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import gradio as gr |
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import torch |
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import numpy as np |
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import requests |
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import random |
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from io import BytesIO |
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from utils import * |
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from constants import * |
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from inversion_utils import * |
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from modified_pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline |
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from torch import autocast, inference_mode |
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from diffusers import StableDiffusionPipeline |
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from diffusers import DDIMScheduler |
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from transformers import AutoProcessor, BlipForConditionalGeneration |
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sd_model_id = "stabilityai/stable-diffusion-2-1-base" |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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sd_pipe = StableDiffusionPipeline.from_pretrained(sd_model_id,torch_dtype=torch.float16).to(device) |
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sd_pipe.scheduler = DDIMScheduler.from_config(sd_model_id, subfolder = "scheduler") |
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sem_pipe = SemanticStableDiffusionPipeline.from_pretrained(sd_model_id, torch_dtype=torch.float16).to(device) |
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blip_processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base") |
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blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base",torch_dtype=torch.float16).to(device) |
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def caption_image(input_image): |
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inputs = blip_processor(images=input_image, return_tensors="pt").to(device, torch.float16) |
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pixel_values = inputs.pixel_values |
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generated_ids = blip_model.generate(pixel_values=pixel_values, max_length=50) |
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generated_caption = blip_processor.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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return generated_caption, generated_caption |
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def invert(x0, prompt_src="", num_diffusion_steps=100, cfg_scale_src = 3.5, eta = 1): |
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sd_pipe.scheduler.set_timesteps(num_diffusion_steps) |
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with inference_mode(): |
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w0 = (sd_pipe.vae.encode(x0).latent_dist.mode() * 0.18215) |
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wt, zs, wts = inversion_forward_process(sd_pipe, w0, etas=eta, prompt=prompt_src, cfg_scale=cfg_scale_src, prog_bar=True, num_inference_steps=num_diffusion_steps) |
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return zs, wts |
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def sample(zs, wts, prompt_tar="", cfg_scale_tar=15, skip=36, eta = 1): |
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w0, _ = inversion_reverse_process(sd_pipe, xT=wts[skip], etas=eta, prompts=[prompt_tar], cfg_scales=[cfg_scale_tar], prog_bar=True, zs=zs[skip:]) |
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with inference_mode(): |
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x0_dec = sd_pipe.vae.decode(1 / 0.18215 * w0).sample |
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if x0_dec.dim()<4: |
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x0_dec = x0_dec[None,:,:,:] |
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img = image_grid(x0_dec) |
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return img |
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def reconstruct(tar_prompt, |
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tar_cfg_scale, |
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skip, |
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wts, zs, |
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do_reconstruction, |
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reconstruction, |
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reconstruct_button |
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): |
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if reconstruct_button == "Hide Reconstruction": |
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return reconstruction.value, reconstruction, ddpm_edited_image.update(visible=False), do_reconstruction, "Show Reconstruction" |
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else: |
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if do_reconstruction: |
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reconstruction_img = sample(zs.value, wts.value, prompt_tar=tar_prompt, skip=skip, cfg_scale_tar=tar_cfg_scale) |
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reconstruction = gr.State(value=reconstruction_img) |
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do_reconstruction = False |
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return reconstruction.value, reconstruction, ddpm_edited_image.update(visible=True), do_reconstruction, "Hide Reconstruction" |
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def load_and_invert( |
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input_image, |
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do_inversion, |
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seed, randomize_seed, |
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wts, zs, |
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src_prompt ="", |
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tar_prompt="", |
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steps=100, |
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src_cfg_scale = 3.5, |
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skip=36, |
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tar_cfg_scale=15, |
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progress=gr.Progress(track_tqdm=True) |
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): |
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x0 = load_512(input_image, device=device).to(torch.float16) |
