import gradio as gr
import albumentations as A
import cv2
import numpy as np

def augment_image(image, flip=False, rotate=0, brightness=1.0, elastic=False, alpha=1.0, sigma=50):
    image = np.array(image)
    
    aug_list = []
    if flip: aug_list.append(A.HorizontalFlip(p=1.0))
    if rotate: aug_list.append(A.Rotate(limit=rotate, p=1.0))
    if brightness != 1.0: aug_list.append(A.RandomBrightnessContrast(brightness_limit=(brightness-1, brightness-1), p=1.0))
    if elastic: aug_list.append(A.ElasticTransform(alpha=alpha, sigma=sigma, alpha_affine=None, p=1.0))
    
    aug = A.Compose(aug_list)
    augmented = aug(image=image)
    
    return augmented["image"]

def image_augmentor_interface(image, flip, rotate, brightness, elastic, alpha, sigma):
    augmented_image = augment_image(image, flip, rotate, brightness, elastic, alpha, sigma)
    return augmented_image

iface = gr.Interface(
    fn=image_augmentor_interface,
    inputs=[
        gr.Image(type="numpy"),
        gr.Checkbox(label="Flip Horizontally"),
        gr.Slider(0, 360, label="Rotate Degrees"),
        gr.Slider(0.5, 1.5, step=0.1, value=1, label="Brightness Adjustment"),
        gr.Checkbox(label="Elastic Distortion"),
        gr.Slider(1.0, 200.0, step=1.0, label="Elastic Alpha (distortion intensity)"),
        gr.Slider(1.0, 100.0, step=1.0, label="Elastic Sigma (smoothness)")
    ],
    outputs="image",
    title="Image Augmentation with Gradio"
)

iface.launch(share=True)