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Predict food (Fruits and Vegetables) images using Python

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Food Recognition GUI

Food Recognition GUI

Food Recognition GUI using Python

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Built With

Dataset

Fruits and Vegetables Image Recognition Dataset Source: Fruits and Vegetables Image Recognition Dataset

  1. Context :
    the dataset contains images of the following food items:
  • fruits: banana, apple, pear, grapes, orange, kiwi, watermelon, pomegranate, pineapple, mango.
  • vegetables: cucumber, carrot, capsicum, onion, potato, lemon, tomato, raddish, beetroot, cabbage, lettuce, spinach, soy bean, cauliflower, bell pepper, chilli pepper, turnip, corn, sweetcorn, sweet potato, paprika, jalepeño, ginger, garlic, peas, eggplant.
  1. Content :
    This dataset contains three folders:
  • train (100 images each)
  • test (10 images each)
  • validation (10 images each)

Nutrition API

Nutrition API Source: Calorie Ninjas API

  • Nutrition and recipe data for 100.000+ foods and beverages
  • Free Plan gives 10.000 API calls/month
  • Add your api in chartstest.py

Installation

  1. Clone the repo
git clone https://github.com/hamzaezzine/Food-Recognition-GUI.git
  1. Install the required dependencies:
pip install -r requirements.txt

Usage

Run the main python file

python main.py

Screenshots

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