robert-kamunde / food101project

Building a model for predicting food images using the famous FOOD-101 dataset.

Food101Project

• The dataset being used is [Food 101] (download it here https://www.kaggle.com/dansbecker/food-101)

• This dataset has 101000 images in total. It's a food dataset with 101 categories(multiclass)
  • Each type of food has 750 training samples and 250 test samples
  • The entire dataset is about 5GB in size

• Use tensorflow-gpu for faster training time

• You need to have the food-101 dataset in your working directory (otherwise you should change the paths to the food-101 file)

• Run food101Work.py to create the train set and test set from the dataset.
• Run Food101Model.py to tune and train the model ( a MobileNetV2 Pretrained model is used and tuned to the food-101 dataset )
• Run Prediction_food_images.py to predict new food images. ( the images to be predicted here were in the working directory, if you have them in another location you should change the path)

food101project's Issues

Can you provide complete project files, such as project structure diagrams, as well as dependent environments and packages

Working with less dataset

i cant run the food101model.py in a smaller dataset of 19 classes. please help with this issue