100 lines
3.7 KiB
Python
100 lines
3.7 KiB
Python
from typing import Dict, Any
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from APIs.edamam import EdamamAPI
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from microwaveDishAnalyzer import MicrowaveDishAnalyzer
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from microwaveThermalEngine import MicrowaveThermalEngine, DishThermalState
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class MicrowaveCookPlanner:
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"""Orchestrates Edamam API, Dish Analyzer, and Thermal Engine into a single workflow."""
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def __init__(self, cm_per_pixel: float = 0.05):
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self.edamam_api = EdamamAPI()
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self.analyzer = MicrowaveDishAnalyzer(cm_per_pixel=cm_per_pixel)
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self.engine = MicrowaveThermalEngine()
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def _extract_edamam_data(self, edamam_resp: Dict[str, Any]) -> tuple[str, float, Dict[str, float]]:
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"""Parses Edamam Vision response to extract label, total mass, and macronutrient grams."""
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recipe = edamam_resp.get("combined", {}).get("recipe", {})
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# Fallback to first dish if 'combined' is empty
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if not recipe and edamam_resp.get("dishes"):
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recipe = edamam_resp["dishes"][0].get("recipe", {})
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label = recipe.get("label", "Unknown Dish")
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total_weight = float(recipe.get("totalWeight", 300.0)) # Default 300g fallback
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nutrients = recipe.get("totalNutrients", {})
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# Extract macronutrients in grams (Edamam nutrient codes)
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fat_g = float(nutrients.get("FAT", {}).get("quantity", 0.0))
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protein_g = float(nutrients.get("PROCNT", {}).get("quantity", 0.0))
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carbs_g = float(nutrients.get("CHOCDF", {}).get("quantity", 0.0))
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# Water is sometimes omitted in Edamam; infer remaining mass as water if missing
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if "WATER" in nutrients:
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water_g = float(nutrients["WATER"].get("quantity", 0.0))
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else:
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water_g = max(0.0, total_weight - (fat_g + protein_g + carbs_g))
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macros = {
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"water_g": water_g,
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"fat_g": fat_g,
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"protein_g": protein_g,
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"carbs_g": carbs_g,
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}
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return label, total_weight, macros
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def generate_plan(
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self,
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image_path: str,
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height_cm: float,
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initial_temp_c: float,
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microwave_wattage: int = 900,
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defrost_mode: bool = False
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) -> Dict[str, Any]:
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"""Main pipeline call to parse an image and return cooking parameters."""
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# 1. Vision & Nutrient Analysis
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edamam_resp = self.edamam_api.analyze_dish_image(image_path)
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food_label, edamam_mass_g, macros = self._extract_edamam_data(edamam_resp)
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# 2. Geometric Volume Calculation
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vol_data = self.analyzer.estimate_volume(
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image_path=image_path,
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height_cm=height_cm,
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food_label=food_label
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)
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# 3. Mass Cross-Validation & Density Check
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mass_data = self.analyzer.reconcile_mass(
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edamam_mass_g=edamam_mass_g,
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volume_cm3=vol_data["volume_cm3"],
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food_label=food_label
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)
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final_mass_g = mass_data["final_mass_g"]
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# 4. Thermal State Creation
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thermal_state = DishThermalState(
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food_name=food_label,
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macronutrients=macros,
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estimated_mass_g=final_mass_g,
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initial_temp_c=initial_temp_c,
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volume_cm3=vol_data["volume_cm3"]
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)
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# 5. Cook Plan Calculation
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cook_plan = self.engine.calculate_cook_plan(
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state=thermal_state,
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microwave_wattage=microwave_wattage,
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defrost_mode=defrost_mode
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)
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# Return consolidated output
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return {
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"dish_name": food_label,
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"reconciled_mass_g": final_mass_g,
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"mass_validation_status": mass_data["status"],
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"cook_plan": cook_plan,
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"geometry": vol_data
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} |