from typing import Any import gradio as gr from backend.models.lcmdiffusion_setting import LCMDiffusionSetting from context import Context from models.interface_types import InterfaceType from app_settings import Settings from constants import LCM_DEFAULT_MODEL, LCM_DEFAULT_MODEL_OPENVINO from frontend.utils import is_reshape_required from app_settings import AppSettings from constants import DEVICE from frontend.utils import enable_openvino_controls from scipy.ndimage import zoom import numpy as np from PIL import Image from super_image import CarnModel,ImageLoader random_enabled = True context = Context(InterfaceType.WEBUI) previous_width = 0 previous_height = 0 previous_model_id = "" previous_num_of_images = 0 upscaler = CarnModel.from_pretrained('eugenesiow/carn-bam', scale=2) def generate_text_to_image( prompt, inference_steps, guidance_scale, seed, use_openvino, use_safety_checker, ) -> Any: global previous_height, previous_width, previous_model_id, previous_num_of_images model_id = LCM_DEFAULT_MODEL if use_openvino: model_id = LCM_DEFAULT_MODEL_OPENVINO use_seed = True if seed != -1 else False lcm_diffusion_settings = LCMDiffusionSetting( lcm_model_id=model_id, prompt=prompt, image_height=384, image_width=384, inference_steps=inference_steps, guidance_scale=guidance_scale, number_of_images=1, seed=seed, use_openvino=use_openvino, use_safety_checker=use_safety_checker, use_seed=use_seed, ) settings = Settings( lcm_diffusion_setting=lcm_diffusion_settings, ) reshape = False if use_openvino: reshape = is_reshape_required( previous_width, 384, previous_height, 384, previous_model_id, model_id, previous_num_of_images, 1, ) images = context.generate_text_to_image( settings, reshape, DEVICE, ) previous_width = 384 previous_height = 384 previous_model_id = model_id previous_num_of_images = 1 out_images = [] for image in images: #out_images.append(image.resize((768, 768),resample=Image.LANCZOS)) in_image = ImageLoader.load_image(image) up_image =upscaler(in_image) out_images.append(up_image) return out_images def get_text_to_image_ui(app_settings: AppSettings) -> None: with gr.Blocks(): with gr.Row(): with gr.Column(): def random_seed(): global random_enabled random_enabled = not random_enabled seed_val = -1 if not random_enabled: seed_val = 42 return gr.Number.update( interactive=not random_enabled, value=seed_val ) with gr.Row(): prompt = gr.Textbox( label="Describe the image you'd like to see", lines=3, placeholder="A fantasy landscape", ) generate_btn = gr.Button( "Generate", elem_id="generate_button", scale=0, ) with gr.Accordion("Advanced options", open=False): guidance_scale = gr.Slider( 1.0, 30.0, value=8, step=0.5, label="Guidance Scale" ) seed = gr.Number( label="Seed", value=-1, precision=0, interactive=False, ) seed_checkbox = gr.Checkbox( label="Use random seed", value=True, interactive=True, ) openvino_checkbox = gr.Checkbox( label="Use OpenVINO", value=True, interactive=False, ) safety_checker_checkbox = gr.Checkbox( label="Use Safety Checker", value=True, interactive=True, ) num_inference_steps = gr.Slider( 1, 8, value=4, step=1, label="Inference Steps" ) # image_height = gr.Slider( # 256, 768, value=384, step=64, label="Image Height",interactive=Fa # ) # image_width = gr.Slider( # 256, 768, value=384, step=64, label="Image Width" # ) # num_images = gr.Slider( # 1, # 50, # value=1, # step=1, # label="Number of images to generate", # ) input_params = [ prompt, num_inference_steps, guidance_scale, seed, openvino_checkbox, safety_checker_checkbox, ] with gr.Column(): output = gr.Gallery( label="Generated images", show_label=True, elem_id="gallery", columns=2, ) seed_checkbox.change(fn=random_seed, outputs=seed) generate_btn.click( fn=generate_text_to_image, inputs=input_params, outputs=output, )