apporg.py

import numpy as np
import gradio as gr
import ast
import requests

import logging
from rembg import new_session
from cutter import remove, make_label
from utils import *

API_URL_INITIAL = "https://ysharma-playground-ai-exploration.hf.space/run/initial_dataframe"
API_URL_NEXT10 = "https://ysharma-playground-ai-exploration.hf.space/run/next_10_rows"

from theme_dropdown import create_theme_dropdown  # noqa: F401

dropdown, js = create_theme_dropdown()

models = [
    {"name": "❤ STABLE DIFFUSION MODELS ==========", "url": "stabilityai/stable-diffusion-2-1"},
     {"name": "SD ComVis 1.2","url": "CompVis/stable-diffusion-v1-2"},
    {"name": "SD Comvis 1.4","url": "CompVis/stable-diffusion-v1-4"},
    {"name": "SD runawayml 1.5","url": "runwayml/stable-diffusion-v1-5"},
    {"name": "SD stable-diffusion xl base 1.0","url": "timothymhowe/stable-diffusion-xl-base-1.0"},
     {"name": "SD NSFW","url": "digiplay/CamelliaMix_NSFW_diffusers_v1.1"},
    
     {"name": "SD Dreamshaper-Anime","url": "Lykon/DreamShaper"},
     {"name": "Dreamlike Anime","url": "dreamlike-art/dreamlike-photoreal-2.0"},
    {"name": "❤ REALISTIC PHOTO MODELS ==========", "url": "dreamlike-art/dreamlike-photoreal-2.0"},
    {"name": "AmiIReal", "url": "stablediffusionapi/amireal"},
    {"name": "Analog Diffusion", "url": "wavymulder/Analog-Diffusion"},
    {"name": "Circulus 2.8", "url": "circulus/sd-photoreal-v2.8"},
    {"name": "UltraSkin", "url": "VegaKH/Ultraskin"},
    {"name": "Wavyfusion", "url": "wavymulder/wavyfusion"},
    {"name": "❤ SEMI-REALISTIC MODELS ==========", "url": "stablediffusionapi/all-526"},    
    {"name": "All 526", "url": "stablediffusionapi/all-526"},
    {"name": "All 526 animated", "url": "stablediffusionapi/all-526-animated"},
    {"name": "Circulus Semi Real 2", "url": "circulus/sd-photoreal-semi-v2"},
    {"name": "Semi Real Mix", "url": "robotjung/SemiRealMix"},
    {"name": "SpyBG", "url": "stablediffusionapi/spybg"},
    {"name": "Stable Diffusion 2", "url": "stabilityai/stable-diffusion-2-1"},
    {"name": "stability AI", "url": "stabilityai/stable-diffusion-2-1-base"},
    {"name": "Compressed-S-D", "url": "nota-ai/bk-sdm-small"},
    {"name": "Future Diffusion", "url": "nitrosocke/Future-Diffusion"},
    {"name": "JWST Deep Space Diffusion", "url": "dallinmackay/JWST-Deep-Space-diffusion"},
    {"name": "Robo Diffusion 3 Base", "url": "nousr/robo-diffusion-2-base"},
    {"name": "Robo Diffusion", "url": "nousr/robo-diffusion"},
    {"name": "Tron Legacy Diffusion", "url": "dallinmackay/Tron-Legacy-diffusion"},
    {"name": "❤ 3D ART MODELS ==========", "url": "DucHaiten/DucHaitenAIart"},
    {"name": "DucHaiten Art", "url": "DucHaiten/DucHaitenAIart"},
    {"name": "DucHaiten ClassicAnime", "url": "DucHaiten/DH_ClassicAnime"},
    {"name": "DucHaiten DreamWorld", "url": "DucHaiten/DucHaitenDreamWorld"},
    {"name": "DucHaiten Journey", "url": "DucHaiten/DucHaitenJourney"},
    {"name": "DucHaiten StyleLikeMe", "url": "DucHaiten/DucHaiten-StyleLikeMe"},
    {"name": "DucHaiten SuperCute", "url": "DucHaiten/DucHaitenSuperCute"},
    {"name": "Redshift Diffusion 768", "url": "nitrosocke/redshift-diffusion-768"},
    {"name": "Redshift Diffusion", "url": "nitrosocke/redshift-diffusion"},
]   


