Image-Segregator

To use Classifier.ipynb (To train the model): Load Drive: from google.colab import drive drive.mount('/content/drive/') Enter Dataset Directory: %cd ./AML_Project/Images/Training/ Run all cells sequentially.

To access the trained model:

1. Enter /content/drive/My Drive/AML_Project/Images/Training.
2. Load vgg16_1.h5. The model gets stored in /content/drive/My Drive/AML_Project/Images/vgg16_1.h5.

To test the model: Load the model from: /content/drive/My Drive/AML_Project/Images/vgg16_1.h5.

1. Enter /content/drive/My Drive/AML_Project/Test.
2. Specify the range of number of images that contain meme, text and human faces. The ranges can be manually seen( and separated) in : /content/drive/My Drive/AML_Project/Test/
3. Results of the test sets are stored in the following directories:

/content/drive/My Drive/AML_Project/Test/Humans_Classified.

/content/drive/My Drive/AML_Project/Test/Memes_Classified.

/content/drive/My Drive/AML_Project/Test/Text_Classified.