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title: Foodrecipe Ai | |
emoji: 🔥 | |
colorFrom: purple | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 4.25.0 | |
app_file: app.py | |
pinned: false | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
# Recipe Application Based on Food101 | |
This application utilizes image recognition technology to identify food items from images and provides appropriate recipes. It leverages AI and machine learning to offer quick recipe suggestions based on the identified dish, making cooking more accessible and enjoyable. | |
## Features | |
- Identify food items from images using deep learning models. | |
- Provide recipe suggestions based on the identified food item. | |
- Utilize the Food101 dataset for training and testing. | |
- Simple and user-friendly interface powered by Gradio. | |
## Installation | |
To run this application locally, follow these steps: | |
### 1. Clone the Repository | |
``` | |
git clone https://github.com/your-username/recipe-app.git | |
cd recipe-app | |
``` | |
### 2. Install Requirements | |
``` | |
pip install -r requirements.txt | |
``` | |
### 3. Run the Gradio App | |
``` | |
python app.py | |
``` | |
## Usage | |
After running the script, you will see an output similar to this: | |
``` | |
Running on local URL: http://127.0.0.1:7860/ | |
``` | |
Open the provided URL in your web browser to interact with the application. You can upload food images, and the app will identify the dish and provide recipe suggestions. | |
## Data and Model | |
The application is based on the Food101 dataset, which includes 101,000 images across 101 categories of food. We use deep learning models like ResNet-50, Vision Transformer (ViT), and EfficientNet for image classification. | |