A raw facial geometry analyzer that measures your face against mathematical beauty standards. Built with Flask, OpenCV, and MediaPipe because I was curious about the science behind facial attractiveness.

Analyzes faces using actual research formulas:

• Rule of thirds (face divided into equal parts)
• Golden ratio proportions (1.618)
• Facial symmetry measurements
• Nose width ratios
• Lip proportion analysis

Gives you a brutal 0-100 score based purely on geometry.

This uses real research from actual scientists:

Marquardt (2002) - Found that attractive faces follow the golden ratio (1.618) Farkas et al. (1985) - Measured thousands of faces to find ideal proportions Rhodes et al. (1998) - Proved that symmetry equals attractiveness Powell & Humphreys (1984) - Mapped out the "perfect" face ratios

Rule of Thirds:

# Face should split into 3 equal parts
hairline_to_eyebrows = eyebrows_to_nose = nose_to_chin
deviation = how far off from perfect thirds
score = 20 points max

Golden Ratio:

face_length / face_width should equal 1.618
upper_lip / lower_lip should equal 1/1.6
actual_ratio compared to ideal_ratio = points

Symmetry:

left_eye_position vs right_eye_position
perfect_center = face_width / 2
symmetry_score = how close to perfect center

Nose Analysis:

nose_width / face_width should equal 0.28
deviation from 0.28 = point deduction

eros/
├── app.py              # Flask server
├── face_analyzer.py    # All the math happens here
├── static/
│   ├── assets/
│   │   ├── logo.png
│   │   └── upload.svg
│   ├── uploads/        # temp image storage
│   └── style.css
├── templates/
│   ├── index.html      # upload page
│   └── result.html     # results page
└── requirements.txt

git clone https://github.com/yourusername/eros.git
cd eros
pip install -r requirements.txt
python app.py

Go to localhost:5000

Check it out: erosweb.pythonanywhere.com

Flask==2.3.3
opencv-python==4.8.1.78
mediapipe==0.10.7
numpy==1.24.3
Pillow==10.0.1

1. MediaPipe detects 468 facial landmarks
2. Calculates distances between key points
3. Compares measurements to research-backed ideal ratios
4. Harsh scoring system - small deviations lose points fast
5. Gives you the raw numbers

def ratio_score(actual, ideal):
    deviation = abs(actual - ideal) / ideal
    if deviation <= 0.05: return 10      # perfect
    if deviation <= 0.2:  return 10 * (0.2 - deviation) / 0.15
    return 0  # you're cooked

landmarks = {
    "top": 10,        # hairline
    "brow": 9,        # eyebrow center
    "nose": 2,        # nose tip
    "chin": 152,      # chin bottom
    "left": 234,      # face left edge
    "right": 454,     # face right edge
    "eyeL": 133,      # left eye center
    "eyeR": 362,      # right eye center
    "noseL": 98,      # nose left
    "noseR": 327,     # nose right
    "lipU": 13,       # upper lip
    "lipM": 14,       # lip center
    "lipL": 17        # lower lip
}

Raw Brutal Report
Overall harsh score: 67.3/100
Vertical thirds deviation: 0.15 -> 14.0/20
Face ratio L/W: 1.45 -> 6.5/5
Symmetry factor: 0.89 -> 22.3/25
Nose width ratio: 0.31 -> 3.2/5
Lip balance ratio: 0.58 -> 4.8/5

This only measures geometry. It doesn't care about:

• Skin quality
• Eye color
• Hair
• Makeup
• Lighting
• Camera angle
• Facial expression
• Personal style

The scoring is intentionally harsh because tiny deviations from "perfect" proportions drop your score fast.

• Based on Western beauty standards
• Needs clear front-facing photos
• MediaPipe sometimes misses landmarks
• Beauty is way more complex than math
• Don't take this too seriously

If you want to add features or fix bugs, just fork it and make a pull request. Keep the code simple and the scoring brutal.

MIT License - do whatever you want with this code.

This is just math applied to faces. Your worth as a human isn't determined by facial geometry ratios. I built this because the science is interesting, not to make anyone feel bad about their face.

Use for fun/education only.