---
# System prepended metadata

title: FoodPath

---

# FoodPath
## Table of Contents
1. [Overview](#Overview)
2. [Product Spec](#Product-Spec)
3. [Wireframes](#Wireframes)
4. [Schema](#Schema)

## Overview
### Description
Helps users recognize an unknown food dish through image recognition and by specifying the ingredients used in the dish. The app will then recommend and redirect users to other websites that contain the recipes for said dish.

### App Evaluation
- **Category:** Food
- **Mobile:** This app would be primarily developed for mobile. Functionality is limited to mobile devices, specifically only for iOS.
- **Story:** Analyzes the unknown food dish specified by user either through taking a picture or by specifying the ingredients. The user can then choose from a list of recommended recipes to said dish.
- **Market:** Any individual could choose to use this app. This app is targeted so that it is user-friendly and is not hard to navigate through.
- **Habit:** This app could be used as often or unoften as the user wanted depending on how interested they are in cooking. This app aims to also increase the user's interest in cooking.
- **Scope:** First we would ensure that the app successfully recognizes the unknown food dish through image recognition and by specifying its ingredients. From there, our app will recommend a few dishes based off the results above, of which will then recommend a list of recipes accordingly. In the future, we are looking to implement more features to enhance the user's experience, such as through daily recommendations of recipes, history tracking etc.

## Video Walkthrough

Here's a walkthrough of implemented user stories:

<img src= "https://user-images.githubusercontent.com/43968366/142963603-87182839-a010-439a-8ce3-d4fe7063dde6.gif" width=250 height=500>
<img src="./foodRecommenderAPI.mp4" width=250 height=500>


## Product Spec
### 1. User Stories (Required and Optional)
**Required Must-have Stories**
- [x] User can select from a predefined list of ingredients
- [x] User can be recommended a food dish based off the image taken by user
- [x] User can access camera to take a picture of their food
- [x] User can be recommended a list of food dishes based off the user's selected ingredients
- [ ] User can select the from a list of recommended food dishes
- [ ] User can select from a list of recommended recipes
- [ ] User can be redirected to the website of the recipe

**Optional Nice-to-have Stories**
- [ ] User can save recipes for later reference 
- [ ] User can discover different recipes (be recommended different recipes) based on time of day 
- [ ] User can see a list of recent searches
- [ ] User can change the settings of the app (ex: dark mode)

### 2. Screen Archetypes
* Discover Today *(optional)*
    - User can discover various recipes (get recommendations) 
* Stream
    - User can select from a predefined list of ingredients
    - User can access camera to take a picture of their food
    - User can see a list of recent searches *(optional)*
* Camera
    - User can take a picture of their food
* Food Picker 
    - User can select from a list of recommended food dishes
* Details of Recipes 
    - User can select from multiple recommended recipes 
    - User can save their favorite recipes *(optional)*
    - User gets redirected to the website of the recipe    
* Settings *(optional)*
    - User can change the settings of the app    

### 3. Navigation
**Nav Bar:**
*    Back Button
*    Home button
        
**Flow Navigation:**
* Discover Today *(optional)*
&#8594; Stream
* Stream
&#8594; Discover Today *(optional)*
&#8594; Camera
* Camera
&#8594; Stream
&#8594; Food Picker
* Food Picker 
&#8594; Stream
&#8594; Details of Recipes
* Details of Recipes
&#8594; Stream
&#8594; Image/Name/bookmarking option *(optional)*
&#8594; Redirect to website
&#8594; Food picker
* Settings *(optional)*
&#8594; Stream

## Wireframes
![](https://i.imgur.com/XIC1GFg.jpg)

### [BONUS] Digital Wireframes & Mockups
![](https://i.imgur.com/uTD3Gyd.jpg)

## Schema
### Models
#### checkIngredients/getIngredientsFromAPI
|Property    |Type        |Description        |
|:----:        |:----:        |:----:            |
|ingredientId    |INT    |unique identifier for predefined ingredient|
|ingredientName    |STRING        |name of predefined ingredient|
|isChecked    |BOOL    |boolean value to check if ingredient has been selected (True/False)|

