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app.py
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app.py
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# ------------------------------------------
# GlyphControl: Glyph Conditional Control for Visual Text Generation
# Paper Link: https://arxiv.org/pdf/2305.18259
# Code Link: https://github.com/AIGText/GlyphControl-release
# This script is used to build the demo.
# ------------------------------------------
import math
from omegaconf import OmegaConf
from scripts.rendertext_tool import Render_Text, load_model_from_config, load_model_ckpt
import gradio as gr
import os
import torch
import time
from PIL import Image
from cldm.hack import disable_verbosity, enable_sliced_attention
# from pytorch_lightning import seed_everything
# from example_list import examples
def process_multi_wrapper(rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3,
shared_prompt,
width_0, width_1, width_2, width_3,
ratio_0, ratio_1, ratio_2, ratio_3,
top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3,
top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3,
yaw_0, yaw_1, yaw_2, yaw_3,
num_rows_0, num_rows_1, num_rows_2, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt, allow_run_generation = True):
if not allow_run_generation:
return "Please get the glyph image first by clicking the 'Render Glyph Image' button", None, allow_run_generation
rendered_txt_values = [rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3]
width_values = [width_0, width_1, width_2, width_3]
ratio_values = [ratio_0, ratio_1, ratio_2, ratio_3]
top_left_x_values = [top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3]
top_left_y_values = [top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3]
yaw_values = [yaw_0, yaw_1, yaw_2, yaw_3]
num_rows_values = [num_rows_0, num_rows_1, num_rows_2, num_rows_3]
allow_run_generation = False
return "The image generation process finished!", render_tool.process_multi(rendered_txt_values, shared_prompt,
width_values, ratio_values,
top_left_x_values, top_left_y_values,
yaw_values, num_rows_values,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt
), allow_run_generation
def process_multi_wrapper_only_show_rendered(rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3,
shared_prompt,
width_0, width_1, width_2, width_3,
ratio_0, ratio_1, ratio_2, ratio_3,
top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3,
top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3,
yaw_0, yaw_1, yaw_2, yaw_3,
num_rows_0, num_rows_1, num_rows_2, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt):
rendered_txt_values = [rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3]
width_values = [width_0, width_1, width_2, width_3]
ratio_values = [ratio_0, ratio_1, ratio_2, ratio_3]
top_left_x_values = [top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3]
top_left_y_values = [top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3]
yaw_values = [yaw_0, yaw_1, yaw_2, yaw_3]
num_rows_values = [num_rows_0, num_rows_1, num_rows_2, num_rows_3]
allow_run_generation = True
glyph_image = render_tool.process_multi(rendered_txt_values, shared_prompt,
width_values, ratio_values,
top_left_x_values, top_left_y_values,
yaw_values, num_rows_values,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt,
only_show_rendered_image=True)
if glyph_image[0] is None:
return "Warning: no glyph image would be rendered because the glyph insructions are not provided!", None, allow_run_generation
else:
return "The glyph image is successfully rendered!", glyph_image, allow_run_generation
def load_ckpt(model_ckpt = "LAION-Glyph-10M-Epoch-5"):
global render_tool, model
if torch.cuda.is_available():
for i in range(5):
torch.cuda.empty_cache()
time.sleep(2)
print("empty the cuda cache")
if model_ckpt == "LAION-Glyph-10M-Epoch-6":
model = load_model_ckpt(model, "checkpoints/laion10M_epoch_6_model_ema_only.ckpt")
elif model_ckpt == "TextCaps-5K-Epoch-10":
model = load_model_ckpt(model, "checkpoints/textcaps5K_epoch_10_model_ema_only.ckpt")
elif model_ckpt == "TextCaps-5K-Epoch-20":
model = load_model_ckpt(model, "checkpoints/textcaps5K_epoch_20_model_ema_only.ckpt")
elif model_ckpt == "TextCaps-5K-Epoch-40":
model = load_model_ckpt(model, "checkpoints/textcaps5K_epoch_40_model_ema_only.ckpt")
render_tool = Render_Text(model, save_memory = SAVE_MEMORY)
output_str = f"already change the model checkpoint to {model_ckpt}"
print(output_str)
if torch.cuda.is_available():
for i in range(5):
torch.cuda.empty_cache()
time.sleep(2)
print("empty the cuda cache")
allow_run_generation = False
return output_str, None, allow_run_generation
def export_parameters(*args):
return str(args)
def import_parameters(parameters):
return eval(parameters)
SAVE_MEMORY = False
disable_verbosity()
if SAVE_MEMORY:
enable_sliced_attention()
cfg = OmegaConf.load("configs/config.yaml")
model = load_model_from_config(cfg, "checkpoints/laion10M_epoch_6_model_ema_only.ckpt", verbose=True)
render_tool = Render_Text(model, save_memory = SAVE_MEMORY)
description = """
## Control Stable Diffusion with Glyph Images
Github link: [Link](https://github.com/AIGText/GlyphControl-release).
