@app.post("/analyze/upload-models") async def upload_models(models: List[ModelInput]): """Upload multiple male models for analysis""" model_objects = [MaleModel( id=f"M{idx:04d}", name=m.name, height_cm=m.height_cm, agency=m.agency, category=m.category ) for idx, m in enumerate(models)]
@app.get("/analyze/outliers") async def detect_outliers(multiplier: float = Query(1.5, ge=1.0, le=3.0)): """Detect height outliers using IQR method""" # Implementation would use analyzer pass # Sample data sample_models = [ MaleModel("M001", "John Doe", 188, "6'2\"", "Elite Models", "runway"), MaleModel("M002", "Mike Smith", 185, "6'1\"", "IMG Models", "runway"), MaleModel("M003", "Alex Chen", 178, "5'10\"", "Wilhelmina", "commercial"), MaleModel("M004", "Chris Evans", 183, "6'0\"", "Ford Models", "fitness"), MaleModel("M005", "David Kim", 192, "6'3.6\"", "Next Models", "runway"), MaleModel("M006", "Tom Wilson", 175, "5'9\"", "Elite Models", "commercial"), MaleModel("M007", "James Brown", 195, "6'4.8\"", "IMG Models", "runway"), ] Analyze analyzer = MaleModelHeightAnalyzer(sample_models) print(analyzer.generate_height_report()) Visualize visualizer = HeightVisualizer(analyzer) visualizer.plot_height_distribution("height_analysis.png") Get category fit category_fit = analyzer.category_fit() for model_id, info in category_fit.items(): print(f"{info['name']}: {info['height_ft_in']} - Suitable for {', '.join(info['suitable_categories'])}") height of male models
def height_outliers(self, multiplier: float = 1.5) -> List[Dict]: """Detect height outliers using IQR method""" if len(self.heights) < 4: return [] q1 = statistics.quantiles(self.heights, n=4)[0] q3 = statistics.quantiles(self.heights, n=4)[2] iqr = q3 - q1 lower_bound = q1 - multiplier * iqr upper_bound = q3 + multiplier * iqr outliers = [] for model in self.models: if model.height_cm < lower_bound or model.height_cm > upper_bound: outliers.append({ "id": model.id, "name": model.name, "height_cm": model.height_cm, "height_ft_in": model.height_ft_in, "deviation": "below" if model.height_cm < lower_bound else "above" }) return outliers category=m.category ) for idx
@staticmethod def cm_to_ft_in(cm: float) -> str: total_inches = cm / 2.54 feet = int(total_inches // 12) inches = round(total_inches % 12, 1) return f"{feet}'{inches}\"" multiplier: float = 1.5) ->
@staticmethod def ft_in_to_cm(ft: int, inches: float) -> float: return (ft * 12 + inches) * 2.54 class MaleModelHeightAnalyzer: """Feature for analyzing male model heights""" # Industry standard height ranges (cm) RUNWAY_MIN = 185 # 6'1" RUNWAY_MAX = 192 # 6'3.6" COMMERCIAL_MIN = 175 # 5'9" COMMERCIAL_MAX = 190 # 6'2.8" FITNESS_MIN = 178 # 5'10" FITNESS_MAX = 188 # 6'2"