Upload 44 files

.gitattributes

@@ -46,3 +46,7 @@ assets/not_illuminated/4.jpg filter=lfs diff=lfs merge=lfs -text
 assets/not_illuminated/5.png filter=lfs diff=lfs merge=lfs -text
 assets/not_illuminated/6.jpg filter=lfs diff=lfs merge=lfs -text
 assets/odil-logo.png filter=lfs diff=lfs merge=lfs -text
+mobilenetv2/onnx/model.onnx.data filter=lfs diff=lfs merge=lfs -text
+mobilenetv3_large/onnx/model.onnx.data filter=lfs diff=lfs merge=lfs -text
+mobilenetv3_small/onnx/model.onnx.data filter=lfs diff=lfs merge=lfs -text
+mobilevitv2/onnx/model.onnx.data filter=lfs diff=lfs merge=lfs -text

mobilenetv2/README.md

@@ -0,0 +1,13 @@
+# Run artefacts: run_20260228_173634_timm_mobilenetv2_100.ra_in1k
+
+This folder is **uploadable as-is** to the Hugging Face Hub.
+
+## Files
+- `onnx/model.onnx`: single-file ONNX model
+- `preprocess.json`: resize/normalize info
+- `inference_config.json`: threshold + labels + IO names
+- `metrics_val.json`, `metrics_test.json`
+- `pr_curve_val.png`, `roc_curve_val.png`
+
+## Quick inference (Python)
+Use `scripts/infer_local.py` or `scripts/infer_hf.py`.

mobilenetv2/config_resolved.yml

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+run:
+  out_root: artefacts
+  name: null
+  seed: 42
+  device: auto
+  num_workers: 0
+  early_stopping_patience: 5
+  metric_for_best: ap
+data:
+  source: local
+  local:
+    root: dataset
+    splits:
+      train: train
+      val: val
+      test: test
+    classes:
+      negative: non_illustration
+      positive: illustration
+  hf:
+    dataset: null
+    image_column: image
+    label_column: label
+    splits:
+      train: train
+      val: validation
+      test: test
+    label_names:
+    - '0'
+    - '1'
+model:
+  backend: timm
+  name: mobilenetv2_100.ra_in1k
+  pretrained: true
+  freeze_backbone: false
+preprocess:
+  mode: auto
+  img_size: 224
+  mean:
+  - 0.485
+  - 0.456
+  - 0.406
+  std:
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+  - 0.224
+  - 0.225
+  augment:
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+    hflip: true
+    rotation_deg: 5
+    jitter:
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+      contrast: 0.12
+      saturation: 0.08
+      hue: 0.02
+train:
+  epochs: 15
+  batch_size: 32
+  lr: 3e-4
+export:
+  opset: 18

mobilenetv2/history.json

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mobilenetv2/inference_config.json

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+}

mobilenetv2/metrics_test.json

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+}

mobilenetv2/metrics_val.json

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mobilenetv2/onnx/model.onnx

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mobilenetv2/onnx/model.onnx.data

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mobilenetv2/preprocess.json

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+{
+  "img_size": 224,
+  "mean": [
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+    0.456,
+    0.406
+  ],
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+  "labels": [
+    "non_illuminated",
+    "illuminated"
+  ]
+}

mobilenetv3_large/README.md

@@ -0,0 +1,13 @@
+# Run artefacts: run_20260228_171950_timm_mobilenetv3_large_100.ra_in1k
+
+This folder is **uploadable as-is** to the Hugging Face Hub.
+
+## Files
+- `onnx/model.onnx`: single-file ONNX model
+- `preprocess.json`: resize/normalize info
+- `inference_config.json`: threshold + labels + IO names
+- `metrics_val.json`, `metrics_test.json`
+- `pr_curve_val.png`, `roc_curve_val.png`
+
+## Quick inference (Python)
+Use `scripts/infer_local.py` or `scripts/infer_hf.py`.

mobilenetv3_large/config_resolved.yml

@@ -0,0 +1,61 @@
+run:
+  out_root: artefacts
+  name: null
+  seed: 42
+  device: auto
+  num_workers: 0
+  early_stopping_patience: 5
+  metric_for_best: ap
+data:
+  source: local
+  local:
+    root: dataset
+    splits:
+      train: train
+      val: val
+      test: test
+    classes:
+      negative: non_illustration
+      positive: illustration
+  hf:
+    dataset: null
+    image_column: image
+    label_column: label
+    splits:
+      train: train
+      val: validation
+      test: test
+    label_names:
+    - '0'
+    - '1'
+model:
+  backend: timm
+  name: mobilenetv3_large_100.ra_in1k
+  pretrained: true
+  freeze_backbone: false
+preprocess:
+  mode: auto
+  img_size: 224
+  mean:
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+  - 0.456
+  - 0.406
+  std:
+  - 0.229
+  - 0.224
+  - 0.225
+  augment:
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+    hflip: true
+    rotation_deg: 5
+    jitter:
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+      contrast: 0.12
+      saturation: 0.08
+      hue: 0.02
+train:
+  epochs: 15
+  batch_size: 32
+  lr: 3e-4
+export:
+  opset: 18

mobilenetv3_large/history.json

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mobilenetv3_large/inference_config.json

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+{
+  "backend": "timm",
+  "model_name": "mobilenetv3_large_100.ra_in1k",
+  "img_size": 224,
+  "mean": [
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+  }
+}

mobilenetv3_large/metrics_test.json

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+  "auc": 0.9917953667953668,
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+}

mobilenetv3_large/metrics_val.json

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+  "threshold_best_f1_score": 0.9999999999995
+}

mobilenetv3_large/onnx/model.onnx

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+size 17138155

mobilenetv3_large/onnx/model.onnx.data

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mobilenetv3_large/preprocess.json