Report: [link](https://arxiv.org/pdf/2305.18259.pdf).\n
(By using the "Parameter Summary" part, you can import or export the parameter settings of generated images in an easier way.)
"""
# You could try the listed examples at the bottom by clicking on them and modify the parameters for your own creation. We will update the examples progressively.\n
SPACE_ID = os.getenv('SPACE_ID')
if SPACE_ID is not None:
# description += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. < a href=" ">< img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></ a></p >'
description += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
block = gr.Blocks().queue()
with block:
with gr.Row():
gr.Markdown(description)
only_show_rendered_image = gr.Number(value=1, visible=False)
default_width = [0.3, 0.3, 0.3, 0.3]
default_top_left_x = [0.35, 0.15, 0.15, 0.5]
default_top_left_y = [0.4, 0.15, 0.65, 0.65]
with gr.Column():
with gr.Row():
for i in range(4):
with gr.Column():
exec(f"""rendered_txt_{i} = gr.Textbox(label=f"Render Text {i+1}")""")
with gr.Accordion(f"Advanced options {i+1}", open=False):
exec(f"""width_{i} = gr.Slider(label="Bbox Width", minimum=0., maximum=1, value={default_width[i]}, step=0.01) """)
exec(f"""ratio_{i} = gr.Slider(label="Bbox_width_height_ratio", minimum=0., maximum=5, value=0., step=0.02, visible=False) """)
# exec(f"""top_left_x_{i} = gr.Slider(label="Bbox Top Left x", minimum=0., maximum=1, value={0.35 - 0.25 * math.cos(math.pi * i)}, step=0.01) """)
# exec(f"""top_left_y_{i} = gr.Slider(label="Bbox Top Left y", minimum=0., maximum=1, value={0.1 if i < 2 else 0.6}, step=0.01) """)
exec(f"""top_left_x_{i} = gr.Slider(label="Bbox Top Left x", minimum=0., maximum=1, value={default_top_left_x[i]}, step=0.01) """)
exec(f"""top_left_y_{i} = gr.Slider(label="Bbox Top Left y", minimum=0., maximum=1, value={default_top_left_y[i]}, step=0.01) """)
exec(f"""yaw_{i} = gr.Slider(label="Bbox Yaw", minimum=-20, maximum=20, value=0, step=5) """)
# exec(f"""num_rows_{i} = gr.Slider(label="num_rows", minimum=1, maximum=4, value=1, step=1, visible=False) """)
exec(f"""num_rows_{i} = gr.Slider(label="num_rows", minimum=1, maximum=4, value=1, step=1) """)
with gr.Row():
with gr.Column():
shared_prompt = gr.Textbox(label="Shared Prompt")
with gr.Row():
show_render_button = gr.Button(value="Render Glyph Image")
run_button = gr.Button(value="Run Generation")
allow_run_generation = gr.Checkbox(label='allow_run_generation',
value=False, visible=False)
with gr.Accordion("Model Options", open=False):
with gr.Row():
# model_ckpt = gr.inputs.Dropdown(["LAION-Glyph-10M", "Textcaps5K-10"], label="Checkpoint", default = "LAION-Glyph-10M")
# model_ckpt = gr.inputs.Dropdown(["LAION-Glyph-10M-Epoch-6", "LAION-Glyph-10M-Epoch-5", "LAION-Glyph-1M"], label="Checkpoint", default = "LAION-Glyph-10M-Epoch-6")
model_ckpt = gr.inputs.Dropdown(["LAION-Glyph-10M-Epoch-6", "TextCaps-5K-Epoch-10", "TextCaps-5K-Epoch-20", "TextCaps-5K-Epoch-40"], label="Checkpoint", default = "LAION-Glyph-10M-Epoch-6")
# load_button = gr.Button(value = "Load Checkpoint")
with gr.Accordion("Shared Advanced Options", open=False):
with gr.Row():
shared_num_samples = gr.Slider(label="Images", minimum=1, maximum=12, value=5, step=1)
shared_image_resolution = gr.Slider(label="Image Resolution", minimum=256, maximum=768, value=512, step=64, visible=False)
shared_strength = gr.Slider(label="Control Strength", minimum=0.0, maximum=2.0, value=1.0, step=0.01, visible=False)
shared_guess_mode = gr.Checkbox(label='Guess Mode', value=False, visible=False)
shared_seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)
with gr.Row():
shared_scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
