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| # This demo needs to be run from the repo folder. | |
| # python demo/fake_gan/run.py | |
| import os | |
| import random | |
| import gradio as gr | |
| import itertools | |
| from PIL import Image, ImageFont, ImageDraw | |
| import sys | |
| sys.path.append("source") | |
| import DirectedDiffusion | |
| EX1 = [ | |
| "A painting of a tiger, on the wall in the living room", | |
| "0.2,0.6,0.0,0.5", | |
| "1,5", | |
| 5, | |
| 15, | |
| 1.0, | |
| 2094889, | |
| ] | |
| def fake_gan(a, b, c): | |
| print(a, b, c) | |
| images = [ | |
| ( | |
| random.choice( | |
| [ | |
| "https://images.unsplash.com/photo-1507003211169-0a1dd7228f2d?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=387&q=80", | |
| "https://images.unsplash.com/photo-1554151228-14d9def656e4?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=386&q=80", | |
| "https://images.unsplash.com/photo-1542909168-82c3e7fdca5c?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8aHVtYW4lMjBmYWNlfGVufDB8fDB8fA%3D%3D&w=1000&q=80", | |
| "https://images.unsplash.com/photo-1546456073-92b9f0a8d413?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=387&q=80", | |
| "https://images.unsplash.com/photo-1601412436009-d964bd02edbc?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=464&q=80", | |
| ] | |
| ), | |
| f"label {i}" if i != 0 else "label" * 50, | |
| ) | |
| for i in range(3) | |
| ] | |
| return images | |
| model_bundle = DirectedDiffusion.AttnEditorUtils.load_all_models( | |
| model_path_diffusion="CompVis/stable-diffusion-v1-4" | |
| ) | |
| def directed_diffusion( | |
| in_prompt, | |
| in_bb, | |
| in_token_ids, | |
| in_slider_trailings, | |
| in_slider_ddsteps, | |
| in_slider_gcoef, | |
| in_seed, | |
| is_draw_bbox, | |
| ): | |
| str_arg_to_val = lambda arg, f: [ | |
| [f(b) for b in a.split(",")] for a in arg.split(" ") | |
| ] | |
| roi = str_arg_to_val(in_bb, float) | |
| attn_editor_bundle = { | |
| "edit_index": str_arg_to_val(in_token_ids, int), | |
| "roi": roi, | |
| "num_trailing_attn": [in_slider_trailings] * len(roi), | |
| "num_affected_steps": in_slider_ddsteps, | |
| "noise_scale": [in_slider_gcoef] * len(roi), | |
| } | |
| img = DirectedDiffusion.Diffusion.stablediffusion( | |
| model_bundle, | |
| attn_editor_bundle=attn_editor_bundle, | |
| guidance_scale=7.5, | |
| prompt=in_prompt, | |
| steps=50, | |
| seed=in_seed, | |
| is_save_attn=False, | |
| is_save_recons=False, | |
| ) | |
| print(img.size) | |
| if is_draw_bbox and in_slider_ddsteps > 0: | |
| for r in roi: | |
| x0, y0, x1, y1 = [int(r_ * 512) for r_ in r] | |
| print(x0, y0, x1, y1) | |
| image_editable = ImageDraw.Draw(img) | |
| image_editable.rectangle( | |
| xy=[x0, y0, x1, y1], outline=(255, 0, 0, 255), width=5 | |
| ) | |
| return img | |
| def run_it( | |
| in_prompt, | |
| in_bb, | |
| in_token_ids, | |
| in_slider_trailings, | |
| in_slider_ddsteps, | |
| in_slider_gcoef, | |
| in_seed, | |
| is_draw_bbox, | |
| is_grid_search, | |
| progress=gr.Progress(), | |
| ): | |
| num_affected_steps = [in_slider_ddsteps] | |
| noise_scale = [in_slider_gcoef] | |
| num_trailing_attn = [in_slider_trailings] | |
| if is_grid_search: | |
| num_affected_steps = [5, 10] | |
| #noise_scale = [1.0, 1.5, 2.5] | |
| #num_trailing_attn = [10, 20, 30, 40] | |
| param_list = [num_affected_steps, noise_scale, num_trailing_attn] | |
| param_list = list(itertools.product(*param_list)) | |
| results = [] | |
| progress(0, desc="Starting...") | |
| for i, element in enumerate(progress.tqdm(param_list)): | |
| print("=========== Arguments ============") | |
| print("Prompt:", in_prompt) | |
| print("BoundingBox:", in_bb) | |
| print("Token indices:", in_token_ids) | |
| print("Num Trialings:", element[2]) | |
| print("Num DD steps:", element[0]) | |
| print("Gaussian coef:", element[1]) | |
| print("Seed:", in_seed) | |
| print("===================================") | |
| img = directed_diffusion( | |
| in_prompt=in_prompt, | |
| in_bb=in_bb, | |
| in_token_ids=in_token_ids, | |
| in_slider_trailings=element[2], | |
| in_slider_ddsteps=element[0], | |
| in_slider_gcoef=element[1], | |
| in_seed=in_seed, | |
| is_draw_bbox=is_draw_bbox, | |
| ) | |
| results.append( | |
| ( | |
| img, | |
| "#Trailing:{},#DDSteps:{},GaussianCoef:{}".format( | |
| element[2], element[0], element[1] | |
| ), | |
| ) | |
| ) | |
| return results | |
| with gr.Blocks() as demo: | |
| with gr.Row(variant="panel"): | |
| with gr.Column(variant="compact"): | |
| in_prompt = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| ).style( | |
| container=False, | |
| ) | |
| with gr.Row(variant="compact"): | |
| in_bb = gr.Textbox( | |
| label="Bounding box", | |
| show_label=True, | |
| max_lines=1, | |
| placeholder="e.g., 0.1,0.5,0.3,0.6", | |
| ) | |
| in_token_ids = gr.Textbox( | |
| label="Token idices", | |
| show_label=True, | |
| max_lines=1, | |
| placeholder="e.g., 1,2,3", | |
| ) | |
| in_seed = gr.Number( | |
| value=2483964026821236, label="Random seed", interactive=True | |
| ) | |
| with gr.Row(variant="compact"): | |
| is_grid_search = gr.Checkbox( | |
| value=False, | |
| label="Grid search? (Checked then sliders are ignored)", | |
| ) | |
| is_draw_bbox = gr.Checkbox( | |
| value=True, | |
| label="To draw the bounding box?", | |
| ) | |
| with gr.Row(variant="compact"): | |
| in_slider_trailings = gr.Slider( | |
| minimum=1, maximum=30, value=10, step=1, label="#trailings" | |
| ) | |
| in_slider_ddsteps = gr.Slider( | |
| minimum=0, maximum=20, value=10, step=1, label="#DDSteps" | |
| ) | |
| in_slider_gcoef = gr.Slider( | |
| minimum=1, maximum=5, value=1.0, step=0.1, label="GaussianCoef" | |
| ) | |
| btn = gr.Button("Generate image").style(full_width=False) | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery" | |
| ).style(grid=[2], height="auto") | |
| args = [ | |
| in_prompt, | |
| in_bb, | |
| in_token_ids, | |
| in_slider_trailings, | |
| in_slider_ddsteps, | |
| in_slider_gcoef, | |
| in_seed, | |
| is_draw_bbox, | |
| is_grid_search, | |
| ] | |
| btn.click( | |
| run_it, | |
| inputs=args, | |
| outputs=gallery, | |
| ) | |
| examples = gr.Examples( | |
| examples=[EX1], | |
| inputs=args, | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue().launch(share=True) | |