#### choooseIngredients
| Property | Type | Description |
| -------- | -------- | -------- |
|  ingredientId   | INT     |  unique identifier for predefined ingredient    |
| ingrediemntName| STRING| name for predefined ingredient

#### postImage
| Property | Type | Description |
| -------- | -------- | -------- |
|  imageId   | INT     |  unique identifier for image    |
| image| FILE| image that user uploads

#### getIngredientsFromAPI
| Property | Type | Description |
| -------- | -------- | -------- |
|  ingredientId   | INT     |  unique identifier for predefined ingredient    |
| ingrediemntName| STRING| name for predefined ingredient

#### postDish
| Property | Type | Description |
| -------- | -------- | -------- |
|  imageID   | INT     |  unique identifier for image    |
| image|FILE| image that user uploads|
|ingredientDict| DICT| dictionary to store all ingredients specified by user, identified by ingredientId|

#### getFoodFromAPI/postSearch
| Property | Type | Description |
| -------- | -------- | -------- |
|  foodId   | INT     |  unique identifier for food dish |
| foodName| STRING| food dish that is recommended by the API|

#### getRecipesFromAPI
| Property | Type | Description |
| -------- | -------- | -------- |
|  websiteTitle   | STRING|name of website |
| websiteURL| LINK| link to website|

### Networking
#### List of network requests by screen
- Stream
    - (Read/GET) query all predefined ingredients whose name is query string
    - (Update/PUT) update checked value of predefined ingredient (isChecked is True/False)
- Camera
    - (Create/POST) upload an image for image recognition 
- Image Recognition Details
    - (Read/GET) query all recognized ingredients from list of predefined ingredients from uploaded image using image recognition API
    ```
    let labeler = Vision.vision().cloudImageLabeler()
     labeler.process(image) { labels, error in
        guard error == nil, let labels = labels else { return }

        // Task succeeded.
        // ...
     }
     for label in labels {
        let labelText = label.text
        let entityId = label.entityID
        let confidence = label.confidence
     }
    ```
    - (Update/PUT) update checked value of predefined ingredient (isChecked is True/False)
- Food Picker
    - (Read/GET) query all selected predefined ingredients
    - (Create/POST) upload either both image and list of selected ingredients or just the list of selected ingredients to food search api 
    - (Read/GET) query all recognized food dishes from food search api
    
    ```
    let url = URL(string: someString)!
        let request = URLRequest(url: url, cachePolicy: .reloadIgnoringLocalCacheData, timeoutInterval: 10)
        let session = URLSession(configuration: .default, delegate: nil, delegateQueue: OperationQueue.main)
        let task = session.dataTask(with: request) { (data, response, error) in
             if let error = error {
                    print(error.localizedDescription)
             } else if let data = data {
                    let dataDictionary = try! JSONSerialization.jsonObject(with: data, options: []) as! [String: Any]
                    
                 let foods = dataDictionary["recipes_results"] as! [[String:Any]]
                 
                 //Prints out each possible recipe
                 for recipe in foods {
                     print(recipe["title"] as! String)
 
    ```
- Details of Recipes
    - (Create/POST) upload name of food dish to recipe search api
    - (Read/GET) query all recipes related to food dish

          ```
          var unirest = require("unirest");
          var req = unirest("GET", "https://mytweetmark-homecook.p.rapidapi.com/markets");

             seq.query({
            "searchMarket": "San" });

            req.headers({
            "x-rapidapi-key": "SIGN-UP-FOR-KEY",
            "x-rapidapi-host": "mytweetmark-homecook.p.rapidapi.com",
            "useQueryString": true
                        });


            req.end(function (res) {
            if (res.error) throw new Error(res.error);

            console.log(res.body);
                    });

    

### [Optional] Existing API endpoints
Google Cloud Vision API - label_detection
|HTTP Verb|Endpoint|Description|
|:----:|:----:|:----:|
|`GET`|/mid|if present, contains a machine-generated identifier (MID) corresponding to the entity's Google Knowledge Graph entry|
|`GET`|/description|the label description|
|`GET`|/score|the confidence score, which ranges from 0 (no confidence) to 1 (very high confidence)|
|`GET`|/topicality|The relevancy of the ICA (Image Content Annotation) label to the image. It measures how important/central a label is to the overall context of a page|


