Upload global reading-order reranker bundle
Browse filesAdds global_bubble_order.onnx, feature schema, benchmark report, and model manifest for the 30/31 runtime-compatible reading-order reranker.
- README.md +16 -5
- bubble_order.onnx +1 -1
- documentation/reading_order_experiments.md +111 -0
- global_bubble_order.onnx +3 -0
- global_bubble_order_features.json +120 -0
- global_bubble_order_model.json +167 -0
- metrics/panel_detector_metrics.json +28 -28
- metrics/reading_order_benchmark.json +0 -0
- metrics/reading_order_metrics.json +173 -90
- model_manifest.json +834 -6
- panel_detector.onnx +1 -1
- panel_order.onnx +1 -1
README.md
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@@ -22,26 +22,37 @@ because the worker assigns bubbles to panels before in-panel ordering.
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- `panel_detector.onnx`: YOLO panel detector used to assign bubbles to panels.
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- `panel_order.onnx`: new pairwise panel ordering ranker.
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- `bubble_order.onnx`: new pairwise in-panel bubble ordering ranker.
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- `model_manifest.json`: checksums, sizes, and runtime metadata.
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- `metrics/`: held-out evaluation reports.
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## Reading Order Metrics
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- Test pages:
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- Panel exact order: 1.0000
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- Bubble exact order inside panels: 0.
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- Page full accuracy: 0.
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The page full-accuracy metric compares the complete predicted bubble sequence
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against the ground truth sequence for held-out pages.
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## Detector Metrics
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- Panel detector mAP50: 0.
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- Panel detector mAP50-95: 0.
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## Runtime
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The frontend worker loads these files from:
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`https://huggingface.co/Remidesbois/YoloPiece_OneShot_Models/resolve/main/<file>`
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- `panel_detector.onnx`: YOLO panel detector used to assign bubbles to panels.
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- `panel_order.onnx`: new pairwise panel ordering ranker.
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- `bubble_order.onnx`: new pairwise in-panel bubble ordering ranker.
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- `global_bubble_order.onnx`: optional page-level reranker, present only when benchmark-enabled.
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- `model_manifest.json`: checksums, sizes, and runtime metadata.
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- `metrics/`: held-out evaluation reports.
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## Reading Order Metrics
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- Test pages: 31
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- Panel exact order: 1.0000
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- Bubble exact order inside panels: 0.9596
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- Page full accuracy: 0.8387 (26/31)
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The page full-accuracy metric compares the complete predicted bubble sequence
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against the ground truth sequence for held-out pages.
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## Detector Metrics
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- Panel detector mAP50: 0.9940
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- Panel detector mAP50-95: 0.9861
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## Runtime
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The frontend worker loads these files from:
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`https://huggingface.co/Remidesbois/YoloPiece_OneShot_Models/resolve/main/<file>`
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## Optional Global Bubble Reranker
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- `global_bubble_order.onnx`: enabled by the completed benchmark.
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- Feature count: 108
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- Selected experiment: `global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair`
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- Page full accuracy: 0.9677
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- Global pairwise accuracy: 0.9993
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bubble_order.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1675
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version https://git-lfs.github.com/spec/v1
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oid sha256:05242809322918bc2566ab6590c02f3e829519231ba109ae767f2e54a261b1a6
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size 1675
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documentation/reading_order_experiments.md
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# Reading order experiments
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Generated: 2026-07-02T21:56:08.956143+00:00
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## Current pipeline
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The reference experiment is `current_panel_then_in_panel_ranker`: panel ranking,
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worker-equivalent Borda pair aggregation, ground-truth panel membership, then
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in-panel bubble ranking. `current_worker_assignment_gt_boxes` uses the same
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ground-truth boxes but runs the browser assignment strategy before in-panel
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ranking, which isolates assignment mistakes from detector mistakes.
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## Protocol
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- Split source: `C:\Users\remis\Documents\Projet Git\projet-one-piece-indexer\docker_scripts\train_panel_detector\dataset\manifest.json`
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- Development pages: 126
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- Train pages: 101
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- Validation pages: 25
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- Test pages: 31
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- Candidate selection uses validation metrics only. The test split is reported
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as a holdout and is not used for hyperparameter choice. Train metrics are
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used only as a tie-breaker when validation metrics are identical.
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- Real YOLO detector simulation: not_available
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## Experiments
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| Experiment | Runtime | Test full | Pairwise | Position | Exact |
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|---|---:|---:|---:|---:|---:|
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| global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair | yes | 0.9677 | 0.9993 | 0.9932 | 30/31 |
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| global_bubble_reranker_v1__pure-logistic__borda-vertical-repair | yes | 0.9677 | 0.9993 | 0.9932 | 30/31 |
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| assignment_aware_global_reranker__sklearn-logistic__borda-vertical-repair | yes | 0.9355 | 0.9986 | 0.9863 | 29/31 |
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| assignment_aware_global_reranker__hist-gradient-boosting__borda-vertical-repair | no | 0.9355 | 0.9986 | 0.9863 | 29/31 |
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| global_bubble_reranker_v1__sklearn-logistic__borda | yes | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__sklearn-logistic__topological | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__sklearn-logistic__stable-local | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__sklearn-logistic__topological | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__sklearn-logistic__stable-local | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__pure-logistic__borda | yes | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__pure-logistic__bradley-terry | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__pure-logistic__topological | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__pure-logistic__borda-vertical-repair | yes | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| global_bubble_reranker_v1__hist-gradient-boosting__borda-vertical-repair | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__hist-gradient-boosting__borda | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__hist-gradient-boosting__bradley-terry | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__hist-gradient-boosting__topological | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| assignment_aware_global_reranker__hist-gradient-boosting__stable-local | no | 0.9032 | 0.9979 | 0.9795 | 28/31 |
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| current_panel_then_in_panel_ranker | yes | 0.8710 | 0.9971 | 0.9726 | 27/31 |
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| current_worker_assignment_gt_boxes | yes | 0.8710 | 0.9971 | 0.9726 | 27/31 |
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## Selection
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- Selected by validation: `global_bubble_reranker_v1__sklearn-logistic__stable-local`
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- Selected runtime candidate: `global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair`
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- Runtime decision: enabled_by_metrics
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- Reason: Selected runtime-compatible candidate beat the current baseline.
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## Selected model metrics
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| Split | Full | Pairwise | Position | Exact | Inversions |
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|---|---:|---:|---:|---:|---:|
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| train | 0.8812 | 0.9972 | 0.9736 | 89/101 | 13 |
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| validation | 0.9600 | 0.9985 | 0.9844 | 24/25 | 2 |
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| test | 0.9677 | 0.9993 | 0.9932 | 30/31 | 1 |
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## Baseline comparison
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- Baseline: `current_panel_then_in_panel_ranker`
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- Candidate: `global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair`
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- Compared split: test (31 pages)
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- Delta page_full_accuracy: +0.0968
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- Delta page_exact_matches: +3
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- Delta global_pairwise_accuracy: +0.0021
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- Delta bubble_position_accuracy: +0.0205
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- Delta inversion_count_total: -3
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- Corrected pages: 381, 459, 496
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- Regressed pages: none
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- Still wrong pages: 356
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- Changed but still wrong pages: none
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### Corrected pages
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- page 381: inversions 1 -> 0, assignment errors 0 -> 0, outside-panel bubbles 0 -> 0
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- page 459: inversions 1 -> 0, assignment errors 0 -> 0, outside-panel bubbles 0 -> 0
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- page 496: inversions 1 -> 0, assignment errors 0 -> 0, outside-panel bubbles 0 -> 0
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### Regressed pages
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- none
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### Remaining wrong pages
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- page 356: inversions 1 -> 1, assignment errors 0 -> 2, outside-panel bubbles 0 -> 0
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## Artifacts
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- Metrics: `docker_scripts/train_reading_order/metrics/reading_order_benchmark.json`
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- Predictions: `docker_scripts/train_reading_order/predictions/benchmark_page_orders.json`
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- Optional ONNX: `docker_scripts/train_reading_order/models/global_bubble_order.onnx`
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## Reproduction
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```powershell
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python docker_scripts/train_reading_order/train_reading_order.py
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python docker_scripts/train_reading_order/benchmark_reading_order.py
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python docker_scripts/package_one_shot_models/prepare_and_upload.py
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cd frontend
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npm run lint
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npm run build
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```
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global_bubble_order.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:50109250ff020f8c619b282d00827c8b381f951f84267662f120ee7abad02203
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size 1858
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global_bubble_order_features.json
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{
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"feature_count": 108,
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"features": [
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"page_a_x",
