TCGscanner Detector
This repository contains the current ONNX card-boundary detector used by the TCGscanner prototype.
Fonte do modelo
- Tipo
- Other
- Tamanho do arquivo
- 11,7 MB
- Versão
- vRevision 524cffa
- Atualizado
- 11 de out. de 2026
- Downloads
- 0
- Fonte
- Hugging Face
Descrição da fonte
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 atmodels/riftbound_regions.onnxby 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
uv run python scripts/download_detector.py
The scanner loads the downloaded model from:
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.
Fontes
1 fonte
Fontes
1 fonteVerificado 26 de ago.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoTrechos de fonte
2 trechos
Trechos de fonte
2 trechos--- 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.
Source context: 0 downloads · 1 likes · Pipeline object-detection · Library ultralytics · Repo Adrihp06/TCGscanner-detector
