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from transformers import pipeline | |
from PIL import Image | |
import gradio as gr | |
import os | |
import requests | |
import json | |
model_name = "larimei/food-classification-ai" | |
classifier = pipeline("image-classification", model=model_name) | |
def predict_image(image): | |
predictions = classifier(image) | |
meal_name = predictions[0]['label'] | |
recipe_text = getRecipe(meal_name) | |
meal_info = f"This is {meal_name.replace('_', ' ')}." | |
return meal_info, recipe_text | |
def getRecipe(meal): | |
app_id = "24bf0913" | |
app_key = "03c60f26520f9d25b0d0617e50993aaa" | |
field = ["uri", "label", "image", "ingredientLines", "source", "url"] | |
url = "https://api.edamam.com/api/recipes/v2" | |
querystring = { | |
"type": "public", | |
"q": meal.replace("_", " "), | |
"app_id": app_id, | |
"app_key": app_key, | |
"field": field | |
} | |
response = requests.get(url, params=querystring) | |
json_object = response.json() | |
returnString = "It is made out of the following ingredients: \n\n" | |
for line in json_object["hits"][0]["recipe"]["ingredientLines"]: | |
returnString += line + "\n" | |
returnString += "\n You can make " + json_object["hits"][0]["recipe"]["label"] + " yourself by following the steps of this instruction: " + json_object["hits"][0]["recipe"]["url"] | |
return returnString | |
title = "Recipifier" | |
description = "Discover the world of recipes effortlessly with Recipifier, using advanced AI trained on the extensive Food-101 dataset. Simply upload a photo of any dish, and our application identifies it accurately, providing detailed recipes and cooking instructions sourced from a vast collection. Perfect for food enthusiasts and home chefs alike, Recipifier makes exploring new culinary creations intuitive and inspiring. Start transforming everyday ingredients into extraordinary meals today!" | |
example_list = [["examples/" + example] for example in os.listdir("examples")] | |
css = """ | |
#component-13 { | |
display: none; | |
} | |
""" | |
demo = gr.Interface( | |
fn=predict_image, | |
inputs=gr.Image(type="pil"), | |
outputs=[ | |
gr.Textbox(label="Meal", elem_id="meal"), | |
gr.Textbox(label="Recipe") | |
], | |
examples=example_list, | |
title=title, | |
description=description, | |
css=css, | |
flagging_options=None | |
) | |
demo.launch() | |