####  REM-BG

remove_bg_models = {
    "TracerUniversalB7": "TracerUniversalB7",
    "U2NET": "u2net",
    "U2NET Human Seg": "u2net_human_seg",
    "U2NET Cloth Seg": "u2net_cloth_seg"
}

model_choices = keys(remove_bg_models)


def predict(image, session, smoot, matting, bg_color):

    session = new_session(remove_bg_models[session])

    try:
        return remove(session, image, smoot, matting, bg_color)
    except ValueError as err:
        logging.error(err)
        return make_label(str(err)), None


def change_show_mask(chk_state):
    return gr.Image.update(visible=chk_state)


def change_include_matting(chk_state):
    return gr.Box.update(visible=chk_state), (0, 0, 0), 0, 0, 0


def change_foreground_threshold(fg_value, value):
    fg, bg, erode = value
    return fg_value, bg, erode


def change_background_threshold(bg_value, value):
    fg, bg, erode = value
    return fg, bg_value, erode


def change_erode_size(erode_value, value):
    fg, bg, erode = value
    return fg, bg, erode_value


def set_dominant_color(chk_state):
    return chk_state, gr.ColorPicker.update(value=False, visible=not chk_state)


def change_picker_color(picker, dominant):
    if not dominant:
        return picker
    return dominant


def change_background_mode(chk_state):
    return gr.ColorPicker.update(value=False, visible=chk_state), \
        gr.Checkbox.update(value=False, visible=chk_state)



###########

text_gen = gr.Interface.load("spaces/daspartho/prompt-extend")

current_model = models[0]

models2 = []
for model in models:
    model_url = f"models/{model['url']}"
    loaded_model = gr.Interface.load(model_url, live=True, preprocess=True)
    models2.append(loaded_model)

def text_it(inputs, text_gen=text_gen):
    return text_gen(inputs)

def flip_text(x):
    return x[::-1]

def send_it(inputs, model_choice):
    proc = models2[model_choice]
    return proc(inputs)


def flip_image(x):
    return np.fliplr(x)


def set_model(current_model_index):
    global current_model
    current_model = models[current_model_index]
    return gr.update(value=f"{current_model['name']}")

#define inference function
#First: Get initial images for the grid display 
def get_initial_images():
  response = requests.post(API_URL_INITIAL, json={
            "data": []
            }).json()
  #data = response["data"][0]['data'][0][0][:-1]
  response_dict = response['data'][0]
  return response_dict  #, [resp[0][:-1] for resp in response["data"][0]["data"]]

#Second: Process response dictionary to get imges as hyperlinked image tags
def process_response(response_dict):
  return [resp[0][:-1] for resp in response_dict["data"]]

response_dict = get_initial_images()
initial = process_response(response_dict)
initial_imgs  = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);">\n' + "\n".join(initial[:-1])

#Third: Load more images for the grid
def get_next10_images(response_dict, row_count):
    row_count = int(row_count)
    #print("(1)",type(response_dict))
    #Convert the string to a dictionary
    if isinstance(response_dict, dict) == False :
        response_dict = ast.literal_eval(response_dict)
    response = requests.post(API_URL_NEXT10, json={
              "data": [response_dict, row_count ] #len(initial)-1
               }).json()
    row_count+=10
    response_dict = response['data'][0]
    #print("(2)",type(response))
    #print("(3)",type(response['data'][0]))
    next_set  = [resp[0][:-1] for resp in response_dict["data"]]
    next_set_images = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); ">\n' + "\n".join(next_set[:-1])
    return response_dict, row_count, next_set_images  #response['data'][0]


with gr.Blocks(css ='main.css') as pan:
    gr.Markdown("MENU")
                    
    with gr.Tab("TEXT TO IMAGE"):
        
    ##model = ("stabilityai/stable-diffusion-2-1")
         model_name1 = gr.Dropdown(
                label="Choose Model",
                choices=[m["name"] for m in models],
                type="index",
                value=current_model["name"],
                interactive=True,
         )
         input_text = gr.Textbox(label="Prompt idea",)

        ##  run = gr.Button("Generate Images")
         with gr.Row():
             see_prompts = gr.Button("Generate Prompts")
             run = gr.Button("Generate Images", variant="primary")
        
         with gr.Row():
             magic1 = gr.Textbox(label="Generated Prompt", lines=2)
             output1 = gr.Image(label="")
          
             
         with gr.Row():    
             magic2 = gr.Textbox(label="Generated Prompt", lines=2)
             output2 = gr.Image(label="")

            
         run.click(send_it, inputs=[magic1, model_name1], outputs=[output1])
         run.click(send_it, inputs=[magic2, model_name1], outputs=[output2])
         see_prompts.click(text_it, inputs=[input_text], outputs=[magic1])
         see_prompts.click(text_it, inputs=[input_text], outputs=[magic2])
        
    model_name1.change(set_model, inputs=model_name1, outputs=[output1, output2,])
        
    with gr.Tab("AI Library"):
         #Using Gradio Demos as API - This is Hot!
#get_next10_images(response_dict=response_dict, row_count=9)
#position: fixed; top: 0; left: 0; width: 100%; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);

