Update README.md

README.md

@@ -1,9 +1,11 @@
 ---
 license: agpl-3.0
 metrics:
-- precision
-- recall
-- accuracy
+  - map50
+  - map50-95
+  - precision
+  - recall
+  - f1
 base_model:
 - Ultralytics/YOLO26
 pipeline_tag: object-detection
@@ -27,24 +29,47 @@ This model is a fine-tuned YOLO object detection model specifically trained to a
 
 - **Train Images**: 13,565
 - **Validation Images**: 1,507
-- **Image Size (`imgsz`)**: 1920 (match for standard VRChat screenshot resolution)
+- **Image Size (`imgsz`)**: 1920 (Source is 1920x1080 ~ 15360x8360)
 - **Data Source**: Photos captured using the in-game camera over 7 years of VRChat gameplay, along with frame data extracted from 1,707 hours of recorded video footage.
 
 ### Data Filtering & Preprocessing
 - **Included**: Humanoid 3D avatars only.
-- **Excluded**: Non-humanoid avatars, Fallback avatars, and Impostor avatars.
+- **Excluded**: Non-humanoid avatars, Fallback avatars, default robot avatar, and Impostor avatars.
 
 ## Training Configuration
 - **Task**: Object Detection
-- **Base Framework**: Ultralytics YOLO
-- **Input Resolution**: 1920x1920
+- **Base Framework**: Ultralytics YOLO26m
+- **Input Resolution**: 1920
 
 ## Usage
 
 ```python
 from ultralytics import YOLO
 
-model = YOLO("model.pt")
+model = YOLO("yolo26m_vrchat_avatar.pt")
 results = model.predict(source="vrchat_screenshot.png", imgsz=1920)
 results[0].show()
-```
+```
+
+## Performance
+
+| Metric     | Score (%)       |
+| ---------- | --------------- |
+| mAP@50     | 96.30           |
+| mAP@50-95  | 81.30           |
+| Precision  | 96.50           |
+| Recall     | 92.80           |
+| F1 Score   | 94.61           |
+| Parameters | 20.35M          |
+| FLOPs      | 68.1B           |
+| Inference  | 4.7ms (NVIDIA H100) |
+
+## Per-Class Performance
+
+| Class   | Images | Instances | Precision (%) | Recall (%) | mAP@50 (%) | mAP@50-95 (%) |
+| ------- | ------ | --------- | ------------- | ---------- | ---------- | ------------- |
+| avatar  | 1455   | 2777      | 95.90         | 90.80      | 95.80      | 79.80         |
+| nametag | 121    | 268       | 97.10         | 94.80      | 96.80      | 82.80         |
+| all     | 1507   | 3045      | 96.50         | 92.80      | 96.30      | 81.30         |
+
+---