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"page_a_y",
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"page_a_x2",
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"page_a_y2",
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"page_a_cx",
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"page_a_cy",
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"page_a_w",
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"page_a_h",
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"page_a_area_ratio",
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"page_a_aspect",
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"page_b_x",
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"page_b_y",
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"page_b_x2",
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"page_b_y2",
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"page_b_cx",
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"page_b_cy",
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"page_b_w",
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"page_b_h",
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"page_b_area_ratio",
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"page_b_aspect",
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"page_dx",
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"page_dy",
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"page_abs_dx",
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"page_abs_dy",
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"page_delta_x",
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"page_delta_y",
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"page_delta_x2",
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"page_delta_y2",
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"page_delta_w",
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"page_delta_h",
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"page_distance",
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"page_angle",
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"page_overlap_x",
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"page_overlap_y",
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"page_a_right_of_b",
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"page_a_above_b",
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"page_same_y_overlap_band",
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"page_same_x_overlap_band",
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"page_same_reading_band",
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"page_heuristic_rtl_before",
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"page_heuristic_ltr_before",
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"page_heuristic_direction_score",
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| 46 |
+
"same_predicted_panel",
|
| 47 |
+
"predicted_panel_order_a",
|
| 48 |
+
"predicted_panel_order_b",
|
| 49 |
+
"delta_predicted_panel_order",
|
| 50 |
+
"predicted_local_order_a",
|
| 51 |
+
"predicted_local_order_b",
|
| 52 |
+
"delta_predicted_local_order",
|
| 53 |
+
"current_pipeline_index_a",
|
| 54 |
+
"current_pipeline_index_b",
|
| 55 |
+
"delta_current_pipeline_index",
|
| 56 |
+
"relative_a_in_panel_x",
|
| 57 |
+
"relative_a_in_panel_y",
|
| 58 |
+
"relative_a_in_panel_x2",
|
| 59 |
+
"relative_a_in_panel_y2",
|
| 60 |
+
"relative_a_in_panel_cx",
|
| 61 |
+
"relative_a_in_panel_cy",
|
| 62 |
+
"relative_a_in_panel_w",
|
| 63 |
+
"relative_a_in_panel_h",
|
| 64 |
+
"relative_a_in_panel_area_ratio",
|
| 65 |
+
"relative_a_in_panel_aspect",
|
| 66 |
+
"relative_b_in_panel_x",
|
| 67 |
+
"relative_b_in_panel_y",
|
| 68 |
+
"relative_b_in_panel_x2",
|
| 69 |
+
"relative_b_in_panel_y2",
|
| 70 |
+
"relative_b_in_panel_cx",
|
| 71 |
+
"relative_b_in_panel_cy",
|
| 72 |
+
"relative_b_in_panel_w",
|
| 73 |
+
"relative_b_in_panel_h",
|
| 74 |
+
"relative_b_in_panel_area_ratio",
|
| 75 |
+
"relative_b_in_panel_aspect",
|
| 76 |
+
"predicted_panel_a_x",
|
| 77 |
+
"predicted_panel_a_y",
|
| 78 |
+
"predicted_panel_a_x2",
|
| 79 |
+
"predicted_panel_a_y2",
|
| 80 |
+
"predicted_panel_a_cx",
|
| 81 |
+
"predicted_panel_a_cy",
|
| 82 |
+
"predicted_panel_a_w",
|
| 83 |
+
"predicted_panel_a_h",
|
| 84 |
+
"predicted_panel_a_area_ratio",
|
| 85 |
+
"predicted_panel_a_aspect",
|
| 86 |
+
"predicted_panel_b_x",
|
| 87 |
+
"predicted_panel_b_y",
|
| 88 |
+
"predicted_panel_b_x2",
|
| 89 |
+
"predicted_panel_b_y2",
|
| 90 |
+
"predicted_panel_b_cx",
|
| 91 |
+
"predicted_panel_b_cy",
|
| 92 |
+
"predicted_panel_b_w",
|
| 93 |
+
"predicted_panel_b_h",
|
| 94 |
+
"predicted_panel_b_area_ratio",
|
| 95 |
+
"predicted_panel_b_aspect",
|
| 96 |
+
"bubble_confidence_a",
|
| 97 |
+
"bubble_confidence_b",
|
| 98 |
+
"panel_confidence_a",
|
| 99 |
+
"panel_confidence_b",
|
| 100 |
+
"assignment_a_center_in_panel",
|
| 101 |
+
"assignment_a_overlap_area_ratio",
|
| 102 |
+
"assignment_a_distance_to_panel_center",
|
| 103 |
+
"assignment_a_border_distance",
|
| 104 |
+
"assignment_a_second_best_panel_margin",
|
| 105 |
+
"assignment_a_overlap_panel_count",
|
| 106 |
+
"assignment_b_center_in_panel",
|
| 107 |
+
"assignment_b_overlap_area_ratio",
|
| 108 |
+
"assignment_b_distance_to_panel_center",
|
| 109 |
+
"assignment_b_border_distance",
|
| 110 |
+
"assignment_b_second_best_panel_margin",
|
| 111 |
+
"assignment_b_overlap_panel_count"
|
| 112 |
+
],
|
| 113 |
+
"experiment": "global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair",
|
| 114 |
+
"postprocess": {
|
| 115 |
+
"name": "vertical_small_bubble_repair_v1",
|
| 116 |
+
"gap_factor": 1.5,
|
| 117 |
+
"max_y_overlap": 0.05,
|
| 118 |
+
"max_area_ratio": 0.7
|
| 119 |
+
}
|
| 120 |
+
}
|
global_bubble_order_model.json
ADDED
|
@@ -0,0 +1,167 @@
|
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|
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|
|
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|
|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"kind": "sklearn_pairwise_ranker",
|
| 3 |
+
"name": "global_bubble_reranker_v1__sklearn-logistic",
|
| 4 |
+
"model_type": "sklearn-logistic",
|
| 5 |
+
"created_at": "2026-07-02T21:56:08.938446+00:00",
|
| 6 |
+
"metadata": {
|
| 7 |
+
"experiment": "global_bubble_reranker_v1__sklearn-logistic__borda-vertical-repair",
|
| 8 |
+
"feature_schema": [
|
| 9 |
+
"page_a_x",
|
| 10 |
+
"page_a_y",
|
| 11 |
+
"page_a_x2",
|
| 12 |
+
"page_a_y2",
|
| 13 |
+
"page_a_cx",
|
| 14 |
+
"page_a_cy",
|
| 15 |
+
"page_a_w",
|
| 16 |
+
"page_a_h",
|
| 17 |
+
"page_a_area_ratio",
|
| 18 |
+
"page_a_aspect",
|
| 19 |
+
"page_b_x",
|
| 20 |
+
"page_b_y",
|
| 21 |
+
"page_b_x2",
|
| 22 |
+
"page_b_y2",
|
| 23 |
+
"page_b_cx",
|
| 24 |
+
"page_b_cy",
|
| 25 |
+
"page_b_w",
|
| 26 |
+
"page_b_h",
|
| 27 |
+
"page_b_area_ratio",
|
| 28 |
+
"page_b_aspect",
|
| 29 |
+
"page_dx",
|
| 30 |
+
"page_dy",
|
| 31 |
+
"page_abs_dx",
|
| 32 |
+
"page_abs_dy",
|
| 33 |
+
"page_delta_x",
|
| 34 |
+
"page_delta_y",
|
| 35 |
+
"page_delta_x2",
|
| 36 |
+
"page_delta_y2",
|
| 37 |
+
"page_delta_w",
|
| 38 |
+
"page_delta_h",
|
| 39 |
+
"page_distance",
|
| 40 |
+
"page_angle",
|
| 41 |
+
"page_overlap_x",
|
| 42 |
+
"page_overlap_y",
|
| 43 |
+
"page_a_right_of_b",
|
| 44 |
+
"page_a_above_b",
|
| 45 |
+
"page_same_y_overlap_band",
|
| 46 |
+
"page_same_x_overlap_band",
|
| 47 |
+
"page_same_reading_band",
|
| 48 |
+
"page_heuristic_rtl_before",
|
| 49 |
+
"page_heuristic_ltr_before",
|
| 50 |
+
"page_heuristic_direction_score",
|
| 51 |
+
"same_predicted_panel",
|
| 52 |
+
"predicted_panel_order_a",
|
| 53 |
+
"predicted_panel_order_b",
|
| 54 |
+
"delta_predicted_panel_order",
|
| 55 |
+
"predicted_local_order_a",
|
| 56 |
+
"predicted_local_order_b",
|
| 57 |
+
"delta_predicted_local_order",
|
| 58 |
+
"current_pipeline_index_a",
|
| 59 |
+
"current_pipeline_index_b",
|
| 60 |
+
"delta_current_pipeline_index",
|
| 61 |
+
"relative_a_in_panel_x",
|
| 62 |
+
"relative_a_in_panel_y",
|
| 63 |
+
"relative_a_in_panel_x2",
|
| 64 |
+
"relative_a_in_panel_y2",
|
| 65 |
+
"relative_a_in_panel_cx",
|
| 66 |
+
"relative_a_in_panel_cy",
|
| 67 |
+
"relative_a_in_panel_w",
|
| 68 |
+
"relative_a_in_panel_h",
|
| 69 |
+
"relative_a_in_panel_area_ratio",
|
| 70 |
+
"relative_a_in_panel_aspect",
|
| 71 |
+
"relative_b_in_panel_x",
|
| 72 |
+
"relative_b_in_panel_y",
|
| 73 |
+
"relative_b_in_panel_x2",
|
| 74 |
+
"relative_b_in_panel_y2",
|
| 75 |
+
"relative_b_in_panel_cx",
|
| 76 |
+
"relative_b_in_panel_cy",
|
| 77 |
+
"relative_b_in_panel_w",
|
| 78 |
+
"relative_b_in_panel_h",
|
| 79 |
+
"relative_b_in_panel_area_ratio",
|
| 80 |
+
"relative_b_in_panel_aspect",
|
| 81 |
+
"predicted_panel_a_x",
|
| 82 |
+
"predicted_panel_a_y",
|
| 83 |
+
"predicted_panel_a_x2",
|
| 84 |
+
"predicted_panel_a_y2",
|
| 85 |
+
"predicted_panel_a_cx",
|
| 86 |
+
"predicted_panel_a_cy",
|
| 87 |
+
"predicted_panel_a_w",
|
| 88 |
+
"predicted_panel_a_h",
|
| 89 |
+
"predicted_panel_a_area_ratio",
|
| 90 |
+
"predicted_panel_a_aspect",
|
| 91 |
+
"predicted_panel_b_x",
|
| 92 |
+
"predicted_panel_b_y",
|
| 93 |
+
"predicted_panel_b_x2",
|
| 94 |
+
"predicted_panel_b_y2",
|
| 95 |
+
"predicted_panel_b_cx",
|
| 96 |
+
"predicted_panel_b_cy",
|
| 97 |
+
"predicted_panel_b_w",
|
| 98 |
+
"predicted_panel_b_h",
|
| 99 |
+
"predicted_panel_b_area_ratio",
|
| 100 |
+
"predicted_panel_b_aspect",
|
| 101 |
+
"bubble_confidence_a",
|
| 102 |
+
"bubble_confidence_b",
|
| 103 |
+
"panel_confidence_a",
|
| 104 |
+
"panel_confidence_b",
|
| 105 |
+
"assignment_a_center_in_panel",
|
| 106 |
+
"assignment_a_overlap_area_ratio",
|
| 107 |
+
"assignment_a_distance_to_panel_center",
|
| 108 |
+
"assignment_a_border_distance",
|
| 109 |
+
"assignment_a_second_best_panel_margin",
|
| 110 |
+
"assignment_a_overlap_panel_count",
|
| 111 |
+
"assignment_b_center_in_panel",
|
| 112 |
+
"assignment_b_overlap_area_ratio",
|
| 113 |
+
"assignment_b_distance_to_panel_center",
|
| 114 |
+
"assignment_b_border_distance",
|
| 115 |
+
"assignment_b_second_best_panel_margin",
|
| 116 |
+
"assignment_b_overlap_panel_count"
|
| 117 |
+
],
|
| 118 |
+
"selection": "validation",
|
| 119 |
+
"test_metrics": {
|
| 120 |
+
"page_full_accuracy": 0.967741935483871,
|
| 121 |
+
"page_exact_matches": 30,
|
| 122 |
+
"page_count": 31,
|
| 123 |
+
"bubble_position_accuracy": 0.9931506849315068,
|
| 124 |
+
"bubble_position_correct": 290,
|
| 125 |
+
"bubble_position_total": 292,
|
| 126 |
+
"global_pairwise_accuracy": 0.9992862241256245,
|
| 127 |
+
"global_pairwise_correct": 1400,
|
| 128 |
+
"global_pairwise_total": 1401,
|
| 129 |
+
"kendall_tau_distance_mean": 0.03225806451612903,
|
| 130 |
+
"inversion_count_total": 1,
|
| 131 |
+
"panel_order_full_accuracy": 1.0,
|
| 132 |
+
"bubble_within_panel_full_accuracy": 0.98989898989899,
|
| 133 |
+
"error_categories": {
|
| 134 |
+
"wrong_panel_order": {
|
| 135 |
+
"pages": 0,
|
| 136 |
+
"rate": 0.0
|
| 137 |
+
},
|
| 138 |
+
"wrong_order_in_panel": {
|
| 139 |
+
"pages": 1,
|
| 140 |
+
"rate": 0.03225806451612903
|
| 141 |
+
},
|
| 142 |
+
"wrong_bubble_panel_assignment": {
|
| 143 |
+
"pages": 1,
|
| 144 |
+
"rate": 0.03225806451612903
|
| 145 |
+
},
|
| 146 |
+
"bubble_outside_panel": {
|
| 147 |
+
"pages": 0,
|
| 148 |
+
"rate": 0.0
|
| 149 |
+
},
|
| 150 |
+
"empty_or_missing_panels": {
|
| 151 |
+
"pages": 10,
|
| 152 |
+
"rate": 0.3225806451612903
|
| 153 |
+
},
|
| 154 |
+
"fallback_mangaOrderSort_used": {
|
| 155 |
+
"pages": 0,
|
| 156 |
+
"rate": 0.0
|
| 157 |
+
}
|
| 158 |
+
}
|
| 159 |
+
},
|
| 160 |
+
"postprocess": {
|
| 161 |
+
"name": "vertical_small_bubble_repair_v1",
|
| 162 |
+
"gap_factor": 1.5,
|
| 163 |
+
"max_y_overlap": 0.05,
|
| 164 |
+
"max_area_ratio": 0.7
|
| 165 |
+
}
|
| 166 |
+
}
|
| 167 |
+
}
|
metrics/panel_detector_metrics.json
CHANGED
|
@@ -1,8 +1,8 @@
|
|
| 1 |
{
|
| 2 |
"kind": "panel_detector_training_metrics",
|
| 3 |
-
"created_at": "2026-
|
| 4 |
-
"started_at": "2026-
|
| 5 |
-
"training_seconds":
|
| 6 |
"model_name": "yolo26n.pt",
|
| 7 |
"dataset_yaml": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\dataset\\data.yaml",
|
| 8 |
"imgsz": 800,
|
|
@@ -10,42 +10,42 @@
|
|
| 10 |
"batch": 16,
|
| 11 |
"patience": 20,
|
| 12 |
"device": "0",
|
| 13 |
-
"run_dir": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\
|
| 14 |
-
"best_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\
|
| 15 |
-
"last_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\
|
| 16 |
-
"onnx_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\
|
| 17 |
"test": {
|
| 18 |
"split": "test",
|
| 19 |
-
"precision": 0.
|
| 20 |
-
"recall": 0.
|
| 21 |
-
"f1": 0.
|
| 22 |
-
"mAP50": 0.
|
| 23 |
-
"mAP50-95": 0.
|
| 24 |
-
"fitness": 0.
|
| 25 |
"speed_ms": {
|
| 26 |
-
"preprocess":
|
| 27 |
-
"inference":
|
| 28 |
-
"loss": 0.
|
| 29 |
-
"postprocess": 0.
|
| 30 |
},
|
| 31 |
"raw": {
|
| 32 |
-
"metrics/precision(B)": 0.
|
| 33 |
-
"metrics/recall(B)": 0.
|
| 34 |
-
"metrics/mAP50(B)": 0.
|
| 35 |
-
"metrics/mAP50-95(B)": 0.
|
| 36 |
-
"fitness": 0.
|
| 37 |
},
|
| 38 |
"per_class": [
|
| 39 |
{
|
| 40 |
"class_id": 0,
|
| 41 |
"class_name": "panel",
|
| 42 |
-
"precision": 0.
|
| 43 |
-
"recall": 0.
|
| 44 |
-
"f1": 0.
|
| 45 |
-
"mAP50": 0.
|
| 46 |
-
"mAP50-95": 0.
