app.py

import torch
import numpy as np
import gradio as gr
import spaces
import cv2
import os

from typing import Dict
from PIL import Image
from huggingface_hub import Repository

token = os.environ['model_fetch']

engine_repo = Repository(local_dir="engine", clone_from="felixrosberg/EngageDiffusion", use_auth_token=token)

from engine.ui_model import fetch_model, run_model
from engine.ui_gradio import fetch_ui

engage_logo = Image.open("engage_studios_logo.png").resize((700, 88), Image.Resampling.BICUBIC)
engage_logo_mask = np.clip(np.array(engage_logo.split()[-1])[..., None] / 255, 0, 1)
engage_logo_np = np.array(engage_logo.convert('RGB'))

pipe = fetch_model()
pipe.to('cuda')


@spaces.GPU
def inference(user_state, condition_image, settings, prompt, neg_prompt, inference_steps=8, num_images=2,
              guidance_scale=2.0,
              guidance_rescale=0.0,
              enable_freeu=False,

              height=1024,
              width=1024,

              condition_scale=0.5,
              sketch_detail=1.0,
              sketch_softness=0.5,
              inpaint_strength=0.9,

              exposure=0.0,
              enable_stylation=False,

              style_1_down=0.0,
              style_1_mid=0.0,
              style_1_up=0.0,

              style_2_down=0.0,
              style_2_mid=0.0,
              style_2_up=0.0,

              style_3_down=0.0,
              style_3_mid=0.0,
              style_3_up=0.0,

              style_4_down=0.0,
              style_4_mid=0.0,
              style_4_up=0.0,

              seed=None,
              progress=gr.Progress()):

    images = run_model(pipe, user_state, condition_image, settings, prompt, neg_prompt, inference_steps, num_images,
              guidance_scale,
              guidance_rescale,
              enable_freeu,

              height,
              width,

              condition_scale,
              sketch_detail,
              sketch_softness,
              inpaint_strength,

              exposure,
              enable_stylation,

              style_1_down,
              style_1_mid,
              style_1_up,

              style_2_down,
              style_2_mid,
              style_2_up,

              style_3_down,
              style_3_mid,
              style_3_up,

              style_4_down,
              style_4_mid,
              style_4_up,

              seed,
              progress)

    for idx, im in enumerate(images):
        im = np.asarray(im).copy()
        im[-88:, :700] = im[-88:, :700] * (1 - engage_logo_mask) + engage_logo_np
        images[idx] = Image.fromarray(np.clip(im.astype('uint8'), 0, 255))

    user_state["IMAGE_GALLERY"] += images
    return user_state["IMAGE_GALLERY"], user_state


engage_demo = fetch_ui(inference)
engage_demo.launch()