Healthy home meals is a web app which enables users to take a picture of their refrigerator, or items over the kitchen top, detects the ingredients present in the picture along with the ones they usually have at home, considers allergies and dietary styles like vegan, lactose-free etc, and recommends healthy recipes that they can make at home. They include detailed step-by-step instructions, youtube video, and other info like cuisine, and cooking time from a dataset of over 5000 Indian recipes.
Tech used | For |
---|---|
React.js | Frontend |
Flask | Backend |
MongoDB | Database |
Tensorflow and CustomVision | ML model to detect ingredients in picture |
SciKit Learn | ML model to find matching recipes |
Google Cloud | Hosting |
Cloudflare | CDN for static data |
- Open frontend/src/index.js and update window.APIROOT to the base URL for the backend. Default URL is given below.
window.APIROOT = "http://127.0.0.1:4950/"
- Run the below command in frontend folder.
npm install
- Run the below command in backend folder.
pip install -r requirements.txt
- Create an OAuth client ID in Google cloud console with the below info.
# Authorized JavaScript origins
http://127.0.0.1:4950
https://127.0.0.1:4950
# Authorized redirect URIs
http://127.0.0.1:4950/callback
https://127.0.0.1:4950/callback
-
Download the client_secret.json file and save it in the backend folder.
-
Create a YouTube Data API v3 key from Google cloud console.
-
Include an attribute data in the client_secret.json file as below.
{
"web": {
// No changes here
},
"data": {
"redirect_uri": "http://127.0.0.1:4950/callback",
"home": "http://127.0.0.1:3000",
"mongo": "MongoDB URL here",
"youtube": "YouTube Data API v3 key here"
}
}
Run the below command in the frontend folder.
npm run start
Run the below command in the backend folder.
python main.py