6cb0435b30
- Implemented FoodCameraScreen for capturing food images with meal type selection. - Created FoodRecognitionScreen for processing and recognizing food images. - Added Redux slice for managing food recognition state and results. - Integrated image upload functionality to cloud storage. - Enhanced UI components for better user experience during food recognition. - Updated FloatingFoodOverlay to navigate to the new camera screen. - Added food recognition service for API interaction. - Improved styling and layout for various components.
34 lines
799 B
TypeScript
34 lines
799 B
TypeScript
import { api } from '@/services/api';
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export type FoodNutritionData = {
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proteinGrams?: number;
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carbohydrateGrams?: number;
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fatGrams?: number;
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fiberGrams?: number;
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};
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export type FoodConfirmationOption = {
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id: string;
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label: string;
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foodName: string;
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portion: string;
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calories: number;
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mealType: string;
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nutritionData: FoodNutritionData;
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};
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export type FoodRecognitionRequest = {
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imageUrls: string[];
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};
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export type FoodRecognitionResponse = {
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items: FoodConfirmationOption[];
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analysisText: string;
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confidence: number;
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isFoodDetected: boolean;
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nonFoodMessage?: string;
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};
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export async function recognizeFood(request: FoodRecognitionRequest): Promise<FoodRecognitionResponse> {
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return api.post<FoodRecognitionResponse>('/ai-coach/food-recognition', request);
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} |