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
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Use tensorflow-gpu for faster training time
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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)