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ref: Add comprehensive test suite and enhance model functionality

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- Add new test files for age_gender, factory, landmark, recognition, scrfd, and utils
- Add new scripts for age_gender, landmarks, and video detection
- Update documentation in README.md, MODELS.md, QUICKSTART.md
- Improve model constants and face utilities
- Update detection models (retinaface, scrfd) with enhanced functionality
- Update project configuration in pyproject.toml
This commit is contained in:
yakhyo
2025-11-15 21:09:37 +09:00
parent df673c4a3f
commit 2c78f39e5d
28 changed files with 2014 additions and 591 deletions
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51
QUICKSTART.md
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@@ -7,8 +7,8 @@ Get up and running with UniFace in 5 minutes! This guide covers the most common
## Installation
```bash
# macOS (Apple Silicon)
pip install uniface[silicon]
# macOS (Apple Silicon) - automatically includes ARM64 optimizations
pip install uniface
# Linux/Windows with NVIDIA GPU
pip install uniface[gpu]
@@ -114,9 +114,9 @@ if faces1 and faces2:
# Interpret result
if similarity > 0.6:
print(f"✅ Same person (similarity: {similarity:.3f})")
print(f"Same person (similarity: {similarity:.3f})")
else:
print(f"❌ Different people (similarity: {similarity:.3f})")
print(f"Different people (similarity: {similarity:.3f})")
else:
print("No faces detected")
```
@@ -264,31 +264,46 @@ print("Done!")
Choose the right model for your use case:
### Detection Models
```python
from uniface import create_detector
from uniface.detection import RetinaFace, SCRFD
from uniface.constants import RetinaFaceWeights, SCRFDWeights
# Fast detection (mobile/edge devices)
detector = create_detector(
'retinaface',
detector = RetinaFace(
model_name=RetinaFaceWeights.MNET_025,
conf_thresh=0.7
)
# Balanced (recommended)
detector = create_detector(
'retinaface',
detector = RetinaFace(
model_name=RetinaFaceWeights.MNET_V2
)
# High accuracy (server/GPU)
detector = create_detector(
'scrfd',
detector = SCRFD(
model_name=SCRFDWeights.SCRFD_10G_KPS,
conf_thresh=0.5
)
```
### Recognition Models
```python
from uniface import ArcFace, MobileFace, SphereFace
from uniface.constants import MobileFaceWeights, SphereFaceWeights
# ArcFace (recommended for most use cases)
recognizer = ArcFace() # Best accuracy
# MobileFace (lightweight for mobile/edge)
recognizer = MobileFace(model_name=MobileFaceWeights.MNET_V2) # Fast, small size
# SphereFace (angular margin approach)
recognizer = SphereFace(model_name=SphereFaceWeights.SPHERE20) # Alternative method
```
---
## Common Issues
@@ -316,20 +331,22 @@ print("Available providers:", ort.get_available_providers())
### 3. Slow Performance on Mac
Make sure you installed with CoreML support:
The standard installation includes ARM64 optimizations for Apple Silicon. If performance is slow, verify you're using the ARM64 build of Python:
```bash
pip install uniface[silicon]
python -c "import platform; print(platform.machine())"
# Should show: arm64 (not x86_64)
```
### 4. Import Errors
```python
# ✅ Correct imports
from uniface import RetinaFace, ArcFace, Landmark106
from uniface.detection import create_detector
# Correct imports
from uniface.detection import RetinaFace
from uniface.recognition import ArcFace
from uniface.landmark import Landmark106
# ❌ Wrong imports
# Wrong imports
from uniface import retinaface # Module, not class
```