Update README.md

README.md

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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 The dataset we are using is the Standford Dog Dataset (http://vision.stanford.edu/aditya86/ImageNetDogs/) 
-As this dataset were built using ImageNet images, the images can be normalized using the mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225] this will assure that the neural network will have and mean of 0 and standar deviation of 1
+As this dataset were built using ImageNet images, the images can be normalized using the mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225] this will assure that the neural network will have and mean of 0 and standar deviation of 1.
+
+The input of the application is an image of a dog that you can insert through the UI built with Gradio.
+The output of the application is a text describing the breed of the dog or the closest breed that the model predicted for the image.
+
+# Prediction Task
+The task the application will be performing is classification. Specifically, the classification of images of dogs, with the objective of accurately classifying them according to their breed. As such, the input will be images of dogs, and the possible values for the output will be one of one hundred and twenty two different breeds; e.g. Poodle, Briard, Newfoundland, Bluetick, etc.
+
+# Data collection
+The initial train dataset will be the Stanford Dogs dataset. The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization[1]. Contents of this dataset:
+
+Number of categories: 120
+Number of images: 20,580
+Annotations: Class labels, Bounding boxes
+
+# Making Predictions
+To make a prediction, the model will be available for interaction in the HuggingFace platform, over at https://huggingface.co/spaces/Samood/whos_that_doggo
+Building models 
+The application is based on a single model, based on a pre-trained ANN, ResNet50. Additional layers have been added for the purpose of dog breed classification and the pre-trained layers were frozen.
+