from cldm.ddim_hacked import DDIMSampler
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
ALLOW_RUN_GENERATION = False
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):  
    global ALLOW_RUN_GENERATION
    if not ALLOW_RUN_GENERATION:
        return "Please get the glyph image first by clicking the 'Only Rendered' button", None

    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 
                                    ) 
     
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):  
    global 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 = True
  
    return "The glyph image is generated!", 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)  

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-1M":
    #     model = load_model_ckpt(model, "laion1M_model_wo_ema.ckpt")
    if model_ckpt == "LAION-Glyph-10M-Epoch-5":
        model = load_model_ckpt(model, "laion10M_epoch_5_model_wo_ema.ckpt")
    elif model_ckpt == "LAION-Glyph-10M-Epoch-6":
        model = load_model_ckpt(model, "laion10M_epoch_6_model_wo_ema.ckpt")
    elif model_ckpt == "TextCaps-5K-Epoch-10":
        model = load_model_ckpt(model, "textcaps5K_epoch_10_model_wo_ema.ckpt")
    elif model_ckpt == "TextCaps-5K-Epoch-20":
        model = load_model_ckpt(model, "textcaps5K_epoch_20_model_wo_ema.ckpt")
    elif model_ckpt == "TextCaps-5K-Epoch-40":
        model = load_model_ckpt(model, "textcaps5K_epoch_40_model_wo_ema.ckpt")

    render_tool = Render_Text(model)
    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")
    return output_str, None


cfg = OmegaConf.load("config.yaml")
model = load_model_from_config(cfg, "laion10M_epoch_6_model_wo_ema.ckpt", verbose=True)
# model = load_model_from_config(cfg, "model_wo_ema.ckpt", verbose=True)
# model = load_model_from_config(cfg, "model_states.pt", verbose=True)
# model = load_model_from_config(cfg, "model.ckpt", verbose=True)
# ddim_sampler = DDIMSampler(model)
render_tool = Render_Text(model)


description = """
## Control Stable Diffusion with Glyph Images
"""

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")     
                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", "LAION-Glyph-10M-Epoch-5", "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=1, 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='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("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')  
    
    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],  
                outputs=[message, result_gallery])  
    
    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]) 
    
    model_ckpt.change(load_ckpt,                 
                inputs = [model_ckpt],
                outputs = [message, result_gallery]
    )

    block.launch()