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if do_inversion or randomize_seed: |
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zs_tensor, wts_tensor = invert(x0 =x0 , prompt_src=src_prompt, num_diffusion_steps=steps, cfg_scale_src=src_cfg_scale) |
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wts = gr.State(value=wts_tensor) |
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zs = gr.State(value=zs_tensor) |
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do_inversion = False |
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return wts, zs, do_inversion, inversion_progress.update(visible=False) |
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def edit(input_image, |
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wts, zs, |
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tar_prompt, |
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image_caption, |
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steps, |
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skip, |
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tar_cfg_scale, |
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edit_concept_1,edit_concept_2,edit_concept_3, |
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guidnace_scale_1,guidnace_scale_2,guidnace_scale_3, |
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warmup_1, warmup_2, warmup_3, |
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neg_guidance_1, neg_guidance_2, neg_guidance_3, |
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threshold_1, threshold_2, threshold_3, |
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do_reconstruction, |
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reconstruction, |
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do_inversion, |
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seed, |
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randomize_seed, |
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src_prompt, |
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src_cfg_scale): |
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if do_inversion or randomize_seed: |
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x0 = load_512(input_image, device=device).to(torch.float16) |
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zs_tensor, wts_tensor = invert(x0 =x0 , prompt_src=src_prompt, num_diffusion_steps=steps, cfg_scale_src=src_cfg_scale) |
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wts = gr.State(value=wts_tensor) |
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zs = gr.State(value=zs_tensor) |
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do_inversion = False |
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if image_caption.lower() == tar_prompt.lower(): |
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tar_prompt = "" |
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if edit_concept_1 != "" or edit_concept_2 != "" or edit_concept_3 != "": |
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editing_args = dict( |
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editing_prompt = [edit_concept_1,edit_concept_2,edit_concept_3], |
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reverse_editing_direction = [ neg_guidance_1, neg_guidance_2, neg_guidance_3,], |
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edit_warmup_steps=[warmup_1, warmup_2, warmup_3,], |
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edit_guidance_scale=[guidnace_scale_1,guidnace_scale_2,guidnace_scale_3], |
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edit_threshold=[threshold_1, threshold_2, threshold_3], |
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edit_momentum_scale=0.3, |
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edit_mom_beta=0.6, |
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eta=1,) |
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latnets = wts.value[skip].expand(1, -1, -1, -1) |
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sega_out = sem_pipe(prompt=tar_prompt, latents=latnets, guidance_scale = tar_cfg_scale, |
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num_images_per_prompt=1, |
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num_inference_steps=steps, |
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use_ddpm=True, wts=wts.value, zs=zs.value[skip:], **editing_args) |
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return sega_out.images[0], reconstruct_button.update(visible=True), do_reconstruction, reconstruction, wts, zs, do_inversion |
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else: |
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if do_reconstruction: |
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pure_ddpm_img = sample(zs.value, wts.value, prompt_tar=tar_prompt, skip=skip, cfg_scale_tar=tar_cfg_scale) |
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reconstruction = gr.State(value=pure_ddpm_img) |
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do_reconstruction = False |
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return pure_ddpm_img, reconstruct_button.update(visible=False), do_reconstruction, reconstruction, wts, zs, do_inversion |
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return reconstruction.value, reconstruct_button.update(visible=False), do_reconstruction, reconstruction, wts, zs, do_inversion |
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def randomize_seed_fn(seed, randomize_seed): |
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if randomize_seed: |
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seed = random.randint(0, np.iinfo(np.int32).max) |
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torch.manual_seed(seed) |
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return seed |
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def get_example(): |
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case = [ |
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[ |
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'examples/lemons_input.jpg', |
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'apples', 'lemons', |
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'a ceramic bowl', |
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'examples/lemons_output.jpg', |
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7,7, |
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1,1, |
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False, True, |
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100, |
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36, |
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15, |
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], |
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[ |
