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import spaces
import gradio as gr
import subprocess
from PIL import Image,ImageEnhance,ImageFilter,ImageDraw
import json
import numpy as np
from skimage.exposure import match_histograms
from gradio_utils import save_image
from color_utils import simple_white_balance,apply_tone_curve,curve_midtones,create_left_half_mask,create_top_half_mask,create_compare_image ,mirror
def color_match(base_image,cropped_image,color_match_format="RGB"):
reference = np.array(base_image.convert(color_match_format))
target =np.array(cropped_image.convert(color_match_format))
matched = match_histograms(target, reference,channel_axis=-1)
return Image.fromarray(matched,mode=color_match_format)
def apply_layer(image_dict):
base_rgba = image_dict["background"].convert("RGBA")
if len(image_dict['layers']) > 0:
layer = image_dict['layers'][0]
mask = layer.convert("L") # グレイスケールに変換
mask=mask.point(lambda x: 255 if x > 0 else x)
layer_rgba = layer.convert("RGBA")
base_rgba.paste(layer_rgba, (0, 0),mask)
return base_rgba
def create_enhanced_image(reference_image,brightness=1.0,color=1.0,contrast=1.0,use_whitebalance=False,top_whitebalance=1):
if use_whitebalance:
reference_image = simple_white_balance(reference_image,top_whitebalance)
if brightness!=1.0:
brightness_enhancer = ImageEnhance.Brightness(reference_image)
reference_image = brightness_enhancer.enhance(brightness)
if color!=1.0:
color_enhancer = ImageEnhance.Color(reference_image)
reference_image = color_enhancer.enhance(color)
if contrast!=1.0:
contrast_enhancer = ImageEnhance.Contrast(reference_image)
reference_image = contrast_enhancer.enhance(contrast)
return reference_image
def process_images(reference_image_dict,target_image_dict,mirror_target=False,middle_tone_value=0.75,color_match_format="RGB",progress=gr.Progress(track_tqdm=True)):
progress(0, desc="Start color matching")
if reference_image_dict == None:
raise gr.Error("Need reference_image")
if target_image_dict == None:
raise gr.Error("Need target_image")
if not isinstance(reference_image_dict, dict):
raise gr.Error("Need DictData reference_image_dict")
if not isinstance(target_image_dict, dict):
raise gr.Error("Need DictData target_image_dict")
reference_image = apply_layer(reference_image_dict)
target_image = apply_layer(target_image_dict)
if mirror_target:
target_image = mirror(target_image)
images = []
left_mask = create_left_half_mask(reference_image)
top_mask = create_top_half_mask(reference_image)
color_matched = color_match(reference_image,target_image,color_match_format)
color_matched_resized = color_matched.resize(reference_image.size)
matched_path = save_image(color_matched.convert("RGB"))
images.append((matched_path,"color matched"))
progress(0.2)
reference_mix_left,reference_mix_right = create_compare_image(reference_image,color_matched_resized,left_mask)
images.append((save_image(reference_mix_left.convert("RGB"),extension="webp"),"mixed_left"))
images.append((save_image(reference_mix_right.convert("RGB"),extension="webp"),"mixed_right"))
progress(0.4)
reference_mix_top,reference_mix_bottom = create_compare_image(reference_image,color_matched_resized,top_mask)
images.append((save_image(reference_mix_top.convert("RGB"),extension="webp"),"mixed_top"))
images.append((save_image(reference_mix_bottom.convert("RGB"),extension="webp"),"mixed_bottom"))
progress(0.6)
color_matched_tone = apply_tone_curve(color_matched.convert("RGB"),curve_midtones,middle_tone_value)
color_matched_tone_resized = color_matched_tone.resize(reference_image.size)
images.append((save_image(color_matched_tone.convert("RGB")),"tone-curved"))
reference_mix_left,reference_mix_right = create_compare_image(reference_image,color_matched_tone_resized,left_mask)
images.append((save_image(reference_mix_left.convert("RGB"),extension="webp"),"mixed_left"))
