Unless otherwise specified, please download all models and place the entire folder under /saved_models
- Ingredients Image Classification [Download]
- Cuisine Classification [Download]
- D2VModel [Download]
- Recipe Database for D2VModel, put it under RecRes folder [Download]
- Models & Data for Attention Encoder Decoder [Download]
pip install -r requirements.txtPip-installed Tensorflow might not work, instead, install it with conda.
pip uninstall tensorflow
conda install tensorflowstreamlit run app.py| Dataset | Features | #Data | Remark | Used |
|---|---|---|---|---|
| Food Recommendation System - schemersays | name, ingredients, cuisines, ratings | 400 | ||
| Food.com - Recipes | name, preparing time, date, tags, nutrition, # cooking steps, description, ingredients, #ingredients | 180K | Provides raw and tokenize data. Paper. | |
| Food.com - Review of Recipes | date, rating | 700K | Provides raw and tokenize data. Paper. | |
| Indian Food and Its Recipes Dataset (With Images) | name, image_url, description, cuisine, course, diet, prep_time, ingredients, instructions | 4226 | Scraped from Archana's Kitchen | |
| MealRec | name, #reviews, category, aver_rate, image_url, ingredients, cooking_directions, nutritions, reviews, tags | 7280 | There are multiple reviews for one recipe | |
| Indian Food 101 | name, ingredients, diet, prep_time, cook_time, flavor_profile, course, state, region | 255 | ||
| foodRecSys-V1 | recipe_name, image_url, ingredients, cooking_directions, nutritions, rating | 45568 |
| Dataset | Features | #Data | Remark | Used |
|---|---|---|---|---|
| Restaurant Data with Consumer Ratings | payment type, operating hours, operating days, parking_lot, latitude, longitude, the_geom_meter, name, address, city, state, country, fax, zip, alchohol, smoking_area, dress_code, accessibility, price, url, Rambience, franchise, area, other_services, rating, food_rating, service_rating | - | Consist of multiple csv of users and restaurants with different length | |
| Micheline Guide Restaurants | name, address, location, price, cuisine, longitude, latitude, phoneNumber, Url, WebsiteUrl | 6653 |
| Name | Description | Remark |
|---|---|---|
| Scraping Google Reviews with Selenium(Python) | Web scraping google reviews via Selenium and BeautifulSoup | |
| recipe-recommendation-system | Data-driven recipe recommendation system using web-scraped recipe data (including but not limited to data like ingredients, health facts, etc.) and user’s historical preference | No access to dataset |
| recipes-telegram-bot | Telegram bot that can recommend recipes based on the ingredients you already have | Technical article on Medium |
| Food Recommendation using BERT | Based on cosine similarities computed on embedding from BERT | |
| Restaurant_recommendation_system | Recommend users based on ratings and comments of other visitors taking into consideration of their location and preferences | Slides |