Add ONNX graphs: KvasirSEG.onnx, KvasirSEG.onnx.config.json, KvasirSEG.onnx.provenance.json (tools/hf_onnx_export.py)

KvasirSEG.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58b0c44ad64b7ba3bcc96a46ebe9f4b8a623cbff611f7589e10295dc2f8bc5d6
+size 88217993

KvasirSEG.onnx.config.json

@@ -0,0 +1,30 @@
+{
+  "schema": "medotter/model-sidecar/v1",
+  "model": {
+    "graph": "onnx",
+    "args": {
+      "input_channel": 3,
+      "num_classes": 1
+    }
+  },
+  "inference": {
+    "normalize": {
+      "mean": [
+        0.485,
+        0.456,
+        0.406
+      ],
+      "std": [
+        0.229,
+        0.224,
+        0.225
+      ]
+    },
+    "scale": 255.0,
+    "size": [
+      256,
+      256
+    ],
+    "threshold": 0.5
+  }
+}

KvasirSEG.onnx.provenance.json

@@ -0,0 +1,244 @@
+{
+  "schema": "medotter/graph-provenance/v1",
+  "source": {
+    "file": "KvasirSEG.pth",
+    "sha256": "018dec5209664dea5b0a260d28401b08aa7a6d84866a0a923113cb69f10274bf",
+    "reference": "KvasirSEG.pth",
+    "model": "MSLAU_Net",
+    "declaration_source": "sidecar",
+    "declaration": [
+      {
+        "file": "KvasirSEG.pth.config.json",
+        "sha256": "aff31ee870a162f916d3747da8ffc3c107899fa6ee4fbc09c70a139e387e80b1"
+      }
+    ],
+    "float32_vs_float64": {
+      "shape": [
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+        3,
+        256,
+        256
+      ],
+      "torch": "ok",
+      "float64": "ok",
+      "threads": 6,
+      "max_abs_diff": 2.8276445668495853e-05,
+      "scale": 14.522411660690986,
+      "rel_diff": 1.9470902167739844e-06,
+      "kernel_noise_rel": 1.3133839936185298e-06
+    }
+  },
+  "graph": {
+    "kind": "onnx",
+    "file": "KvasirSEG.onnx",
+    "sha256": "58b0c44ad64b7ba3bcc96a46ebe9f4b8a623cbff611f7589e10295dc2f8bc5d6",
+    "bytes": 88217993,
+    "opset": 17,
+    "dynamic": false,
+    "reason": "fixed_size",
+    "input": "image",
+    "output": "logits",
+    "input_channel": 3,
+    "num_classes": 1,
+    "size": [
+      256,
+      256
+    ]
+  },
+  "exporter": {
+    "api": "torch.onnx.export",
+    "name": "torchscript",
+    "dynamo": false,
+    "registered_symbolics": {
+      "aten::_convolution_mode": 17,
+      "aten::add": 17,
+      "aten::roll": 17,
+      "aten::rsub": 17,
+      "aten::sub": 17,
+      "aten::upsample_nearest2d": 17
+    },
+    "producer": "pytorch 2.13.0",
+    "torch": "2.13.0+cpu",
+    "onnx": "1.22.0",
+    "onnxruntime": "1.29.0"
+  },
+  "verification_input": {
+    "kind": "smooth_random_field",
+    "distribution": "normal",
+    "coarse_factor": 16,
+    "min_coarse": 4,
+    "interpolation": "bilinear",
+    "align_corners": false,
+    "seed": 0,
+    "pixel_domain": "uint8-range smooth field through the declaration's intensity contract",
+    "pixel_mean": 127.5,
+    "pixel_std": 45.0,
+    "through_contract": true
+  },
+  "attempts": [
+    {
+      "mode": "dynamic",
+      "exporter": "torchscript",
+      "outcome": "fell_back",
+      "reason": "fixed_size",
+      "error": null,
+      "verification": [
+        {
+          "shape": [
+            1,
+            3,
+            256,
+            256
+          ],
+          "torch": "ok",
+          "graph": "ok",
+          "max_abs_diff": 2.574920654296875e-05,
+          "scale": 14.522398948669434,
+          "rel_diff": 1.7730683913850152e-06
+        },
+        {
+          "shape": [
+            1,
+            3,
+            320,
+            320
+          ],
+          "torch": "error",
+          "graph": "error",
+          "max_abs_diff": null,
+          "scale": null,
+          "rel_diff": null,
+          "torch_error": "AssertionError: Input image size (320*320) doesn't match model (256*256).",
+          "graph_error": "Fail: [ONNXRuntimeError] : 1 : FAIL : Non-zero status code returned while running Conv node. Name:'/inner/encoder/blocks3.0/attn/dw_conv_9x9/depthwise/Conv_output_0_nchwc' Status Message: Input channels C is not equal to kernel channels * group. C: 208 kernel channels: 1 group: 64",
+          "error": "AssertionError: Input image size (320*320) doesn't match model (256*256)."
