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README.md

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+---
+tags:
+- keypoint-detection
+- sports
+- football
+- soccer
+- roboflow
+- yolov8
+license: mit
+---
+
+# Football Field Keypoint Detection (Roboflow)
+
+YOLOv8 keypoint detection model for identifying field lines and key points on a football/soccer pitch.
+
+## Model Details
+
+- **Model ID**: `football-field-detection-f07vi/14`
+- **Platform**: Roboflow
+- **Architecture**: YOLOv8 Pose
+- **Task**: Keypoint detection
+
+## Quick Start
+
+### Installation
+
+```bash
+pip install inference-gpu  # or inference for CPU
+pip install supervision
+```
+
+### Basic Usage
+
+```python
+from inference import get_model
+import supervision as sv
+
+# Initialize model
+api_key = "YOUR_ROBOFLOW_API_KEY"
+model = get_model(
+    model_id="football-field-detection-f07vi/14",
+    api_key=api_key
+)
+
+# Run inference
+result = model.infer("image.jpg", confidence=0.3)[0]
+key_points = sv.KeyPoints.from_inference(result)
+
+print(f"Detected {len(key_points.xy[0])} keypoints")
+```
+
+### Using the Wrapper
+
+```python
+from field_inference import FootballFieldDetector
+import os
+
+detector = FootballFieldDetector(api_key=os.getenv("ROBOFLOW_API_KEY"))
+results = detector.predict("image.jpg", confidence=0.3)
+```
+
+## Applications
+
+- **Homography Estimation**: Map player positions to tactical view
+- **Camera Calibration**: Align multiple camera views
+- **Tactical Analysis**: Project player movements on 2D pitch
+- **AR Overlays**: Augmented reality graphics on field
+- **Voronoi Diagrams**: Team possession and control analysis
+
+## Example: View Transformation
+
+```python
+import numpy as np
+from sports.common.view import ViewTransformer
+from sports.configs.soccer import SoccerPitchConfiguration
+
+# Get field keypoints
+result = model.infer(frame, confidence=0.3)[0]
+key_points = sv.KeyPoints.from_inference(result)
+
+# Filter confident keypoints
+filter = key_points.confidence[0] > 0.5
+frame_points = key_points.xy[0][filter]
+
+# Create transformer
+config = SoccerPitchConfiguration()
+pitch_points = np.array(config.vertices)[filter]
+
+transformer = ViewTransformer(
+    source=frame_points,
+    target=pitch_points
+)
+
+# Transform player positions to pitch coordinates
+pitch_xy = transformer.transform_points(player_xy)
+```
+
+## API Key
+
+You need a Roboflow API key to use this model. Get one at [roboflow.com](https://roboflow.com).
+
+## Citation
+
+```
+@misc{football-field-detection,
+    title={Football Field Detection},
+    author={Roboflow},
+    year={2024},
+    url={https://universe.roboflow.com/roboflow-jvuqo/football-field-detection-f07vi}
+}
+```