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+{
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+    0.456,
+    0.406
+  ],
+  "std": [
+    0.229,
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+    0.225
+  ],
+  "labels": [
+    "non_illuminated",
+    "illuminated"
+  ]
+}

mobilenetv3_small/README.md

@@ -0,0 +1,13 @@
+# Run artefacts: run_20260228_165352_timm_mobilenetv3_small_100.lamb_in1k
+
+This folder is **uploadable as-is** to the Hugging Face Hub.
+
+## Files
+- `onnx/model.onnx`: single-file ONNX model
+- `preprocess.json`: resize/normalize info
+- `inference_config.json`: threshold + labels + IO names
+- `metrics_val.json`, `metrics_test.json`
+- `pr_curve_val.png`, `roc_curve_val.png`
+
+## Quick inference (Python)
+Use `scripts/infer_local.py` or `scripts/infer_hf.py`.

mobilenetv3_small/config_resolved.yml

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+run:
+  out_root: artefacts
+  name: null
+  seed: 42
+  device: auto
+  num_workers: 0
+  early_stopping_patience: 5
+  metric_for_best: ap
+data:
+  source: local
+  local:
+    root: dataset
+    splits:
+      train: train
+      val: val
+      test: test
+    classes:
+      negative: non_illustration
+      positive: illustration
+  hf:
+    dataset: null
+    image_column: image
+    label_column: label
+    splits:
+      train: train
+      val: validation
+      test: test
+    label_names:
+    - non_illustration
+    - illustration
+model:
+  backend: timm
+  name: mobilenetv3_small_100.lamb_in1k
+  pretrained: true
+  freeze_backbone: false
+preprocess:
+  mode: auto
+  img_size: 224
+  mean:
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+  - 0.456
+  - 0.406
+  std:
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+  - 0.224
+  - 0.225
+  augment:
+    enabled: true
+    hflip: true
+    rotation_deg: 5
+    jitter:
+      brightness: 0.12
+      contrast: 0.12
+      saturation: 0.08
+      hue: 0.02
+train:
+  epochs: 15
+  batch_size: 32
+  lr: 3e-4
+export:
+  opset: 18

mobilenetv3_small/history.json

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mobilenetv3_small/inference_config.json

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+{
+  "backend": "timm",
+  "model_name": "mobilenetv3_small_100.lamb_in1k",
+  "img_size": 224,
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+        ]
+      }
+    }
+  }
+}

mobilenetv3_small/metrics_test.json

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+{
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+        [
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+        ]
+      ]
+    }
+  }
+}

mobilenetv3_small/metrics_val.json

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+{
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+  },
+  "threshold_best_f1_score": 0.991150442477376
+}

mobilenetv3_small/onnx/model.onnx

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+size 6375702

mobilenetv3_small/onnx/model.onnx.data

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+size 6094848

mobilenetv3_small/preprocess.json

@@ -0,0 +1,17 @@
+{
+  "img_size": 224,
+  "mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "labels": [
+    "non_illuminated",
+    "illuminated"
+  ]
+}

mobilevitv2/README.md

@@ -0,0 +1,13 @@
+# Run artefacts: run_20260228_175756_transformers_apple__mobilevitv2-1.0-imagenet1k-256
+
+This folder is **uploadable as-is** to the Hugging Face Hub.
+
+## Files
+- `onnx/model.onnx`: single-file ONNX model
+- `preprocess.json`: resize/normalize info
+- `inference_config.json`: threshold + labels + IO names
+- `metrics_val.json`, `metrics_test.json`
+- `pr_curve_val.png`, `roc_curve_val.png`
+
+## Quick inference (Python)
+Use `scripts/infer_local.py` or `scripts/infer_hf.py`.

mobilevitv2/config_resolved.yml

@@ -0,0 +1,62 @@
+run:
+  out_root: artefacts
+  name: null
+  seed: 42
+  device: auto
+  num_workers: 0
+  early_stopping_patience: 5
+  metric_for_best: ap
+data:
+  source: local
+  local:
+    root: dataset
+    splits:
+      train: train
+      val: val
+      test: test
+    classes:
+      negative: non_illustration
+      positive: illustration
+  hf:
+    dataset: null
+    image_column: image
+    label_column: label
+    splits:
+      train: train
+      val: validation
+      test: test
+    label_names:
+    - '0'
+    - '1'
+model:
+  backend: transformers
+  name: apple/mobilevitv2-1.0-imagenet1k-256
+  pretrained: true
+  freeze_backbone: false
+preprocess:
+  processor_use_fast: false
+  mode: auto
+  img_size: 288
+  mean:
+  - 0.485
+  - 0.456
+  - 0.406
+  std:
+  - 0.229
+  - 0.224
+  - 0.225
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+  batch_size: 32
+  lr: 5e-5
+export:
+  opset: 18

mobilevitv2/history.json

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mobilevitv2/inference_config.json

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+}

mobilevitv2/metrics_test.json

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+}

mobilevitv2/metrics_val.json

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+}

mobilevitv2/onnx/model.onnx

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mobilevitv2/onnx/model.onnx.data

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+oid sha256:086d3a9a704ba63008d524d86dabf78978119db0c620c61615c38794543879a9
+size 17563648

mobilevitv2/preprocess.json

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+{
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+}