Here I used transfer learning to generate new recepi. The dataset consists of a lot of basic food items like egg, soup, bread etc. I also performed some image augmentation to increase the no of training dataset. I used the trained model InceptionResNetV2 which has almost 54M parameter. Then I add some other layer with this model and train 43k parameter. The training will take a lot of time. Thats why after training I commented out the cells.
The notebook contains a lot of theory that is needed for the model. Also you can check the image folder for the theory.
Source code for python is added with .ipynb format
Folders and files
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