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README.md

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+---
+license: mit
+tags:
+  - object-detection
+  - image-classification
+  - set-game
+  - card-game
+  - computer-vision
+  - synthetic-data
+size_categories:
+  - 1K<n<10K
+---
+
+# Set Solver Dataset
+
+Training data for the [Set card game](https://www.setgame.com/) solver.
+
+**[Live demo](https://huggingface.co/spaces/wangtianthu/set-solver)** | **[Models](https://huggingface.co/wangtianthu/set-solver-models)** | **[Source code](https://github.com/wangtian24/set-solver)**
+
+## Dataset Structure
+
+### Classifier — Card Attribute Classification
+
+`classifier/{number}/{color}/{shape}/{fill}/`
+
+1943 cropped card images organized into 81 classes (3 numbers x 3 colors x 3 shapes x 3 fills).
+
+| Attribute | Values |
+|-----------|--------|
+| Number | one, two, three |
+| Color | red, green, blue (purple) |
+| Shape | diamond, oval, squiggle |
+| Fill | empty, full (solid), partial (striped) |
+
+### Detector — Card Detection (YOLO format)
+
+`detector/images/` and `detector/labels/`
+
+5000 synthetic board images (1280x960) with YOLO-format bounding box annotations.
+
+- **Train**: 4000 images (`detector/images/train/`)
+- **Val**: 1000 images (`detector/images/val/`)
+- **Labels**: YOLO `.txt` files + rich `.json` metadata per image
+- **Class**: single class (`card`)
+
+The synthetic boards feature:
+- Grid, random, overlap, and pile card layouts
+- Varied background textures (wood, marble, gradients)
+- Perspective transforms simulating camera angles
+- Noise objects (buttons, coins, paper clips)
+- 9-12 cards per board
+
+## Usage
+
+### Detector training with Ultralytics
+
+```python
+from ultralytics import YOLO
+
+model = YOLO("yolo11n.pt")
+model.train(data="detector/dataset.yaml", epochs=10, imgsz=640)
+```
+
+### Classifier training
+
+```python
+from torchvision.datasets import ImageFolder
+from torchvision import transforms
+
+dataset = ImageFolder("classifier/", transform=transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+]))
+```

detector/dataset.yaml

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+path: /Users/wangtian/data/set-solver/synthetic
+train: images/train
+val: images/val
+
+names:
+  0: card