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| import gradio as gr | |
| import os | |
| from gradio_client import Client | |
| title="Prompt Converter" | |
| description=""" | |
| <h1>Prompt Converter</h1> | |
| <p style="text-align:center;"> | |
| Stable Diffusion 2 uses OpenCLIP ViT-H model trained on LAION dataset so it knows different things than the OpenAI ViT-L we're all used to prompting. | |
| <br />This demo converts a v1.x stable diffusion prompt to a stable diffusion 2.x prompt, | |
| <br />by generating an image through <a href="https://huggingface.co/runwayml/stable-diffusion-v1-5" target="_blank">RunwayML Stable Diffusion 1.5</a>, then Interrogate the resulting image through <a href="https://huggingface.co/spaces/fffiloni/CLIP-Interrogator-2" target="_blank">CLIP Interrogator 2</a> to give you a Stable Diffusion 2 equivalent prompt. | |
| </p> | |
| """ | |
| stable_diffusion = Client("https://runwayml-stable-diffusion-v1-5.hf.space/") | |
| clip_interrogator_2 = Client("https://fffiloni-clip-interrogator-2.hf.space/") | |
| def get_images(prompt): | |
| print("Calling SD") | |
| gallery_dir = stable_diffusion.predict(prompt, fn_index=2) | |
| print(f"Gallery Directory: {gallery_dir}") | |
| img_results = [os.path.join(gallery_dir, img) for img in os.listdir(gallery_dir)] | |
| return img_results[0] | |
| def get_new_prompt(img, mode): | |
| interrogate = clip_interrogator_2.predict( | |
| img, # str (filepath or URL to image) in 'parameter_3' Image component | |
| mode, # str in 'Select mode' Radio component | |
| 12, # int | float (numeric value between 2 and 24) in 'best mode max flavors' Slider component | |
| api_name="/clipi2" | |
| ) | |
| #interrogate = clip_interrogator_2(img, mode, 12, api_name="clipi2") | |
| return interrogate | |
| def infer(prompt, mode): | |
| img = get_images(prompt) | |
| result = get_new_prompt(img, mode) | |
| #return result[0], img | |
| return img | |
| with gr.Blocks() as demo: | |
| gr.HTML(description) | |
| with gr.Row(): | |
| with gr.Column(): | |
| prompt_input = gr.Textbox(lines=4, label="Input v1.x Stable Diffusion prompt") | |
| mode_input = gr.Radio(['best', 'classic', 'fast'], label='mode', value='fast') | |
| submit_btn = gr.Button("Submit") | |
| with gr.Column(): | |
| sd_inter = gr.Image() | |
| prompt_output = gr.Textbox(lines=4, label="Converted v2.x Stable Diffusion prompt") | |
| submit_btn.click( | |
| fn=infer, inputs=[prompt_input,mode_input], outputs=[sd_inter] | |
| ) | |
| examples=[ | |
| ["girl with steampunk weapons and uniform, serious, finely detailed, made by wlop, boichi, ilya kuvshinov, full body portrait, illustration, grass, sunny, sky, anime, side view, perfect anime face, detailed face, zoomed out, smooth","fast"], | |
| ["a yellow cockatiel riding on the rings of saturn wearing a propeller hat, fantasy, intricate, elegant, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha ","classic"], | |
| ["painting, view from inside edward hopper's painting nighthawks, of a group of werebears robbing a bank, foggy ","best"] | |
| ] | |
| gr.Examples( | |
| examples = examples, | |
| fn = infer, | |
| inputs=[prompt_input,mode_input], | |
| outputs=[sd_inter] | |
| ) | |
| #demo=gr.Interface(fn=infer, inputs=[prompt_input,mode_input], outputs=[prompt_output],title=title,description=description,examples=examples) | |
| demo.queue(max_size=10,concurrency_count=20) | |
| demo.launch(enable_queue=True) |