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import gradio as gr
from PIL import Image, ImageEnhance
import numpy as np
import torch
import torchvision.transforms as transforms
from torchvision.models import resnet34
# Load a pre-trained ResNet model
model = resnet34(pretrained=True)
# Define the upscaling function
def upscale_image(image, upscale_factor=2, sharpness=1.0, contrast=1.0, brightness=1.0):
# Resize the image
width, height = image.size
new_size = (int(width * upscale_factor), int(height * upscale_factor))
upscaled_image = image.resize(new_size, Image.BICUBIC)
# Apply sharpness, contrast, and brightness adjustments
upscaled_image = ImageEnhance.Sharpness(upscaled_image).enhance(sharpness)
upscaled_image = ImageEnhance.Contrast(upscaled_image).enhance(contrast)
upscaled_image = ImageEnhance.Brightness(upscaled_image).enhance(brightness)
return upscaled_image
# Define the remastering function
def remaster_image(image, color_range=1.0, sharpness=1.0, hdr_intensity=1.0, tone_mapping=1.0, color_grading=1.0):
# Adjust color range
enhancer = ImageEnhance.Color(image)
image = enhancer.enhance(color_range)
# Adjust sharpness
enhancer = ImageEnhance.Sharpness(image)
image = enhancer.enhance(sharpness)
# For HDR simulation and tone mapping, we're using simple brightness adjustments
enhancer = ImageEnhance.Brightness(image)
image = enhancer.enhance(hdr_intensity)
# Simulate color grading by adjusting contrast
enhancer = ImageEnhance.Contrast(image)
image = enhancer.enhance(color_grading)
return image
# Process function for Gradio
def process_image(image, upscale=False, upscale_factor=2, sharpness=1.0, contrast=1.0, brightness=1.0,
remaster=False, color_range=1.0, hdr_intensity=1.0, tone_mapping=1.0, color_grading=1.0):
if upscale:
image = upscale_image(image, upscale_factor, sharpness, contrast, brightness)
if remaster:
image = remaster_image(image, color_range, sharpness, hdr_intensity, tone_mapping, color_grading)
return image
# Gradio UI
with gr.Blocks() as demo:
with gr.Row():
image_input = gr.Image(label="Upload Image", type="pil")
image_output = gr.Image(label="Output Image")
with gr.Row():
with gr.Group():
gr.Markdown("### Upscaling Options")
upscale_checkbox = gr.Checkbox(label="Apply Upscaling")
upscale_factor = gr.Slider(1, 8, value=2, label="Upscale Factor")
sharpness = gr.Slider(0.5, 2.0, value=1.0, label="Sharpness")
contrast = gr.Slider(0.5, 2.0, value=1.0, label="Contrast")
brightness = gr.Slider(0.5, 2.0, value=1.0, label="Brightness")
with gr.Group():
gr.Markdown("### Remastering Options")
remaster_checkbox = gr.Checkbox(label="Apply Remastering")
color_range = gr.Slider(0.5, 2.0, value=1.0, label="Dynamic Color Range")
hdr_intensity = gr.Slider(0.5, 2.0, value=1.0, label="HDR Intensity")
tone_mapping = gr.Slider(0.5, 2.0, value=1.0, label="Tone Mapping")
color_grading = gr.Slider(0.5, 2.0, value=1.0, label="Color Grading")
process_button = gr.Button("Process Image")
process_button.click(
process_image,
inputs=[image_input, upscale_checkbox, upscale_factor, sharpness, contrast, brightness,
remaster_checkbox, color_range, hdr_intensity, tone_mapping, color_grading],
outputs=image_output
)
demo.launch() |