|
| 47 |
}
|
| 48 |
],
|
| 49 |
-
"save_dir": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\eval\\
|
| 50 |
}
|
| 51 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"kind": "panel_detector_training_metrics",
|
| 3 |
+
"created_at": "2026-07-02T20:24:53.146010+00:00",
|
| 4 |
+
"started_at": "2026-07-02T20:21:26.454977+00:00",
|
| 5 |
+
"training_seconds": 201.44488549232483,
|
| 6 |
"model_name": "yolo26n.pt",
|
| 7 |
"dataset_yaml": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\dataset\\data.yaml",
|
| 8 |
"imgsz": 800,
|
|
|
|
| 10 |
"batch": 16,
|
| 11 |
"patience": 20,
|
| 12 |
"device": "0",
|
| 13 |
+
"run_dir": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\yolo26n_panel3",
|
| 14 |
+
"best_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\yolo26n_panel3\\weights\\best.pt",
|
| 15 |
+
"last_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\yolo26n_panel3\\weights\\last.pt",
|
| 16 |
+
"onnx_model": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\yolo26n_panel3\\weights\\best.onnx",
|
| 17 |
"test": {
|
| 18 |
"split": "test",
|
| 19 |
+
"precision": 0.9795184747289132,
|
| 20 |
+
"recall": 0.9801324503311258,
|
| 21 |
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"f1": 0.9798253663480834,
|
| 22 |
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"mAP50": 0.9940366112707735,
|
| 23 |
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"mAP50-95": 0.986110385292093,
|
| 24 |
+
"fitness": 0.986110385292093,
|
| 25 |
"speed_ms": {
|
| 26 |
+
"preprocess": 2.6662500022212043,
|
| 27 |
+
"inference": 7.567143748019589,
|
| 28 |
+
"loss": 0.00032812749850563705,
|
| 29 |
+
"postprocess": 0.1320750016020611
|
| 30 |
},
|
| 31 |
"raw": {
|
| 32 |
+
"metrics/precision(B)": 0.9795184747289132,
|
| 33 |
+
"metrics/recall(B)": 0.9801324503311258,
|
| 34 |
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"metrics/mAP50(B)": 0.9940366112707735,
|
| 35 |
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"metrics/mAP50-95(B)": 0.986110385292093,
|
| 36 |
+
"fitness": 0.986110385292093
|
| 37 |
},
|
| 38 |
"per_class": [
|
| 39 |
{
|
| 40 |
"class_id": 0,
|
| 41 |
"class_name": "panel",
|
| 42 |
+
"precision": 0.9795184747289132,
|
| 43 |
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"recall": 0.9801324503311258,
|
| 44 |
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"f1": 0.9798253663480834,
|
| 45 |
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"mAP50": 0.9940366112707735,
|
| 46 |
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"mAP50-95": 0.986110385292093
|
| 47 |
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|
| 48 |
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|
| 49 |
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"save_dir": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\runs\\eval\\yolo26n_panel_test3"
|
| 50 |
}
|
| 51 |
}
|
metrics/reading_order_benchmark.json
ADDED
|
The diff for this file is too large to render.
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|
|
|
metrics/reading_order_metrics.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"kind": "reading_order_training_metrics",
|
| 3 |
-
"created_at": "2026-
|
| 4 |
"annotations": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\panel_annotation_dataset\\panel_annotations.json",
|
| 5 |
"split_source": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\dataset\\manifest.json",
|
| 6 |
"seed": 42,
|
|
@@ -10,84 +10,66 @@
|
|
| 10 |
"note": "Final page_full_accuracy evaluates ordering only: ground-truth panel and bubble boxes/assignments are used, then the trained panel and bubble rankers predict order. Optional manga RTL/top-to-bottom priors and clear-vertical bubble overrides are selected only on training pages; selected values are recorded in heuristic_blend.",
|
| 11 |
"skipped_pages": {
|
| 12 |
"missing_size": 0,
|
| 13 |
-
"missing_panels":
|
| 14 |
"missing_bubbles": 3,
|
| 15 |
"invalid_panel": 0
|
| 16 |
},
|
| 17 |
"dataset": {
|
| 18 |
"all": {
|
| 19 |
-
"pages":
|
| 20 |
-
"panels":
|
| 21 |
-
"bubbles":
|
| 22 |
-
"multi_bubble_panels":
|
| 23 |
},
|
| 24 |
"train": {
|
| 25 |
-
"pages":
|
| 26 |
-
"panels":
|
| 27 |
-
"bubbles":
|
| 28 |
-
"multi_bubble_panels":
|
| 29 |
},
|
| 30 |
"test": {
|
| 31 |
-
"pages":
|
| 32 |
-
"panels":
|
| 33 |
-
"bubbles":
|
| 34 |
-
"multi_bubble_panels":
|
| 35 |
}
|
| 36 |
},
|
| 37 |
"train_page_ids": [
|
| 38 |
-
269,
|
| 39 |
271,
|
| 40 |
273,
|
| 41 |
275,
|
| 42 |
276,
|
| 43 |
277,
|
|
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| 44 |
279,
|
| 45 |
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|
| 46 |
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283,
|
| 47 |
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|
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|
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|
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|
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|
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|
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| 68 |
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|
| 69 |
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| 70 |
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|
| 71 |
-
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|
| 72 |
-
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|
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315,
|
| 74 |
316,
|
| 75 |
317,
|
| 76 |
318,
|
|
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|
|
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| 77 |
339,
|
|
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|
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| 78 |
343,
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-
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| 80 |
345,
|
|
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| 84 |
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| 85 |
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| 86 |
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|
|
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|
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| 93 |
363,
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|
@@ -97,35 +79,136 @@
|
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368,
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| 99 |
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| 100 |
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371
|
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],
|
| 102 |
"test_page_ids": [
|
| 103 |
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|
| 104 |
-
|
| 105 |
-
|
| 106 |
-
|
| 107 |
-
|
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|
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],
|
| 120 |
"pairs": {
|
| 121 |
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"panel_train":
|
| 122 |
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"panel_test":
|
| 123 |
-
"bubble_train":
|
| 124 |
-
"bubble_test":
|
| 125 |
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|
| 126 |
"heuristic_blend": {
|
| 127 |
"candidate_weights": [
|
| 128 |
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0.0
|
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|
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],
|
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"vertical_override_candidates": [
|
| 131 |
null,
|
|
@@ -140,19 +223,19 @@
|
|
| 140 |
"selection_metric": "train page_full_accuracy, tie-broken by panel accuracy, bubble accuracy, lower total blend weight, and no/smaller override",
|
| 141 |
"selected_train_ordering": {
|
| 142 |
"panel_order_full_accuracy": 1.0,
|
| 143 |
-
"bubble_within_panel_full_accuracy": 0.
