def get_training_data(self,datafolder):
        print("Loading training data...")

        training_data = []
        #Finds all files in datafolder
        filenames = os.listdir(datafolder)
        for filename in tqdm(filenames):
            #Combines folder name and file name.
            path = os.path.join(datafolder,filename)
            #Opens an image as an Image object.
            image = Image.open(path)
            #Resizes to a desired size.
            image = image.resize((self.image_width,self.image_height),Image.ANTIALIAS)
            #Creates an array of pixel values from the image.
            pixel_array = np.asarray(image)

            training_data.append(pixel_array)

        #training_data is converted to a numpy array
        training_data = np.reshape(training_data,(-1,self.image_width,self.image_height,self.channels))
        return training_data