shared_ddim_steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=20, step=1)
shared_eta = gr.Number(label="eta (DDIM)", value=0.0, visible=False)
with gr.Row():
shared_a_prompt = gr.Textbox(label="Added Prompt", value='4K, dslr, best quality, extremely detailed')
shared_n_prompt = gr.Textbox(label="Negative Prompt",
value='longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality')
with gr.Accordion("Parameter Summary", open=False):
with gr.Row():
parameters = gr.Text(label = "Parameters")
with gr.Row():
import_button = gr.Button(value="Import")
export_button = gr.Button(value="Export")
with gr.Accordion("Output", open=True):
with gr.Row():
message = gr.Text(interactive=False, label = "Message")
with gr.Row():
result_gallery = gr.Gallery(label='Images', show_label=False, elem_id="gallery").style(grid=2, height='auto')
# gr.Examples(
# examples= examples,
# inputs=[ model_ckpt, shared_prompt,
# rendered_txt_0, width_0, ratio_0, top_left_x_0, top_left_y_0, yaw_0, num_rows_0,
# rendered_txt_1, width_1, ratio_1, top_left_x_1, top_left_y_1, yaw_1, num_rows_1,
# rendered_txt_2, width_2, ratio_2, top_left_x_2, top_left_y_2, yaw_2, num_rows_2,
# rendered_txt_3, width_3, ratio_3, top_left_x_3, top_left_y_3, yaw_3, num_rows_3,
# shared_num_samples, shared_image_resolution,
# shared_ddim_steps, shared_guess_mode,
# shared_strength, shared_scale, shared_seed,
# shared_eta, shared_a_prompt, shared_n_prompt],
# )
export_button.click(fn=export_parameters,
inputs = [model_ckpt, shared_prompt,
rendered_txt_0, width_0, ratio_0, top_left_x_0, top_left_y_0, yaw_0, num_rows_0,
rendered_txt_1, width_1, ratio_1, top_left_x_1, top_left_y_1, yaw_1, num_rows_1,
rendered_txt_2, width_2, ratio_2, top_left_x_2, top_left_y_2, yaw_2, num_rows_2,
rendered_txt_3, width_3, ratio_3, top_left_x_3, top_left_y_3, yaw_3, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt],
outputs = [parameters] )
import_button.click(fn=import_parameters,
inputs = [parameters],
outputs = [model_ckpt, shared_prompt,
rendered_txt_0, width_0, ratio_0, top_left_x_0, top_left_y_0, yaw_0, num_rows_0,
rendered_txt_1, width_1, ratio_1, top_left_x_1, top_left_y_1, yaw_1, num_rows_1,
rendered_txt_2, width_2, ratio_2, top_left_x_2, top_left_y_2, yaw_2, num_rows_2,
rendered_txt_3, width_3, ratio_3, top_left_x_3, top_left_y_3, yaw_3, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt]
)
run_button.click(fn=process_multi_wrapper,
inputs=[rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3,
shared_prompt,
width_0, width_1, width_2, width_3,
ratio_0, ratio_1, ratio_2, ratio_3,
top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3,
top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3,
yaw_0, yaw_1, yaw_2, yaw_3,
num_rows_0, num_rows_1, num_rows_2, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt, allow_run_generation],
outputs=[message, result_gallery, allow_run_generation])
show_render_button.click(fn=process_multi_wrapper_only_show_rendered,
inputs=[rendered_txt_0, rendered_txt_1, rendered_txt_2, rendered_txt_3,
shared_prompt,
width_0, width_1, width_2, width_3,
ratio_0, ratio_1, ratio_2, ratio_3,
top_left_x_0, top_left_x_1, top_left_x_2, top_left_x_3,
top_left_y_0, top_left_y_1, top_left_y_2, top_left_y_3,
yaw_0, yaw_1, yaw_2, yaw_3,
num_rows_0, num_rows_1, num_rows_2, num_rows_3,
shared_num_samples, shared_image_resolution,
shared_ddim_steps, shared_guess_mode,
shared_strength, shared_scale, shared_seed,
shared_eta, shared_a_prompt, shared_n_prompt],
outputs=[message, result_gallery, allow_run_generation])
model_ckpt.change(load_ckpt,
inputs = [model_ckpt],
outputs = [message, result_gallery, allow_run_generation]
)
block.launch()