Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,211 Bytes
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import spaces
import numpy as np
from pixeloe.pixelize import pixelize
from PIL import Image
import gradio as gr
@spaces.GPU
def pixelize_image(
image,
downscale_mode="contrast",
target_size=128,
patch_size=16,
thickness=2,
color_matching=True,
upscale=True
):
"""
Apply pixelization effect to an image or batch of images.
"""
if isinstance(image, Image.Image):
image = np.array(image)
processed = pixelize(
image,
mode=downscale_mode,
target_size=target_size,
patch_size=patch_size,
thickness=thickness,
contrast=1.0,
saturation=1.0,
color_matching=color_matching,
no_upscale=not upscale
)
return Image.fromarray(processed)
def process_image(image, downscale_mode, target_size, patch_size, thickness, color_matching, upscale):
if image is None:
return None
result = pixelize_image(
image,
downscale_mode=downscale_mode,
target_size=target_size,
patch_size=patch_size,
thickness=thickness,
color_matching=color_matching,
upscale=upscale
)
return result
def create_pixelize_tab():
with gr.Tab("Pixelizer"):
with gr.Row():
with gr.Column():
input_image = gr.Image(label="Input Image", type="pil", height=256)
downscale_mode = gr.Dropdown(
choices=["contrast", "bicubic", "nearest", "center", "k-centroid"],
value="contrast",
label="Downscale Mode"
)
target_size = gr.Slider(
minimum=8,
maximum=1024,
value=128,
step=8,
label="Target Size"
)
patch_size = gr.Slider(
minimum=4,
maximum=32,
value=16,
step=2,
label="Patch Size"
)
thickness = gr.Slider(
minimum=1,
maximum=16,
value=2,
step=1,
label="Thickness"
)
color_matching = gr.Checkbox(
value=True,
label="Color Matching"
)
upscale = gr.Checkbox(
value=True,
label="Upscale"
)
process_btn = gr.Button("Process Image")
with gr.Column():
output_image = gr.Image(label="Processed Image")
# Set up processing event
process_btn.click(
fn=process_image,
inputs=[
input_image,
downscale_mode,
target_size,
patch_size,
thickness,
color_matching,
upscale
],
outputs=output_image
) |