+        },
+        {
+          "shape": [
+            1,
+            3,
+            224,
+            224
+          ],
+          "torch": "error",
+          "graph": "error",
+          "max_abs_diff": null,
+          "scale": null,
+          "rel_diff": null,
+          "torch_error": "AssertionError: Input image size (224*224) doesn't match model (256*256).",
+          "graph_error": "Fail: [ONNXRuntimeError] : 1 : FAIL : Non-zero status code returned while running Conv node. Name:'/inner/encoder/blocks3.0/attn/dw_conv_9x9/depthwise/Conv_output_0_nchwc' Status Message: Input channels C is not equal to kernel channels * group. C: 8 kernel channels: 1 group: 64",
+          "error": "AssertionError: Input image size (224*224) doesn't match model (256*256)."
+        },
+        {
+          "shape": [
+            1,
+            3,
+            512,
+            512
+          ],
+          "torch": "error",
+          "graph": "error",
+          "max_abs_diff": null,
+          "scale": null,
+          "rel_diff": null,
+          "torch_error": "AssertionError: Input image size (512*512) doesn't match model (256*256).",
+          "graph_error": "Fail: [ONNXRuntimeError] : 1 : FAIL : Non-zero status code returned while running Conv node. Name:'/inner/encoder/blocks3.0/attn/dw_conv_9x9/depthwise/Conv_output_0_nchwc' Status Message: Input channels C is not equal to kernel channels * group. C: 832 kernel channels: 1 group: 64",
+          "error": "AssertionError: Input image size (512*512) doesn't match model (256*256)."
+        },
+        {
+          "shape": [
+            2,
+            3,
+            256,
+            256
+          ],
+          "torch": "ok",
+          "graph": "ok",
+          "max_abs_diff": 3.0517578125e-05,
+          "scale": 15.618277549743652,
+          "rel_diff": 1.953965667968354e-06
+        }
+      ]
+    },
+    {
+      "mode": "static",
+      "exporter": "torchscript",
+      "outcome": "kept",
+      "reason": "fixed_size",
+      "error": null,
+      "verification": [
+        {
+          "shape": [
+            1,
+            3,
+            256,
+            256
+          ],
+          "torch": "ok",
+          "graph": "ok",
+          "max_abs_diff": 2.6702880859375e-05,
+          "scale": 14.522398948669434,
+          "rel_diff": 1.838737591065942e-06
+        }
+      ]
+    }
+  ],
+  "verification": [
+    {
+      "shape": [
+        1,
+        3,
+        256,
+        256
+      ],
+      "torch": "ok",
+      "graph": "ok",
+      "max_abs_diff": 2.6702880859375e-05,
+      "scale": 14.522398948669434,
+      "rel_diff": 1.838737591065942e-06
+    }
+  ],
+  "exported_at": "2026-09-09T23:20:09+00:00",
+  "release": {
+    "repo": "MedOtter/MSLAU_Net",
+    "revision": "98e746d11981d253399348d3b051b7f3a497df79",
+    "pth_file": "KvasirSEG.pth",
+    "pth_sha256": "018dec5209664dea5b0a260d28401b08aa7a6d84866a0a923113cb69f10274bf",
+    "sidecar_sha256": "1445f651ec927f1196af8ad861bf4ef54128f23d2812ee825908fa7d98195fa6",
+    "sidecar_source": "hub",
+    "group": "checkout_only",
+    "reason": "fixed_size",
+    "dynamic_attempt": null,
+    "reference_check": {
+      "dataset": "KvasirSEG",
+      "split": "val",
+      "samples": 4,
+      "reproducible": true,
+      "status": "pass",
+      "sizes": [
+        {
+          "size": [
+            256,
+            256
+          ],
+          "predict_masks_equal": 4,
+          "pixels": 262144,
+          "disagreeing_pixels": 0,
+          "unexplained_pixels": 0,
+          "max_abs_diff": 0.000118255615234375,
+          "scale": 38.82075119018555,
+          "rel_diff": 3.0461959547107306e-06,
+          "float32_vs_float64": {
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+            "scale": 38.820765577347814,
+            "rel_diff": 2.6595372411884293e-06,
+            "samples": 4,
+            "of": 4,
+            "complete": true
+          }
+        }
+      ]
+    },
+    "tool": "tools/hf_onnx_export.py",
+    "stamped_at": "2026-09-09T23:20:27+00:00"
+  }
+}