fast-ai-utils.py

# fast.ai Lesson 1
def create_validation_set(from_path, to_path, percentage = 0.2):
    count_files_from_path = len(os.listdir(from_path))
    validation_count = percentage * count_files_from_path
    print('Lets copy {}/{} files for validation'.format(validation_count, count_files_from_path))
    for i in range(int(validation_count)):
        random_path = random.choice(os.listdir(from_path))
        os.rename(from_path+random_path, to_path+random_path)

    print('Create {} Validation Set finished! '.format(percentage))    

# create_validation_set('/home/ec2-user/courses/deeplearning1/nbs/data/train/cat/', '/home/ec2-user/courses/deeplearning1/nbs/data/validation/cat/')
# create_validation_set('/home/ec2-user/courses/deeplearning1/nbs/data/train/dog/', '/home/ec2-user/courses/deeplearning1/nbs/data/validation/dog/')


def move_files_to_categories(from_directory):
    """
    It will move labeled images to respective folders.
    e.g. file cat_1.jpg will be moved to folder cat
    """
    for filename in os.listdir(from_directory):
        parts = filename.split('.')
        if len(parts) > 2 and parts[2] in ['jpg', 'jpeg', 'png']:
            category = from_directory + parts[0]
            if not os.path.exists(category):
                os.makedirs(category)
            print('Rename from {}'.format(from_directory+filename))
            os.rename(from_directory+filename, os.path.join(category, filename))
            print ('Moved file to {}'.format(os.path.join(category, filename)))
        
# move_files_to_categories('/home/ec2-user/courses/deeplearning1/nbs/data/train/')

def show_image(image_path):
    import matplotlib.image as mpimg    
    img=mpimg.imread(image_path)
    imgplot = plt.imshow(img)


# fast.ai Lesson 2
# fast.ai Lesson 3
# fast.ai Lesson 4
# fast.ai Lesson 5
# fast.ai Lesson 6
# fast.ai Lesson 7