+   ],
+   "std": [
+    58.395,
+    57.12,
+    57.375
+   ]
+  },
+  "threshold": 0.5,
+  "output_select": "last"
+ }
+}

UWaterlooSkinCancer.pth.provenance.json

@@ -0,0 +1,38 @@
+{
+ "schema": "medotter/hf-sidecars-provenance/v1",
+ "repo": "MedOtter/PraNet",
+ "revision": "37b8705d9b4b1bb3847d3ac97de3c36e47e6094e",
+ "filename": "UWaterlooSkinCancer.pth",
+ "sha256": "0437d98cc12ac5de3a97c93aae4933465446cb9fc9121d99803adac7bc6289d9",
+ "size": 209213522,
+ "upstream": {
+  "repo": "FengheTan9/U-Bench",
+  "path": "PraNet/uwaterlooskincancer/checkpoint_best.pth",
+  "sha256_match": true
+ },
+ "training": {
+  "dataset_name": "uwaterlooskincancer",
+  "img_size": 256,
+  "max_epochs": 300,
+  "do_deeps": 1,
+  "model_id": 39,
+  "seed": 41,
+  "base_lr": 0.01,
+  "batch_size": 8,
+  "epoch": 85
+ },
+ "preprocessing_class": "A",
+ "intensity_written": true,
+ "reason": "class A (uwaterlooskincancer) intensity written",
+ "verification": {
+  "strict_load": "pass",
+  "device": "cpu",
+  "torch": "2.13.0+cpu",
+  "medotter": "0.1.0",
+  "parameters": 52054887,
+  "intensity_overridden_for_probe": [],
+  "verified_at": "2026-09-06T21:41:34+00:00"
+ },
+ "generator": "tools/hf_sidecars.py",
+ "generated_at": "2026-09-06T21:41:34+00:00"
+}