This project (among others) has been submitted for my Jedha Data Fullstack program certification
Checkout the 10min project presentation video (in French) here: https://share.vidyard.com/watch/PH1jj9pV9vEUB1fWdwVQg9?
Deep chef is an online app that helps you find the recipe you need. Take a picture of you fruits and vegetables, the app will recognize it and suggest different recipes.
Try the app here!👉 https://deepchef-app.herokuapp.com/
We used different tools to create the systems interacting with each other in this app:
- Collect data from OpenImageV6 Database with NanoCode012's OIDv6_ToolKit_Download_Open_Images_Support_Yolo_Format
- Train a YoloV5 model to recognise ingredients with ultralytics' yolov5
- Load the model on FastAPI deployed with Heroku
- Get recipes with Spoonacular API
- The online app created with streamlit deployed with Heroku
A special dataset containing 10 000 images was fetched from OpenImageV6 Database. It is available on RoboFlow at https://app.roboflow.com/ds/asCOwPsjUr?key=1nVXvQ7xsQ . To download and extract use command
curl -L "https://app.roboflow.com/ds/asCOwPsjUr?key=1nVXvQ7xsQ" > roboflow.zip; unzip roboflow.zip; rm roboflow.zip
- The source code is written in Python 3.
- To localy run app and API you need Docker and Heroku
Follow instruction in NanoCode012's repository. Command python main.py downloader --classes classes.txt --type_csv all --yoloLabelStyle --multiclasses 1 --limit 600
where classes.txt is the list of ingredients you want.
Follow instruction in ultralytics' repository. Command python train.py --img 640 --batch-size 16 --epochs 50 --save-period 10 --data yolov5s.yaml --weights yolov5s.pt --freeze 10
for example.
Quentin Gottafray
Antoine Costes
Christopher Gbezo
Baptiste Eluard
Léa Boussekeyt
App link: https://deepchef-app.herokuapp.com/
Project presentation: https://docs.google.com/presentation/d/1eNNhturBgnbf9MO3AZ3NRq6GgE9U0vso55SP4R5BbA8/edit?usp=sharing
Project presentation video: