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feat: Add yolov5n, update docs and ruff code format

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yakhyo
2025-12-11 01:02:18 +09:00
parent 3982d677a9
commit da8a5cf35b
13 changed files with 49 additions and 18 deletions
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16
MODELS.md
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@@ -80,10 +80,11 @@ detector = SCRFD(
YOLOv5-Face models provide excellent detection accuracy with 5-point facial landmarks, optimized for real-time applications.
| Model Name | Params | Size | Easy | Medium | Hard | FLOPs (G) | Use Case |
| -------------- | ------ | ---- | ------ | ------ | ------ | --------- | ------------------------------ |
| `YOLOV5S` ⭐ | 7.1M | 28MB | 94.33% | 92.61% | 83.15% | 5.751 | **Real-time + accuracy** |
| `YOLOV5M` | 21.1M | 84MB | 95.30% | 93.76% | 85.28% | 18.146 | High accuracy |
| Model Name | Size | Easy | Medium | Hard | Use Case |
| -------------- | ---- | ------ | ------ | ------ | ------------------------------ |
| `YOLOV5N` | 11MB | 93.61% | 91.52% | 80.53% | Lightweight/Mobile |
| `YOLOV5S` ⭐ | 28MB | 94.33% | 92.61% | 83.15% | **Real-time + accuracy** |
| `YOLOV5M` | 82MB | 95.30% | 93.76% | 85.28% | High accuracy |
**Accuracy**: WIDER FACE validation set - from [YOLOv5-Face paper](https://arxiv.org/abs/2105.12931)
**Speed**: Benchmark on your own hardware using `scripts/run_detection.py --iterations 100`
@@ -95,6 +96,13 @@ YOLOv5-Face models provide excellent detection accuracy with 5-point facial land
from uniface import YOLOv5Face
from uniface.constants import YOLOv5FaceWeights
# Lightweight/Mobile
detector = YOLOv5Face(
model_name=YOLOv5FaceWeights.YOLOV5N,
conf_thresh=0.6,
nms_thresh=0.5
)
# Real-time detection (recommended)
detector = YOLOv5Face(
model_name=YOLOv5FaceWeights.YOLOV5S,