images.append((save_image(reference_mix_right.convert("RGB"),extension="webp"),"mixed_right"))
progress(0.8)
reference_mix_top,reference_mix_bottom = create_compare_image(reference_image,color_matched_tone_resized,top_mask)
images.append((save_image(reference_mix_top.convert("RGB"),extension="webp"),"mixed_top"))
images.append((save_image(reference_mix_bottom.convert("RGB"),extension="webp"),"mixed_bottom"))
progress(1.0)
return images
def read_file(file_path: str) -> str:
"""read the text of target file
"""
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
return content
css="""
#col-left {
margin: 0 auto;
max-width: 640px;
}
#col-right {
margin: 0 auto;
max-width: 640px;
}
.grid-container {
display: flex;
align-items: center;
justify-content: center;
gap:10px
}
.image {
width: 128px;
height: 128px;
object-fit: cover;
}
.text {
font-size: 16px;
}
"""
def color_changed(color):
#mode must be RGBA
editor = gr.ImageEditor(brush=gr.Brush(colors=[color],color_mode="fixed"))
return editor,editor
#css=css,
def update_button_label(image):
if image == None:
print("none replace")
return gr.Button(visible=True),gr.Button(visible=False),gr.Row(visible=True),gr.Row(visible=True)
else:
return gr.Button(visible=False),gr.Button(visible=True),gr.Row(visible=False),gr.Row(visible=False)
def update_visible(fill_color_mode,image):
if image != None:
return gr.Row(visible=False),gr.Row(visible=False)
if fill_color_mode:
return gr.Row(visible=False),gr.Row(visible=True)
else:
return gr.Row(visible=True),gr.Row(visible=False)
with gr.Blocks(css=css, elem_id="demo-container") as demo:
with gr.Column():
gr.HTML(read_file("demo_header.html"))
gr.HTML(read_file("demo_tools.html"))
with gr.Row():
with gr.Column():
reference_image = gr.ImageEditor(height=1050,sources=['upload','clipboard'],layers = False,transforms=[],image_mode='RGBA',elem_id="image_upload", type="pil", label="Reference Image",brush=gr.Brush(colors=["#001"], color_mode="fixed"))
with gr.Row(elem_id="prompt-container", equal_height=False):
btn1 = gr.Button("Color Match", elem_id="run_button",variant="primary")
mirror_target = gr.Checkbox(label="Mirror target",value=False)
pick=gr.ColorPicker(label="color",value="#001",info="ImageEditor color is broken,pick color from here.reselect paint-tool and draw.but not so effective")
target_image = gr.ImageEditor(height=1050,sources=['upload','clipboard'],layers = False,transforms=[],image_mode='RGBA',elem_id="image_upload", type="pil", label="Target Image",brush=gr.Brush(colors=["#001"], color_mode="fixed"))
pick.change(fn=color_changed,inputs=[pick],outputs=[reference_image,target_image])
with gr.Accordion(label="Advanced Settings", open=False):
gr.HTML("<h4>Post-Process Target Image</h4>")
with gr.Row(equal_height=True):
middle_tone_value = gr.Slider(
label="middle tone",
minimum=0,
maximum=2.0,
step=0.01,
value=0.75)
color_match_format = gr.Dropdown(label="Format",choices=["RGB","CMYK","YCbCr","HSV","LAB"],value="RGB",info="RGB and CMYK seems same,others are broken")
with gr.Column():
image_out = gr.Gallery(height=800,label="Output", elem_id="output-img",format="webp", preview=True)
gr.on(
[btn1.click],
fn=process_images, inputs=[reference_image,target_image,mirror_target,middle_tone_value,color_match_format], outputs =[image_out], api_name='infer'
)
gr.Examples(
examples =[
["examples/face01.webp","examples/face02.webp"],
["examples/face01.webp","examples/face03.webp"],
["examples/face01.webp","examples/face04.webp"],
["examples/face02.webp","examples/face03.webp"],
["examples/face02.webp","examples/face04.webp"],
["examples/face03.webp","examples/face04.webp"],
],
inputs=[reference_image,target_image]
)
gr.HTML(read_file("demo_footer.html"))
if __name__ == "__main__":
demo.launch()
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