#Defining the Blocks layout
   # with gr.Blocks(css = """#img_search img {width: 100%; height: 100%; object-fit: cover;}""") as demo:
         gr.HTML(value="top of page", elem_id="top",visible=False)
         gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
            <div
            style="
            display: inline-flex;
            align-items: center;
            gap: 0.8rem;
            font-size: 1.75rem;
            "
            >
            <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
            Using Gradio API - 2 </h1><br></div>
            <div><h4 style="font-weight: 500; margin-bottom: 7px; margin-top: 5px;">
            Stream < href="https://huggingface.co/collections/Dagfinn1962/images-64fc02ca304b8cb412ccda28" target="_blank">Collection Images</a> ina beautiful grid</h4><br>
            </div>""")
    with gr.Tab("Gallery"):
    #with gr.Tab(): #(elem_id = "col-container"):
          #gr.Column(): #(elem_id = "col-container"):
             b1 = gr.Button("Load More Images").style(full_width=False)
             df = gr.Textbox(visible=False,elem_id='dataframe', value=response_dict)
             row_count = gr.Number(visible=False, value=19 )
             img_search = gr.HTML(label = 'Images from PlaygroundAI dataset', elem_id="img_search", 
                                 value=initial_imgs ) #initial[:-1] )
      

    b1.click(get_next10_images, [df, row_count], [df, row_count, img_search], api_name = "load_playgroundai_images" ) 
            
##########################  REM-BG
    with gr.Tab("Remove Background"):
        
        color_state = gr.State(value=False)
        matting_state = gr.State(value=(0, 0, 0))
        gr.HTML("<center><h1>Remove Background Tool</h1></center>")
        
        with gr.Row(equal_height=False):
            with gr.Column():
                input_img = gr.Image(type="pil", label="Input image")
                drp_models = gr.Dropdown(choices=model_choices, label="Model Segment", value="TracerUniversalB7")

            with gr.Row():
                chk_include_matting = gr.Checkbox(label="Matting", value=False)
                chk_smoot_mask = gr.Checkbox(label="Smoot Mask", value=False)
                chk_show_mask = gr.Checkbox(label="Show Mask", value=False)
            with gr.Box(visible=False) as slider_matting:
                slr_fg_threshold = gr.Slider(0, 300, value=270, step=1, label="Alpha matting foreground threshold")
                slr_bg_threshold = gr.Slider(0, 50, value=20, step=1, label="Alpha matting background threshold")
                slr_erode_size = gr.Slider(0, 20, value=11, step=1, label="Alpha matting erode size")
            with gr.Box():
                with gr.Row():
                    chk_change_color = gr.Checkbox(label="Change background color", value=False)
                    pkr_color = gr.ColorPicker(label="Pick a new color", visible=False)
                    chk_dominant = gr.Checkbox(label="Use dominant color", value=False, visible=False)

                #######################
                    ############################
                    #############################
                run_btn = gr.Button(value="Remove background", variant="primary")        

            with gr.Column():
                output_img = gr.Image(type="pil", label="Image Result")
                mask_img = gr.Image(type="pil", label="Image Mask", visible=False)
                gr.ClearButton(components=[input_img, output_img, mask_img])

        chk_include_matting.change(change_include_matting, inputs=[chk_include_matting],
                               outputs=[slider_matting, matting_state,
                                        slr_fg_threshold, slr_bg_threshold, slr_erode_size])
        
        slr_bg_threshold.change(change_background_threshold, inputs=[slr_bg_threshold, matting_state],
                            outputs=[matting_state])

        slr_fg_threshold.change(change_foreground_threshold, inputs=[slr_fg_threshold, matting_state],
                            outputs=[matting_state])

        slr_erode_size.change(change_erode_size, inputs=[slr_erode_size, matting_state],
                          outputs=[matting_state])

        chk_show_mask.change(change_show_mask, inputs=[chk_show_mask], outputs=[mask_img])

        chk_change_color.change(change_background_mode, inputs=[chk_change_color],
                            outputs=[pkr_color, chk_dominant])

        pkr_color.change(change_picker_color, inputs=[pkr_color, chk_dominant], outputs=[color_state])

        chk_dominant.change(set_dominant_color, inputs=[chk_dominant], outputs=[color_state, pkr_color])

        run_btn.click(predict, inputs=[input_img, drp_models, chk_smoot_mask, matting_state, color_state],
                  outputs=[output_img, mask_img])


                
#            text_input = gr.Textbox()                      ##   Diffuser
#            image_output = gr.Image()
#        image_button = gr.Button("Flip")



   # text_button.click(flip_text, inputs=text_input, outputs=text_output)
   # image_button.click(flip_image, inputs=image_input, outputs=image_output)
pan.queue(concurrency_count=200)
pan.launch(inline=True, show_api=True,  max_threads=400 )