|
| 144 |
-
"page_full_accuracy": 0.
|
| 145 |
-
"page_exact_matches":
|
| 146 |
-
"page_count":
|
| 147 |
-
"bubble_position_accuracy": 0.
|
| 148 |
-
"bubble_position_correct":
|
| 149 |
-
"bubble_position_total":
|
| 150 |
}
|
| 151 |
},
|
| 152 |
"panel_order": {
|
| 153 |
"training": {
|
| 154 |
"model_type": "sklearn-logistic",
|
| 155 |
-
"samples":
|
| 156 |
"feature_count": 42,
|
| 157 |
"sklearn_available": true
|
| 158 |
},
|
|
@@ -162,38 +245,38 @@
|
|
| 162 |
"bubble_order": {
|
| 163 |
"training": {
|
| 164 |
"model_type": "sklearn-logistic",
|
| 165 |
-
"samples":
|
| 166 |
"feature_count": 94,
|
| 167 |
"sklearn_available": true
|
| 168 |
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|
| 169 |
-
"train_pair_accuracy": 0.
|
| 170 |
-
"test_pair_accuracy": 0.
|
| 171 |
},
|
| 172 |
"train_ordering": {
|
| 173 |
"panel_order_full_accuracy": 1.0,
|
| 174 |
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|
| 175 |
-
"page_full_accuracy": 0.
|
| 176 |
-
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|
| 177 |
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"page_count":
|
| 178 |
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"bubble_position_accuracy": 0.
|
| 179 |
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"bubble_position_correct":
|
| 180 |
-
"bubble_position_total":
|
| 181 |
},
|
| 182 |
"test_ordering": {
|
| 183 |
"panel_order_full_accuracy": 1.0,
|
| 184 |
-
"bubble_within_panel_full_accuracy": 0.
|
| 185 |
-
"page_full_accuracy": 0.
|
| 186 |
-
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|
| 187 |
-
"page_count":
|
| 188 |
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|
| 189 |
-
"bubble_position_correct":
|
| 190 |
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"bubble_position_total":
|
| 191 |
},
|
| 192 |
"primary_metric": {
|
| 193 |
"name": "page_full_accuracy",
|
| 194 |
-
"value": 0.
|
| 195 |
-
"exact_matches":
|
| 196 |
-
"page_count":
|
| 197 |
},
|
| 198 |
"onnx_models": {
|
| 199 |
"panel_order": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_reading_order\\models\\panel_order.onnx",
|
|
|
|
| 1 |
{
|
| 2 |
"kind": "reading_order_training_metrics",
|
| 3 |
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"created_at": "2026-07-02T20:26:16.681837+00:00",
|
| 4 |
"annotations": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\panel_annotation_dataset\\panel_annotations.json",
|
| 5 |
"split_source": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_panel_detector\\dataset\\manifest.json",
|
| 6 |
"seed": 42,
|
|
|
|
| 10 |
"note": "Final page_full_accuracy evaluates ordering only: ground-truth panel and bubble boxes/assignments are used, then the trained panel and bubble rankers predict order. Optional manga RTL/top-to-bottom priors and clear-vertical bubble overrides are selected only on training pages; selected values are recorded in heuristic_blend.",
|
| 11 |
"skipped_pages": {
|
| 12 |
"missing_size": 0,
|
| 13 |
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"missing_panels": 703,
|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
"dataset": {
|
| 18 |
"all": {
|
| 19 |
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"pages": 157,
|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
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|
| 33 |
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|
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|
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|
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| 141 |
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| 142 |
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| 143 |
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| 144 |
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| 156 |
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| 158 |
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| 159 |
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|
| 160 |
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|
| 161 |
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497,
|
| 162 |
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498,
|
| 163 |
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499
|
| 164 |
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|
| 165 |
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|
| 166 |
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269,
|
| 167 |
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|
| 168 |
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|
| 169 |
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|
| 170 |
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|
| 171 |
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344,
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|
| 172 |
352,
|
| 173 |
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| 174 |
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|
| 175 |
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|
| 176 |
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| 177 |
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|
| 194 |
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491,
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| 195 |
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|
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|
| 197 |
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| 198 |
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|
| 199 |
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|
| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
| 205 |
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|
| 206 |
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|
| 207 |
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0.1,
|
| 208 |
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0.2,
|
| 209 |
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0.3,
|
| 210 |
