Skip to content

Softdude47/Fine-Tunning-VGG16

Repository files navigation

Fine Tunning VGG16

Script

data_prep.py

  • info:
    • caches and preproces dataset to be used in training and testing the model
  • arguments:
    • --input_path: path to dataset
    • --output_path: full path(filename includede) to save the preprocessed and cached dataset
    • --dimension: dimension for any given feature sample of the dataset
    • --batch_size: number of feature and label to be preprocessed and cached the same time

fine_tunning.py

  • info:
    • loads the preprocessed/cached dataset and train a fine tunned VGG16 model
  • arguments:
    • --input_path[required]: path to cached/preprocessed dataset
    • --output_path[optional] : full path(filename includede) to save the train model
    • --epochs[optional]: number of training epochs
    • --train_size[optional] : fraction of dataset to be used to training
    • --learning_rate[optional] : learning rate of optimizer used in training model
    • --batch_size[optional] : number of feature and label samples to train model per each steps

re_train.py

  • info:
    • loads the fine tunned model and retrains it
  • arguments:
    • --input_path[required]: path to the existing model
    • --output_path[optional] : full path(filename includede) to save the re-trained model
    • --epochs[optional]: number of training epochs
    • --train_size[optional] : fraction of dataset to be used to training
    • --learning_rate[optional] : learning rate of optimizer used in training model
    • --batch_size[optional] : number of feature and label samples to train model per each steps

About

Fine Tunning vgg16 model and train it on a new datasets

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages