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Running
on
CPU Upgrade
mischeiwiller
commited on
Commit
•
2006f30
1
Parent(s):
12441f2
fix file handling
Browse files
app.py
CHANGED
@@ -1,109 +1,87 @@
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# created with great guidance from https://github.com/NimaBoscarino
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import gradio as gr
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import kornia as K
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from kornia.core import Tensor
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# Define Functions
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def
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x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
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return K.utils.tensor_to_image(x_out)
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def blur_pool2d_fn(file, blur_pool2d):
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# load the image using the rust backend
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img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
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img = img[None] # 1xCxHxW / fp32 / [0, 1]
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x_out: Tensor = K.filters.blur_pool2d(img, int(blur_pool2d))
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return K.utils.tensor_to_image(x_out)
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def gaussian_blur_fn(file, gaussian_blur2d):
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# load the image using the rust backend
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img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
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img = img[None] # 1xCxHxW / fp32 / [0, 1]
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(int(gaussian_blur2d), int(gaussian_blur2d)),
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(float(gaussian_blur2d), float(gaussian_blur2d)))
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return K.utils.tensor_to_image(x_out)
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def max_blur_pool2d_fn(file, max_blur_pool2d):
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img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
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img = img[None] # 1xCxHxW / fp32 / [0, 1]
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x_out: Tensor = K.filters.max_blur_pool2d(img, int(max_blur_pool2d))
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return K.utils.tensor_to_image(x_out)
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def median_blur_fn(file, median_blur):
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# load the image using the rust backend
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img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
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img = img[None] # 1xCxHxW / fp32 / [0, 1]
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x_out: Tensor = K.filters.median_blur(img, (int(median_blur), int(median_blur)))
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return K.utils.tensor_to_image(x_out)
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# Define Examples
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examples = [
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["examples/monkey.jpg", 1
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["examples/pikachu.jpg", 1
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]
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# Define Demos
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box_blur_demo = gr.Interface(
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box_blur_fn,
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[
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gr.Image(type="
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gr.Slider(minimum=1, maximum=20, step=1, value=10, label="Box Blur")
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],
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"image",
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examples=examples,
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)
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blur_pool2d_demo = gr.Interface(
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blur_pool2d_fn,
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[
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gr.Image(type="
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gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Blur Pool")
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],
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"image",
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examples=examples,
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)
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gaussian_blur_demo = gr.Interface(
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gaussian_blur_fn,
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[
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gr.Image(type="
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gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Gaussian Blur")
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],
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"image",
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examples=examples,
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)
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max_blur_pool2d_demo = gr.Interface(
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max_blur_pool2d_fn,
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[
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gr.Image(type="
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gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Max Pool")
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],
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"image",
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median_blur_demo = gr.Interface(
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median_blur_fn,
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[
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gr.Image(type="
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gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Median Blur")
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],
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"image",
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examples=examples,
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)
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# Create Interface
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demo = gr.TabbedInterface(
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[
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],
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[
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]
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)
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import gradio as gr
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import kornia as K
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from kornia.core import Tensor
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import torch
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import numpy as np
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# Define Functions
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def process_image(file):
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if isinstance(file, np.ndarray):
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# If the input is already a numpy array, convert it to a tensor
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img = K.image_to_tensor(file).float() / 255.0
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else:
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# If it's a file path, load it using kornia
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img = K.io.load_image(file, K.io.ImageLoadType.RGB32)
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return img.unsqueeze(0) # Add batch dimension: 1xCxHxW
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def box_blur_fn(file, box_blur):
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img = process_image(file)
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x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
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return K.utils.tensor_to_image(x_out.squeeze())
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def blur_pool2d_fn(file, blur_pool2d):
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img = process_image(file)
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x_out: Tensor = K.filters.blur_pool2d(img, int(blur_pool2d))
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return K.utils.tensor_to_image(x_out.squeeze())
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def gaussian_blur_fn(file, gaussian_blur2d):
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img = process_image(file)
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x_out: Tensor = K.filters.gaussian_blur2d(img,
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(int(gaussian_blur2d), int(gaussian_blur2d)),
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(float(gaussian_blur2d)/2, float(gaussian_blur2d)/2))
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return K.utils.tensor_to_image(x_out.squeeze())
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def max_blur_pool2d_fn(file, max_blur_pool2d):
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img = process_image(file)
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x_out: Tensor = K.filters.max_blur_pool2d(img, int(max_blur_pool2d))
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return K.utils.tensor_to_image(x_out.squeeze())
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def median_blur_fn(file, median_blur):
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img = process_image(file)
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x_out: Tensor = K.filters.median_blur(img, (int(median_blur), int(median_blur)))
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return K.utils.tensor_to_image(x_out.squeeze())
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# Define Examples
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examples = [
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["examples/monkey.jpg", 1],
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["examples/pikachu.jpg", 1]
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]
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# Define Demos
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box_blur_demo = gr.Interface(
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box_blur_fn,
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[
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gr.Image(type="numpy"),
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gr.Slider(minimum=1, maximum=20, step=1, value=10, label="Box Blur")
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],
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"image",
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examples=examples,
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)
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blur_pool2d_demo = gr.Interface(
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blur_pool2d_fn,
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[
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gr.Image(type="numpy"),
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gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Blur Pool")
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],
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"image",
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examples=examples,
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)
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gaussian_blur_demo = gr.Interface(
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gaussian_blur_fn,
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[
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gr.Image(type="numpy"),
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gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Gaussian Blur")
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],
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"image",
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examples=examples,
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)
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max_blur_pool2d_demo = gr.Interface(
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max_blur_pool2d_fn,
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[
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gr.Image(type="numpy"),
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gr.Slider(minimum=1, maximum=40, step=1, value=20, label="Max Pool")
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],
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"image",
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median_blur_demo = gr.Interface(
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median_blur_fn,
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[
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gr.Image(type="numpy"),
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gr.Slider(minimum=1, maximum=30, step=2, value=15, label="Median Blur")
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],
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"image",
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examples=examples,
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)
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# Create Interface
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demo = gr.TabbedInterface(
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[
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box_blur_demo,
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blur_pool2d_demo,
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gaussian_blur_demo,
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max_blur_pool2d_demo,
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median_blur_demo
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],
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[
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"Box Blur",
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"Blur Pool",
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"Gaussian Blur",
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"Max Pool",
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"Median Blur"
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]
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)
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