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 = True #False
disable_verbosity()
if SAVE_MEMORY:
enable_sliced_attention()
cfg = OmegaConf.load("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 = """
## GlyphControl: Glyph Conditional Control for Visual Text Generation (NeurIPS 2023)
Github link: [Link](https://github.com/AIGText/GlyphControl-release).
Report: [link](https://arxiv.org/pdf/2305.18259.pdf).\n
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
(By using the "Parameter Summary" part, you can import or export the parameter settings of generated images in an easier way.)
"""
SPACE_ID = os.getenv('SPACE_ID')
if SPACE_ID is not None:
# description += f'\nFor 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" />
'
description += f'\nFor faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. 
'
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():
# export_button = gr.Button(value="Export Parameters")
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, #"./examples",
# [[, "LAION-Glyph-10M-Epoch-6"]],
# ["./assets/img2.jpg", "r50-hdetr_sam-vit-b"],
# ["./assets/img3.jpg", "r50-hdetr_sam-vit-b"],
# ["./assets/img4.jpg", "r50-hdetr_sam-vit-b"]],
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=output_img,
# fn=inference
)
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()