app.py

import gradio as gr
import kornia as K
from kornia.core import Tensor
import torch
import numpy as np

# Define Functions
def process_image(file):
 if isinstance(file, np.ndarray):
 # If the input is already a numpy array, convert it to a tensor
 img = K.image_to_tensor(file).float() / 255.0
 else:
 # If it's a file path, load it using kornia
 img = K.io.load_image(file, K.io.ImageLoadType.RGB32)
 return img.unsqueeze(0) # Add batch dimension: 1xCxHxW

def box_blur_fn(file, box_blur):
 img = process_image(file)
 x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
 return K.utils.tensor_to_image(x_out.squeeze())

def blur_pool2d_fn(file, blur_pool2d):
 img = process_image(file)
 x_out: Tensor = K.filters.blur_pool2d(img, int(blur_pool2d))
 return K.utils.tensor_to_image(x_out.squeeze())

def gaussian_blur_fn(file, gaussian_blur2d):
 img = process_image(file)
 x_out: Tensor = K.filters.gaussian_blur2d(img,
 (int(gaussian_blur2d), int(gaussian_blur2d)),
 (float(gaussian_blur2d)/2, float(gaussian_blur2d)/2))
 return K.utils.tensor_to_image(x_out.squeeze())

def max_blur_pool2d_fn(file, max_blur_pool2d):
 img = process_image(file)
 x_out: Tensor = K.filters.max_blur_pool2d(img, int(max_blur_pool2d))
 return K.utils.tensor_to_image(x_out.squeeze())

def median_blur_fn(file, median_blur):
 img = process_image(file)
 x_out: Tensor = K.filters.median_blur(img, (int(median_blur), int(median_blur)))
 return K.utils.tensor_to_image(x_out.squeeze())

# Define Examples
examples = [
 ["examples/monkey.jpg", 1],
 ["examples/pikachu.jpg", 1]
]

# Define Demos
box_blur_demo = gr.Interface(
 box_blur_fn,
 [
 gr.Image(type="numpy"),
 gr.Slider(minimum=1, maximum=20, step=1, value=10, label="Box Blur")
 ],
 "image",
 examples=examples,
)

blur_pool2d_demo = gr.Interface(
 blur_pool2d_fn,
 [
 gr.Image(type="numpy"),
 gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Blur Pool")
 ],
 "image",
 examples=examples,
)

gaussian_blur_demo = gr.Interface(
 gaussian_blur_fn,
 [
 gr.Image(type="numpy"),
 gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Gaussian Blur")
 ],
 "image",
 examples=examples,
)

max_blur_pool2d_demo = gr.Interface(
 max_blur_pool2d_fn,
 [
 gr.Image(type="numpy"),
 gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Max Pool")
 ],
 "image",
 examples=examples,
)

median_blur_demo = gr.Interface(
 median_blur_fn,
 [
 gr.Image(type="numpy"),
 gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Median Blur")
 ],
 "image",
 examples=examples,
)

# Create Interface
demo = gr.TabbedInterface(
 [
 box_blur_demo,
 blur_pool2d_demo,
 gaussian_blur_demo,
 max_blur_pool2d_demo,
 median_blur_demo
 ],
 [
 "Box Blur",
 "Blur Pool",
 "Gaussian Blur",
 "Max Pool",
 "Median Blur"
 ]
)

demo.launch()