from diffusers import DPMSolverMultistepScheduler
import gradio as gr
from PIL import Image
import cv2
import qrcode
import numpy as np
from transformers import pipeline
import PIL.Image
from diffusers.utils import load_image
from accelerate import Accelerator
from diffusers import StableDiffusionPipeline
import torch
from diffusers import StableDiffusionControlNetPipeline, ControlNetModel

accelerator = Accelerator(cpu=True)
models =[
    "runwayml/stable-diffusion-v1-5",
    "prompthero/openjourney-v4",
    "CompVis/stable-diffusion-v1-4",
    "stabilityai/stable-diffusion-2-1",
    "stablediffusionapi/disney-pixal-cartoon",
    "stablediffusionapi/edge-of-realism",
    "MirageML/fantasy-scene",
    "wavymulder/lomo-diffusion",
    "sd-dreambooth-library/fashion",
    "DucHaiten/DucHaitenDreamWorld",
    "VegaKH/Ultraskin",
    "kandinsky-community/kandinsky-2-1",
    "MirageML/lowpoly-cyberpunk",
    "thehive/everyjourney-sdxl-0.9-finetuned",
    "plasmo/woolitize-768sd1-5",
    "plasmo/food-crit",
    "johnslegers/epic-diffusion-v1.1",
    "Fictiverse/ElRisitas",
    "robotjung/SemiRealMix",
    "herpritts/FFXIV-Style",
    "prompthero/linkedin-diffusion",
    "RayHell/popupBook-diffusion",
    "MirageML/lowpoly-world",
    "deadman44/SD_Photoreal_Merged_Models",
    "Conflictx/CGI_Animation",
    "johnslegers/epic-diffusion",
    "tilake/China-Chic-illustration",
    "wavymulder/modelshoot",
    "prompthero/openjourney-lora",
    "Fictiverse/Stable_Diffusion_VoxelArt_Model",
    "darkstorm2150/Protogen_v2.2_Official_Release",
    "hassanblend/HassanBlend1.5.1.2",
    "hassanblend/hassanblend1.4",
    "nitrosocke/redshift-diffusion",
    "prompthero/openjourney-v2",
    "nitrosocke/Arcane-Diffusion",
    "Lykon/DreamShaper",
    "wavymulder/Analog-Diffusion",
    "nitrosocke/mo-di-diffusion",
    "dreamlike-art/dreamlike-diffusion-1.0",
    "dreamlike-art/dreamlike-photoreal-2.0",
    "digiplay/RealismEngine_v1",
    "digiplay/AIGEN_v1.4_diffusers",
    "stablediffusionapi/dreamshaper-v6",
    "JackAnon/GorynichMix",
    "p1atdev/liminal-space-diffusion",
    "nadanainone/gigaschizonegs",
    "darkVOYAGE/dvMJv4",
    "lckidwell/album-cover-style",
    "axolotron/ice-cream-animals",
    "perion/ai-avatar",
    "digiplay/GhostMix",
    "ThePioneer/MISA",
    "TheLastBen/froggy-style-v21-768",
    "FloydianSound/Nixeu_Diffusion_v1-5",
    "kakaobrain/karlo-v1-alpha-image-variations",
    "digiplay/PotoPhotoRealism_v1",
    "ConsistentFactor/Aurora-By_Consistent_Factor",
    "rim0/quadruped_mechas",
    "Akumetsu971/SD_Samurai_Anime_Model",
    "Bojaxxx/Fantastic-Mr-Fox-Diffusion",
    "sd-dreambooth-library/original-character-cyclps",
    "AIArtsChannel/steampunk-diffusion",
]

controlnet = accelerator.prepare(ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=torch.float32))
generator = torch.Generator(device="cpu").manual_seed(1)
def plex(qr_code_value, text, neg_text, modil, one, two, three):
    apol=[]
    modal=""+modil+""
    pipe = accelerator.prepare(StableDiffusionControlNetPipeline.from_pretrained(modal, controlnet=controlnet, torch_dtype=torch.float32, use_safetensors=False, safety_checker=None))
    pipe.scheduler = accelerator.prepare(DPMSolverMultistepScheduler.from_config(pipe.scheduler.config))
    pipe = pipe.to("cpu")
    negative_prompt = "monochrome, lowres, bad anatomy, worst quality, low quality"
    prompt = text
    qr_code = qrcode.make(qr_code_value).resize((512, 512))
    rmage = load_image(qr_code)
    original = rmage.convert("RGB")
    original.thumbnail((512, 512))
    cannyimage = load_image(original).resize((512,512))
    cannyimage = np.array(cannyimage)
    low_threshold = 100
    high_threshold = 200
    cannyimage = cv2.Canny(cannyimage, low_threshold, high_threshold)
    cannyimage = cannyimage[:, :, None]
    cannyimage = np.concatenate([cannyimage, cannyimage, cannyimage], axis=2)
    cannyimage = Image.fromarray(cannyimage)
    images = [cannyimage]

    image = pipe(
        [prompt]*2,
        images,
        num_inference_steps=one,
        generator=generator,
        strength=two
        negative_prompt=[neg_prompt]*2,
        controlnet_conditioning_scale=three,
    )
    for i, imge in enumerate(imoge["images"]):
        apol.append(imge)
    apol.append(original)
    apol.append(cannyimage)
    return apol

iface = gr.Interface(fn=plex, inputs=[gr.Textbox(label="QR Code URL"),gr.Textbox(label="prompt"),gr.Textbox(label="neg prompt"),gr.Dopdown(choices=models, label="some sd models", value=models[0]), gr.Slider(label="num inference steps", minimum=1, step=1, maximum=5, value=5), gr.Slider(label="prompt strength", minimum=0.1, step=0.1, maximum=1, value=0.2), gr.Slider(label="controlnet scale", minimum=0.1, step=0.1, maximum=1, value=0.8)], outputs=gr.Gallery(label="out", columns=1))
iface.queue(max=1)
iface.launch()