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# created with great guidance from https://github.com/NimaBoscarino
import gradio as gr
import kornia as K
from kornia.core import Tensor
# Define Functions
def box_blur_fn(file, box_blur):
# load the image using the rust backend
img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
img = img[None] # 1xCxHxW / fp32 / [0, 1]
x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
return K.utils.tensor_to_image(x_out)
def blur_pool2d_fn(file, blur_pool2d):
# load the image using the rust backend
img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
img = img[None] # 1xCxHxW / fp32 / [0, 1]
x_out: Tensor = K.filters.blur_pool2d(img, int(blur_pool2d))
return K.utils.tensor_to_image(x_out)
def gaussian_blur_fn(file, gaussian_blur2d):
# load the image using the rust backend
img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
img = img[None] # 1xCxHxW / fp32 / [0, 1]
x_out: Tensor = K.filters.gaussian_blur2d(img,
(int(gaussian_blur2d), int(gaussian_blur2d)),
(float(gaussian_blur2d), float(gaussian_blur2d)))
return K.utils.tensor_to_image(x_out)
def max_blur_pool2d_fn(file, max_blur_pool2d):
# load the image using the rust backend
img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
img = img[None] # 1xCxHxW / fp32 / [0, 1]
x_out: Tensor = K.filters.max_blur_pool2d(img, int(max_blur_pool2d))
return K.utils.tensor_to_image(x_out)
def median_blur_fn(file, median_blur):
# load the image using the rust backend
img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
img = img[None] # 1xCxHxW / fp32 / [0, 1]
x_out: Tensor = K.filters.median_blur(img, (int(median_blur), int(median_blur)))
return K.utils.tensor_to_image(x_out)
# Define Examples
examples = [
["examples/monkey.jpg", 1, 1, 1, 1, 1],
["examples/pikachu.jpg", 1, 1, 1, 1, 1],
]
# Define Demos
box_blur_demo = gr.Interface(
box_blur_fn,
[
gr.inputs.Image(type="file"),
gr.inputs.Slider(minimum=1, maximum=20, step=1, default=1, label="Box Blur")
],
"image",
examples=examples,
# title=title,
# description=description,
# article=article,
live=True
)
blur_pool2d_demo = gr.Interface(
blur_pool2d_fn,
[
gr.inputs.Image(type="file"),
gr.inputs.Slider(minimum=1, maximum=40, step=1, default=1, label="Blur Pool")
],
"image",
examples=examples,
# title=title,
# description=description,
# article=article,
live=True
)
gaussian_blur_demo = gr.Interface(
gaussian_blur_fn,
[
gr.inputs.Image(type="file"),
gr.inputs.Slider(minimum=1, maximum=25, step=2, default=1, label="Gaussian Blur")
],
"image",
examples=examples,
# title=title,
# description=description,
# article=article,
live=True
)
max_blur_pool2d_demo = gr.Interface(
max_blur_pool2d_fn,
[
gr.inputs.Image(type="file"),
gr.inputs.Slider(minimum=1, maximum=40, step=1, default=1, label="Max Pool")
],
"image",
examples=examples,
# title=title,
# description=description,
# article=article,
live=True
)
median_blur_demo = gr.Interface(
median_blur_fn,
[
gr.inputs.Image(type="file"),
gr.inputs.Slider(minimum=1, maximum=25, step=2, default=1, label="Median Blur")
],
"image",
examples=examples,
# title=title,
# description=description,
# article=article,
live=True
)
# 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() |