| --- |
| license: other |
| library_name: ultralytics |
| pipeline_tag: object-detection |
| tags: |
| - trading-card-games |
| - object-detection |
| - yolo |
| - onnx |
| - riftbound |
| --- |
| |
| # TCGscanner Card Detector |
|
|
| This repository contains the current ONNX card-boundary detector used by the TCGscanner prototype. |
|
|
| The model is a single-class YOLO detector. Its task is to localize the physical trading card in a camera frame or photograph. Card identification is handled separately by SigLIP 2 visual embeddings and LanceDB vector search in the application repository. |
|
|
| ## Files |
|
|
| - `riftbound_regions.onnx`: exported ONNX detector expected at `models/riftbound_regions.onnx` by the scanner. |
|
|
| ## Current Artifact |
|
|
| - Size: `11.70 MB` |
| - SHA256: `8566d3c8556183c780eab0937f65d9862bdfc57697bfd3c33135218f28230f41` |
| - Class labels: `card` |
| - Default confidence threshold in the app: `0.35` |
|
|
| ## Training Summary |
|
|
| The detector was trained on a universal TCG detection dataset that combines localized card examples from multiple trading card domains. The objective is to learn generic card geometry rather than the visual identity of a specific game. |
|
|
| The selected hybrid experiment used corners, polygons, and isolated full-card samples. The June 27, 2026 audit run reported: |
|
|
| | Experiment | Test precision | Test recall | Test mAP50 | Test mAP50-95 | |
| | --- | ---: | ---: | ---: | ---: | |
| | localization_only | 0.9957 | 1.0000 | 0.9950 | 0.9141 | |
| | hybrid | 0.9992 | 1.0000 | 0.9950 | 0.9635 | |
| |
| The selected hybrid run was stopped manually during epoch 42 after the validation curve had stabilized for the scanner use case. Its best validation checkpoint was epoch 40 with `mAP50=0.9942` and `mAP50-95=0.9628`. |
| |
| ## Usage |
| |
| ```bash |
| uv run python scripts/download_detector.py |
| ``` |
| |
| The scanner loads the downloaded model from: |
| |
| ```text |
| models/riftbound_regions.onnx |
| ``` |
| |
| ## Limitations |
| |
| - This detector only localizes the card boundary. |
| - It does not identify the card. |
| - The current dataset still needs more real-world Riftbound photographs. |
| - Pricing and collection features are outside this model repository. |
| |