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0.4,
|
| 211 |
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0.5
|
| 212 |
],
|
| 213 |
"vertical_override_candidates": [
|
| 214 |
null,
|
|
|
|
| 223 |
"selection_metric": "train page_full_accuracy, tie-broken by panel accuracy, bubble accuracy, lower total blend weight, and no/smaller override",
|
| 224 |
"selected_train_ordering": {
|
| 225 |
"panel_order_full_accuracy": 1.0,
|
| 226 |
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"bubble_within_panel_full_accuracy": 0.9649122807017544,
|
| 227 |
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"page_full_accuracy": 0.8650793650793651,
|
| 228 |
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|
| 229 |
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"page_count": 126,
|
| 230 |
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|
| 231 |
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"bubble_position_correct": 1165,
|
| 232 |
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"bubble_position_total": 1204
|
| 233 |
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|
| 234 |
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|
| 235 |
"panel_order": {
|
| 236 |
"training": {
|
| 237 |
"model_type": "sklearn-logistic",
|
| 238 |
+
"samples": 2570,
|
| 239 |
"feature_count": 42,
|
| 240 |
"sklearn_available": true
|
| 241 |
},
|
|
|
|
| 245 |
"bubble_order": {
|
| 246 |
"training": {
|
| 247 |
"model_type": "sklearn-logistic",
|
| 248 |
+
"samples": 1990,
|
| 249 |
"feature_count": 94,
|
| 250 |
"sklearn_available": true
|
| 251 |
},
|
| 252 |
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|
| 253 |
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|
| 254 |
},
|
| 255 |
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|
| 256 |
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|
| 257 |
+
"bubble_within_panel_full_accuracy": 0.9649122807017544,
|
| 258 |
+
"page_full_accuracy": 0.8650793650793651,
|
| 259 |
+
"page_exact_matches": 109,
|
| 260 |
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"page_count": 126,
|
| 261 |
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"bubble_position_accuracy": 0.967607973421927,
|
| 262 |
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"bubble_position_correct": 1165,
|
| 263 |
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"bubble_position_total": 1204
|
| 264 |
},
|
| 265 |
"test_ordering": {
|
| 266 |
"panel_order_full_accuracy": 1.0,
|
| 267 |
+
"bubble_within_panel_full_accuracy": 0.9595959595959596,
|
| 268 |
+
"page_full_accuracy": 0.8387096774193549,
|
| 269 |
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"page_exact_matches": 26,
|
| 270 |
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"page_count": 31,
|
| 271 |
+
"bubble_position_accuracy": 0.9657534246575342,
|
| 272 |
+
"bubble_position_correct": 282,
|
| 273 |
+
"bubble_position_total": 292
|
| 274 |
},
|
| 275 |
"primary_metric": {
|
| 276 |
"name": "page_full_accuracy",
|
| 277 |
+
"value": 0.8387096774193549,
|
| 278 |
+
"exact_matches": 26,
|
| 279 |
+
"page_count": 31
|
| 280 |
},
|
| 281 |
"onnx_models": {
|
| 282 |
"panel_order": "C:\\Users\\remis\\Documents\\Projet Git\\projet-one-piece-indexer\\docker_scripts\\train_reading_order\\models\\panel_order.onnx",
|
model_manifest.json
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"repo_id": "Remidesbois/YoloPiece_OneShot_Models",
|
| 3 |
-
"created_at": "2026-
|
| 4 |
"runtime": "onnxruntime-web",
|
| 5 |
"models": {
|
| 6 |
"bubble_detector.onnx": {
|
|
@@ -11,24 +11,852 @@
|
|
| 11 |
"panel_detector.onnx": {
|
| 12 |
"path": "panel_detector.onnx",
|
| 13 |
"size_bytes": 9899051,
|
| 14 |
-
"sha256": "
|
| 15 |
},
|
| 16 |
"panel_order.onnx": {
|
| 17 |
"path": "panel_order.onnx",
|
| 18 |
"size_bytes": 1049,
|
| 19 |
-
"sha256": "
|
| 20 |
},
|
| 21 |
"bubble_order.onnx": {
|
| 22 |
"path": "bubble_order.onnx",
|
| 23 |
"size_bytes": 1675,
|
| 24 |
-
"sha256": "
|
|
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| 25 |
}
|
| 26 |
},
|
| 27 |
"metrics": {
|
| 28 |
"reading_order": "metrics/reading_order_metrics.json",
|
| 29 |
-
"panel_detector": "metrics/panel_detector_metrics.json"
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| 30 |
},
|
| 31 |
"source_repos": {
|
| 32 |
-
"bubble_detector": "Remidesbois/YoloPiece_BubbleDetector_Nano"
|
|
|
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|
| 33 |
}
|
| 34 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"repo_id": "Remidesbois/YoloPiece_OneShot_Models",
|
| 3 |
+
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|
| 4 |
"runtime": "onnxruntime-web",
|
| 5 |
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|
| 6 |
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|
| 11 |
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|
| 12 |
"path": "panel_detector.onnx",
|
| 13 |
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| 14 |
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| 15 |
},
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| 16 |
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|
| 17 |
"path": "panel_order.onnx",
|
| 18 |
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| 19 |
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| 20 |
},
|
| 21 |
"bubble_order.onnx": {
|
| 22 |
"path": "bubble_order.onnx",
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| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 44 |
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| 45 |
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| 52 |
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| 53 |
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| 54 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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| 63 |
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| 64 |
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