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'examples/girl_with_pearl_earring_input.png', |
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'glasses', '', |
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'', |
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'examples/girl_with_pearl_earring_output.png', |
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3,7, |
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3,2, |
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False,False, |
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100, |
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36, |
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15, |
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], |
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[ |
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'examples/rockey_shore_input.jpg', |
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'sea turtle', '', |
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'watercolor painting', |
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'examples/rockey_shore_output.jpg', |
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7,7, |
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1,2, |
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False,False, |
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100, |
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36, |
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15, |
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], |
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[ |
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'examples/flower_field_input.jpg', |
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'wheat', 'red flowers', |
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'oil painting', |
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'examples/flower_field_output_2.jpg', |
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20,7, |
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1,1, |
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False,True, |
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100, |
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36, |
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15, |
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], |
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[ |
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'examples/butterfly_input.jpg', |
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'bee', 'butterfly', |
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'oil painting', |
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'examples/butterfly_output.jpg', |
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7, 7, |
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1,1, |
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False, True, |
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100, |
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36, |
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15, |
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] |
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] |
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return case |
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def swap_visibilities(input_image, |
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edit_concept_1, |
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edit_concept_2, |
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tar_prompt, |
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sega_edited_image, |
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guidnace_scale_1, |
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guidnace_scale_2, |
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warmup_1, |
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warmup_2, |
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neg_guidance_1, |
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neg_guidance_2, |
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steps, |
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skip, |
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tar_cfg_scale, |
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sega_concepts_counter |
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): |
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sega_concepts_counter=0 |
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concept1_update = update_display_concept("Remove" if neg_guidance_1 else "Add", edit_concept_1, neg_guidance_1, sega_concepts_counter) |
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if(edit_concept_2 != ""): |
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concept2_update = update_display_concept("Remove" if neg_guidance_2 else "Add", edit_concept_2, neg_guidance_2, sega_concepts_counter+1) |
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else: |
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concept2_update = gr.update(visible=False), gr.update(visible=False),gr.update(visible=False), gr.update(value=neg_guidance_2),gr.update(visible=True),gr.update(visible=False),sega_concepts_counter+1 |
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return (*concept1_update[:-1], *concept2_update) |
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intro = """ |
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<h1 style="font-weight: 1400; text-align: center; margin-bottom: 7px;"> |
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LEDITS - Pipeline for editing images |
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</h1> |
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<h3 style="font-weight: 600; text-align: center;"> |
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Real Image Latent Editing with Edit Friendly DDPM and Semantic Guidance |
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</h3> |
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<h4 style="text-align: center; margin-bottom: 7px;"> |
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<a href="https://editing-images-project.hf.space/" style="text-decoration: underline;" target="_blank">Project Page</a> | <a href="https://arxiv.org/abs/2307.00522" style="text-decoration: underline;" target="_blank">ArXiv</a> |
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</h4> |
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<p style="font-size: 0.9rem; margin: 0rem; line-height: 1.2em; margin-top:1em"> |
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<a href="https://huggingface.co/spaces/editing-images/edit_friendly_ddpm_x_sega?duplicate=true"> |
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<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3CWLGkA" alt="Duplicate Space"></a> |
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<p/>""" |
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help_text = """ |
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- **Getting Started - edit images with DDPM X SEGA:** |
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The are 3 general setting options you can play with - |
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1. **Pure DDPM Edit -** Describe the desired edited output image in detail |
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2. **Pure SEGA Edit -** Keep the target prompt empty ***or*** with a description of the original image and add editing concepts for Semantic Gudiance editing |
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3. **Combined -** Describe the desired edited output image in detail and add additional SEGA editing concepts on top |
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- **Getting Started - Tips** |
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While the best approach depends on your editing objective and source image, we can layout a few guiding tips to use as a starting point - |
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1. **DDPM** is usually more suited for scene/style changes and major subject changes (for example ) while **SEGA** allows for more fine grained control, changes are more delicate, more suited for adding details (for example facial expressions and attributes, subtle style modifications, object adding/removing) |
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2. The more you describe the scene in the target prompt (both the parts and details you wish to keep the same and those you wish to change), the better the result |
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3. **Combining DDPM Edit with SEGA -** |
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Try dividing your editing objective to more significant scene/style/subject changes and detail adding/removing and more moderate changes. Then describe the major changes in a detailed target prompt and add the more fine grained details as SEGA concepts. |
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4. **Reconstruction:** Using an empty source prompt + target prompt will lead to a perfect reconstruction |
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- **Fidelity vs creativity**: |
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Bigger values → more fidelity, smaller values → more creativity |
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1. `Skip Steps` |
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2. `Warmup` (SEGA) |
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3. `Threshold` (SEGA) |
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Bigger values → more creativity, smaller values → more fidelity |
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1. `Guidance Scale` |
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2. `Concept Guidance Scale` (SEGA) |
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""" |
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with gr.Blocks(css="style.css") as demo: |
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def update_counter(sega_concepts_counter, concept1, concept2, concept3): |
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if sega_concepts_counter == "": |
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sega_concepts_counter = sum(1 for concept in (concept1, concept2, concept3) if concept != '') |
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return sega_concepts_counter |
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def remove_concept(sega_concepts_counter, row_triggered): |
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sega_concepts_counter -= 1 |
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rows_visibility = [gr.update(visible=False) for _ in range(4)] |
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if(row_triggered-1 > sega_concepts_counter): |
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rows_visibility[sega_concepts_counter] = gr.update(visible=True) |
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else: |
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rows_visibility[row_triggered-1] = gr.update(visible=True) |
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row1_visibility, row2_visibility, row3_visibility, row4_visibility = rows_visibility |
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guidance_scale_label = "Concept Guidance Scale" |
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return (gr.update(visible=False), |
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gr.update(visible=False, value="",), |
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gr.update(interactive=True, value=""), |
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gr.update(visible=False,label = guidance_scale_label), |
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gr.update(interactive=True, value =False), |
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gr.update(value=DEFAULT_WARMUP_STEPS), |
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gr.update(value=DEFAULT_THRESHOLD), |
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gr.update(visible=True), |
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gr.update(interactive=True, value="custom"), |
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row1_visibility, |
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row2_visibility, |
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row3_visibility, |
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row4_visibility, |
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sega_concepts_counter |
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) |
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def update_display_concept(button_label, edit_concept, neg_guidance, sega_concepts_counter): |
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sega_concepts_counter += 1 |
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guidance_scale_label = "Concept Guidance Scale" |
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if(button_label=='Remove'): |
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neg_guidance = True |
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guidance_scale_label = "Negative Guidance Scale" |
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return (gr.update(visible=True), |
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gr.update(visible=True, value=edit_concept), |
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gr.update(visible=True,label = guidance_scale_label), |
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gr.update(value=neg_guidance), |
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gr.update(visible=False), |
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gr.update(visible=True), |
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sega_concepts_counter |
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) |
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def display_editing_options(run_button, clear_button, sega_tab): |
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return run_button.update(visible=True), clear_button.update(visible=True), sega_tab.update(visible=True) |
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def update_interactive_mode(add_button_label): |
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if add_button_label == "Clear": |
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return gr.update(interactive=False), gr.update(interactive=False) |
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else: |
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return gr.update(interactive=True), gr.update(interactive=True) |
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def update_dropdown_parms(dropdown): |
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if dropdown == 'custom': |
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return DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE,DEFAULT_WARMUP_STEPS, DEFAULT_THRESHOLD |
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elif dropdown =='style': |
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return STYLE_SEGA_CONCEPT_GUIDANCE_SCALE,STYLE_WARMUP_STEPS, STYLE_THRESHOLD |
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elif dropdown =='object': |
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return OBJECT_SEGA_CONCEPT_GUIDANCE_SCALE,OBJECT_WARMUP_STEPS, OBJECT_THRESHOLD |
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elif dropdown =='faces': |
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return FACE_SEGA_CONCEPT_GUIDANCE_SCALE,FACE_WARMUP_STEPS, FACE_THRESHOLD |
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def reset_do_inversion(): |
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return True |
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def reset_do_reconstruction(): |
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do_reconstruction = True |
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return do_reconstruction |
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def reset_image_caption(): |
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return "" |
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def update_inversion_progress_visibility(input_image, do_inversion): |
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if do_inversion and not input_image is None: |
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return inversion_progress.update(visible=True) |
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else: |
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return inversion_progress.update(visible=False) |
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def update_edit_progress_visibility(input_image, do_inversion): |
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return inversion_progress.update(visible=True) |
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gr.HTML(intro) |
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wts = gr.State() |
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zs = gr.State() |
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reconstruction = gr.State() |
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do_inversion = gr.State(value=True) |
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do_reconstruction = gr.State(value=True) |
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sega_concepts_counter = gr.State(0) |
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image_caption = gr.State(value="") |
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with gr.Row(): |
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input_image = gr.Image(label="Input Image", interactive=True) |
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ddpm_edited_image = gr.Image(label=f"Pure DDPM Inversion Image", interactive=False, visible=False) |
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sega_edited_image = gr.Image(label=f"LEDITS Edited Image", interactive=False) |
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input_image.style(height=365, width=365) |
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ddpm_edited_image.style(height=365, width=365) |
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sega_edited_image.style(height=365, width=365) |
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with gr.Row(): |
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with gr.Box(visible=False) as box1: |
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with gr.Row(): |
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concept_1 = gr.Button(scale=3) |
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remove_concept1 = gr.Button("x", scale=1, min_width=10) |
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with gr.Row(): |
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guidnace_scale_1 = gr.Slider(label='Concept Guidance Scale', minimum=1, maximum=30, |
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info="How strongly the concept should modify the image", |
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value=DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE, |
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step=0.5, interactive=True) |
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with gr.Box(visible=False) as box2: |
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with gr.Row(): |
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concept_2 = gr.Button(scale=3) |
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remove_concept2 = gr.Button("x", scale=1, min_width=10) |
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with gr.Row(): |
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guidnace_scale_2 = gr.Slider(label='Concept Guidance Scale', minimum=1, maximum=30, |
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info="How strongly the concept should modify the image", |
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value=DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE, |
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step=0.5, interactive=True) |
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with gr.Box(visible=False) as box3: |
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with gr.Row(): |
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concept_3 = gr.Button(visible=False, scale=3) |
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remove_concept3 = gr.Button("x", scale=1, min_width=10) |
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with gr.Row(): |
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guidnace_scale_3 = gr.Slider(label='Concept Guidance Scale', minimum=1, maximum=30, |
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info="How strongly the concept should modify the image", |
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value=DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE, |
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step=0.5, interactive=True,visible=False) |
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with gr.Row(): |
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inversion_progress = gr.Textbox(visible=False, label="Inversion progress") |
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with gr.Box(): |
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intro_segs = gr.Markdown("Add/Remove Concepts from your Image <span style=\"font-size: 12px; color: rgb(156, 163, 175)\">with Semantic Guidance</span>") |
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with gr.Row().style(mobile_collapse=False) as row1: |
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with gr.Column(scale=3, min_width=100): |
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with gr.Row().style(mobile_collapse=True): |
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edit_concept_1 = gr.Textbox( |
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label="Concept", |
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show_label=True, |
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max_lines=1, value="", |
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placeholder="E.g.: Sunglasses", |
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) |
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dropdown1 = gr.Dropdown(label = "Edit Type", value ='custom' , choices=['custom','style', 'object', 'faces']) |
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with gr.Column(scale=1, min_width=100, visible=False): |
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neg_guidance_1 = gr.Checkbox( |
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label='Remove Concept?') |
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with gr.Column(scale=1, min_width=100): |
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with gr.Row().style(mobile_collapse=False): |
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with gr.Column(): |
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add_1 = gr.Button('Add') |
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remove_1 = gr.Button('Remove') |
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|
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with gr.Row(visible=False).style(equal_height=True) as row2: |
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with gr.Column(scale=3, min_width=100): |
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with gr.Row().style(mobile_collapse=True): |
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|
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edit_concept_2 = gr.Textbox( |
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label="Concept", |
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show_label=True, |
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max_lines=1, |
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placeholder="E.g.: Realistic", |
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) |
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dropdown2 = gr.Dropdown(label = "Edit Type", value ='custom' , choices=['custom','style', 'object', 'faces']) |
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with gr.Column(scale=1, min_width=100, visible=False): |
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neg_guidance_2 = gr.Checkbox( |
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label='Remove Concept?') |
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|
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with gr.Column(scale=1, min_width=100): |
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with gr.Row().style(mobile_collapse=False): |
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with gr.Column(): |
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add_2 = gr.Button('Add') |
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remove_2 = gr.Button('Remove') |
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with gr.Row(visible=False).style(equal_height=True) as row3: |
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with gr.Column(scale=3, min_width=100): |
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with gr.Row().style(mobile_collapse=True): |
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|
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edit_concept_3 = gr.Textbox( |
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label="Concept", |
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show_label=True, |
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max_lines=1, |
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placeholder="E.g.: orange", |
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) |
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dropdown3 = gr.Dropdown(label = "Edit Type", value ='custom' , choices=['custom','style', 'object', 'faces']) |
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with gr.Column(scale=1, min_width=100, visible=False): |
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neg_guidance_3 = gr.Checkbox( |
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label='Remove Concept?',visible=True) |
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|
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with gr.Column(scale=1, min_width=100): |
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with gr.Row().style(mobile_collapse=False): |
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with gr.Column(): |
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add_3 = gr.Button('Add') |
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remove_3 = gr.Button('Remove') |
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with gr.Row(visible=False).style(equal_height=True) as row4: |
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gr.Markdown("### Max of 3 concepts reached. Remove a concept to add more") |
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with gr.Row().style(mobile_collapse=False, equal_height=True): |
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tar_prompt = gr.Textbox( |
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label="Describe your edited image (optional)", |
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|
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max_lines=1, value="", scale=3, |
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placeholder="Target prompt, DDPM Inversion", info = "DDPM Inversion Prompt. Can help with global changes, modify to what you would like to see" |
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) |
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with gr.Row(): |
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run_button = gr.Button("Edit your image!", visible=True) |
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with gr.Accordion("Advanced Options", open=False): |
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with gr.Tabs() as tabs: |
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|
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with gr.TabItem('General options', id=2): |
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with gr.Row(): |
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with gr.Column(min_width=100): |
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clear_button = gr.Button("Clear", visible=True) |
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src_prompt = gr.Textbox(lines=1, label="Source Prompt", interactive=True, placeholder="") |
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steps = gr.Number(value=100, precision=0, label="Num Diffusion Steps", interactive=True) |
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src_cfg_scale = gr.Number(value=3.5, label=f"Source Guidance Scale", interactive=True) |
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|
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with gr.Column(min_width=100): |
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reconstruct_button = gr.Button("Show Reconstruction", visible=False) |
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skip = gr.Slider(minimum=0, maximum=60, value=36, label="Skip Steps", interactive=True, info = "At which step to start denoising. Bigger values increase fidelity to input image") |
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tar_cfg_scale = gr.Slider(minimum=7, maximum=30,value=15, label=f"Guidance Scale", interactive=True) |
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seed = gr.Number(value=0, precision=0, label="Seed", interactive=True) |
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randomize_seed = gr.Checkbox(label='Randomize seed', value=False) |
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|
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with gr.TabItem('SEGA options', id=3) as sega_advanced_tab: |
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|
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gr.Markdown("1st concept") |
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with gr.Row().style(mobile_collapse=False, equal_height=True): |
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warmup_1 = gr.Slider(label='Warmup', minimum=0, maximum=50, |
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value=DEFAULT_WARMUP_STEPS, |
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step=1, interactive=True, info="At which step to start applying semantic guidance. Bigger values reduce edit concept's effect") |
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threshold_1 = gr.Slider(label='Threshold', minimum=0.5, maximum=0.99, |
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value=DEFAULT_THRESHOLD, step=0.01, interactive=True, |
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info = "Lower the threshold for more effect (e.g. ~0.9 for style transfer)") |
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|
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|
|
gr.Markdown("2nd concept") |
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with gr.Row() as row2_advanced: |
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warmup_2 = gr.Slider(label='Warmup', minimum=0, maximum=50, |
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value=DEFAULT_WARMUP_STEPS, |
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step=1, interactive=True, info="At which step to start applying semantic guidance. Bigger values reduce edit concept's effect") |
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threshold_2 = gr.Slider(label='Threshold', minimum=0.5, maximum=0.99, |
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value=DEFAULT_THRESHOLD, |
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step=0.01, interactive=True, |
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info = "Lower the threshold for more effect (e.g. ~0.9 for style transfer)") |
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|
|
gr.Markdown("3rd concept") |
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with gr.Row() as row3_advanced: |
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warmup_3 = gr.Slider(label='Warmup', minimum=0, maximum=50, |
|
value=DEFAULT_WARMUP_STEPS, step=1, |
|
interactive=True, info="At which step to start applying semantic guidance. Bigger values reduce edit concept's effect") |
|
threshold_3 = gr.Slider(label='Threshold', minimum=0.5, maximum=0.99, |
|
value=DEFAULT_THRESHOLD, step=0.01, |
|
interactive=True, |
|
info = "Lower the threshold for more effect (e.g. ~0.9 for style transfer)") |
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add_1.click(fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then(fn = update_display_concept, inputs=[add_1, edit_concept_1, neg_guidance_1, sega_concepts_counter], outputs=[box1, concept_1, guidnace_scale_1,neg_guidance_1,row1, row2, sega_concepts_counter],queue=False) |
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add_2.click(fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then(fn = update_display_concept, inputs=[add_2, edit_concept_2, neg_guidance_2, sega_concepts_counter], outputs=[box2, concept_2, guidnace_scale_2,neg_guidance_2,row2, row3, sega_concepts_counter],queue=False) |
|
add_3.click(fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then(fn = update_display_concept, inputs=[add_3, edit_concept_3, neg_guidance_3, sega_concepts_counter], outputs=[box3, concept_3, guidnace_scale_3,neg_guidance_3,row3, row4, sega_concepts_counter],queue=False) |
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|
|
remove_1.click(fn = update_display_concept, inputs=[remove_1, edit_concept_1, neg_guidance_1, sega_concepts_counter], outputs=[box1, concept_1, guidnace_scale_1,neg_guidance_1,row1, row2, sega_concepts_counter],queue=False) |
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remove_2.click(fn = update_display_concept, inputs=[remove_2, edit_concept_2, neg_guidance_2 ,sega_concepts_counter], outputs=[box2, concept_2, guidnace_scale_2,neg_guidance_2,row2, row3,sega_concepts_counter],queue=False) |
|
remove_3.click(fn = update_display_concept, inputs=[remove_3, edit_concept_3, neg_guidance_3, sega_concepts_counter], outputs=[box3, concept_3, guidnace_scale_3,neg_guidance_3, row3, row4, sega_concepts_counter],queue=False) |
|
|
|
remove_concept1.click( |
|
fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then( |
|
fn = remove_concept, inputs=[sega_concepts_counter,gr.State(1)], outputs= [box1, concept_1, edit_concept_1, guidnace_scale_1,neg_guidance_1,warmup_1, threshold_1, add_1, dropdown1, row1, row2, row3, row4, sega_concepts_counter],queue=False) |
|
remove_concept2.click( |
|
fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then( |
|
fn = remove_concept, inputs=[sega_concepts_counter,gr.State(2)], outputs=[box2, concept_2, edit_concept_2, guidnace_scale_2,neg_guidance_2, warmup_2, threshold_2, add_2 , dropdown2, row1, row2, row3, row4, sega_concepts_counter],queue=False) |
|
remove_concept3.click( |
|
fn=update_counter,inputs=[sega_concepts_counter,edit_concept_1,edit_concept_2,edit_concept_3], outputs=sega_concepts_counter,queue=False).then( |
|
fn = remove_concept,inputs=[sega_concepts_counter,gr.State(3)], outputs=[box3, concept_3, edit_concept_3, guidnace_scale_3,neg_guidance_3,warmup_3, threshold_3, add_3, dropdown3, row1, row2, row3, row4, sega_concepts_counter],queue=False) |
|
|
|
|
|
|
|
|
|
run_button.click( |
|
fn=edit, |
|
inputs=[input_image, |
|
wts, zs, |
|
tar_prompt, |
|
image_caption, |
|
steps, |
|
skip, |
|
tar_cfg_scale, |
|
edit_concept_1,edit_concept_2,edit_concept_3, |
|
guidnace_scale_1,guidnace_scale_2,guidnace_scale_3, |
|
warmup_1, warmup_2, warmup_3, |
|
neg_guidance_1, neg_guidance_2, neg_guidance_3, |
|
threshold_1, threshold_2, threshold_3, do_reconstruction, reconstruction, |
|
do_inversion, |
|
seed, |
|
randomize_seed, |
|
src_prompt, |
|
src_cfg_scale |
|
|
|
|
|
], |
|
outputs=[sega_edited_image, reconstruct_button, do_reconstruction, reconstruction, wts, zs, do_inversion]) |
|
|
|
|
|
|
|
input_image.change( |
|
fn = reset_do_inversion, |
|
outputs = [do_inversion], |
|
queue = False) |
|
|
|
input_image.upload( |
|
fn = reset_do_inversion, |
|
outputs = [do_inversion], |
|
queue = False).then(fn = caption_image, |
|
inputs = [input_image], |
|
outputs = [tar_prompt, image_caption]).then(fn = update_inversion_progress_visibility, inputs =[input_image,do_inversion], |
|
outputs=[inversion_progress],queue=False).then( |
|
fn=load_and_invert, |
|
inputs=[input_image, |
|
do_inversion, |
|
seed, randomize_seed, |
|
wts, zs, |
|
src_prompt, |
|
tar_prompt, |
|
steps, |
|
src_cfg_scale, |
|
skip, |
|
tar_cfg_scale, |
|
], |
|
|
|
outputs=[wts, zs, do_inversion, inversion_progress], |
|
).then(fn = update_inversion_progress_visibility, inputs =[input_image,do_inversion], |
|
outputs=[inversion_progress],queue=False).then( |
|
lambda: reconstruct_button.update(visible=False), |
|
outputs=[reconstruct_button]).then( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], |
|
queue = False) |
|
|
|
|
|
|
|
src_prompt.change( |
|
fn = reset_do_inversion, |
|
outputs = [do_inversion], queue = False).then( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
steps.change( |
|
fn = reset_do_inversion, |
|
outputs = [do_inversion], queue = False).then( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
|
|
src_cfg_scale.change( |
|
fn = reset_do_inversion, |
|
outputs = [do_inversion], queue = False).then( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
|
|
|
|
tar_prompt.change( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
tar_cfg_scale.change( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
skip.change( |
|
fn = reset_do_reconstruction, |
|
outputs = [do_reconstruction], queue = False) |
|
|
|
dropdown1.change(fn=update_dropdown_parms, inputs = [dropdown1], outputs = [guidnace_scale_1,warmup_1, threshold_1]) |
|
dropdown2.change(fn=update_dropdown_parms, inputs = [dropdown2], outputs = [guidnace_scale_2,warmup_2, threshold_2]) |
|
dropdown3.change(fn=update_dropdown_parms, inputs = [dropdown3], outputs = [guidnace_scale_3,warmup_3, threshold_3]) |
|
|
|
clear_components = [input_image,ddpm_edited_image,ddpm_edited_image,sega_edited_image, do_inversion, |
|
src_prompt, steps, src_cfg_scale, seed, |
|
tar_prompt, skip, tar_cfg_scale, reconstruct_button,reconstruct_button, |
|
edit_concept_1, guidnace_scale_1,guidnace_scale_1,warmup_1, threshold_1, neg_guidance_1,dropdown1, concept_1, concept_1, row1, |
|
edit_concept_2, guidnace_scale_2,guidnace_scale_2,warmup_2, threshold_2, neg_guidance_2,dropdown2, concept_2, concept_2, row2, |
|
edit_concept_3, guidnace_scale_3,guidnace_scale_3,warmup_3, threshold_3, neg_guidance_3,dropdown3, concept_3,concept_3, row3, |
|
row4,sega_concepts_counter, box1, box2, box3 ] |
|
|
|
clear_components_output_vals = [None, None,ddpm_edited_image.update(visible=False), None, True, |
|
"", DEFAULT_DIFFUSION_STEPS, DEFAULT_SOURCE_GUIDANCE_SCALE, DEFAULT_SEED, |
|
"", DEFAULT_SKIP_STEPS, DEFAULT_TARGET_GUIDANCE_SCALE, reconstruct_button.update(value="Show Reconstruction"),reconstruct_button.update(visible=False), |
|
"", DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE,guidnace_scale_1.update(visible=False), DEFAULT_WARMUP_STEPS, DEFAULT_THRESHOLD, DEFAULT_NEGATIVE_GUIDANCE, "custom","", concept_1.update(visible=False), row1.update(visible=True), |
|
"", DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE,guidnace_scale_2.update(visible=False), DEFAULT_WARMUP_STEPS, DEFAULT_THRESHOLD, DEFAULT_NEGATIVE_GUIDANCE, "custom","", concept_2.update(visible=False), row2.update(visible=False), |
|
"", DEFAULT_SEGA_CONCEPT_GUIDANCE_SCALE,guidnace_scale_3.update(visible=False), DEFAULT_WARMUP_STEPS, DEFAULT_THRESHOLD, DEFAULT_NEGATIVE_GUIDANCE, "custom","",concept_3.update(visible=False), row3.update(visible=False), row4.update(visible=False), gr.update(value=0), |
|
box1.update(visible=False), box2.update(visible=False), box3.update(visible=False)] |
|
|
|
|
|
clear_button.click(lambda: clear_components_output_vals, outputs =clear_components) |
|
|
|
reconstruct_button.click(lambda: ddpm_edited_image.update(visible=True), outputs=[ddpm_edited_image]).then(fn = reconstruct, |
|
inputs = [tar_prompt, |
|
tar_cfg_scale, |
|
skip, |
|
wts, zs, |
|
do_reconstruction, |
|
reconstruction, |
|
reconstruct_button], |
|
outputs = [ddpm_edited_image,reconstruction, ddpm_edited_image, do_reconstruction, reconstruct_button]) |
|
|
|
randomize_seed.change( |
|
fn = randomize_seed_fn, |
|
inputs = [seed, randomize_seed], |
|
outputs = [seed], |
|
queue = False) |
|
|
|
|
|
|
|
gr.Examples( |
|
label='Examples', |
|
fn=swap_visibilities, |
|
run_on_click=True, |
|
examples=get_example(), |
|
inputs=[input_image, |
|
edit_concept_1, |
|
edit_concept_2, |
|
tar_prompt, |
|
sega_edited_image, |
|
guidnace_scale_1, |
|
guidnace_scale_2, |
|
warmup_1, |
|
warmup_2, |
|
neg_guidance_1, |
|
neg_guidance_2, |
|
steps, |
|
skip, |
|
tar_cfg_scale, |
|
sega_concepts_counter |
|
], |
|
outputs=[box1, concept_1, guidnace_scale_1,neg_guidance_1, row1, row2,box2, concept_2, guidnace_scale_2,neg_guidance_2,row2, row3,sega_concepts_counter], |
|
cache_examples=True |
|
) |
|
|
|
|
|
demo.queue() |
|
demo.launch() |