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# Forge Canvas
# AGPL V3
# by lllyasviel
# Commercial Use is not allowed. (Contact us for commercial use.)
import gradio.component_meta
create_or_modify_pyi_org = gradio.component_meta.create_or_modify_pyi
def create_or_modify_pyi_org_patched(component_class, class_name, events):
try:
if component_class.__name__ == 'LogicalImage':
return
return create_or_modify_pyi_org(component_class, class_name, events)
except:
return
gradio.component_meta.create_or_modify_pyi = create_or_modify_pyi_org_patched
import os
import uuid
import base64
import gradio as gr
import numpy as np
from PIL import Image
from io import BytesIO
from gradio.context import Context
from functools import wraps
canvas_js_root_path = os.path.dirname(__file__)
def web_js(file_name):
full_path = os.path.join(canvas_js_root_path, file_name)
return f'<script src="file={full_path}?{os.path.getmtime(full_path)}"></script>\n'
def web_css(file_name):
full_path = os.path.join(canvas_js_root_path, file_name)
return f'<link rel="stylesheet" href="file={full_path}?{os.path.getmtime(full_path)}">\n'
DEBUG_MODE = False
canvas_html = open(os.path.join(canvas_js_root_path, 'canvas.html'), encoding='utf-8').read()
canvas_head = ''
canvas_head += web_css('canvas.css')
canvas_head += web_js('canvas.min.js')
def image_to_base64(image_array, numpy=True):
image = Image.fromarray(image_array) if numpy else image_array
image = image.convert("RGBA")
buffered = BytesIO()
image.save(buffered, format="PNG")
image_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
return f"data:image/png;base64,{image_base64}"
def base64_to_image(base64_str, numpy=True):
if base64_str.startswith("data:image/png;base64,"):
base64_str = base64_str.replace("data:image/png;base64,", "")
image_data = base64.b64decode(base64_str)
image = Image.open(BytesIO(image_data))
image = image.convert("RGBA")
image_array = np.array(image) if numpy else image
return image_array
class LogicalImage(gr.Textbox):
@wraps(gr.Textbox.__init__)
def __init__(self, *args, numpy=True, **kwargs):
self.numpy = numpy
self.infotext = dict()
if 'value' in kwargs:
initial_value = kwargs['value']
if initial_value is not None:
kwargs['value'] = self.image_to_base64(initial_value)
else:
del kwargs['value']
super().__init__(*args, **kwargs)
def preprocess(self, payload):
if not isinstance(payload, str):
return None
if not payload.startswith("data:image/png;base64,"):
return None
image = base64_to_image(payload, numpy=self.numpy)
if hasattr(image, 'info'):
image.info = self.infotext
return image
def postprocess(self, value):
if value is None:
return None
if hasattr(value, 'info'):
self.infotext = value.info
return image_to_base64(value, numpy=self.numpy)
def get_block_name(self):
return "textbox"
class ForgeCanvas:
def __init__(
self,
no_upload=False,
no_scribbles=False,
contrast_scribbles=False,
height=512,
scribble_color='#000000',
scribble_color_fixed=False,
scribble_width=4,
scribble_width_fixed=False,
scribble_alpha=100,
scribble_alpha_fixed=False,
scribble_softness=0,
scribble_softness_fixed=False,
visible=True,
numpy=False,
initial_image=None,
elem_id=None,
elem_classes=None
):
self.uuid = 'uuid_' + uuid.uuid4().hex
self.block = gr.HTML(canvas_html.replace('forge_mixin', self.uuid), visible=visible, elem_id=elem_id, elem_classes=elem_classes)
self.foreground = LogicalImage(visible=DEBUG_MODE, label='foreground', numpy=numpy, elem_id=self.uuid, elem_classes=['logical_image_foreground'])
self.background = LogicalImage(visible=DEBUG_MODE, label='background', numpy=numpy, value=initial_image, elem_id=self.uuid, elem_classes=['logical_image_background'])
Context.root_block.load(None, js=f'async ()=>{{new ForgeCanvas("{self.uuid}", {no_upload}, {no_scribbles}, {contrast_scribbles}, {height}, '
f"'{scribble_color}', {scribble_color_fixed}, {scribble_width}, {scribble_width_fixed}, "
f'{scribble_alpha}, {scribble_alpha_fixed}, {scribble_softness}, {scribble_softness_fixed});}}')
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