| import gradio as gr |
| from fetch import get_values |
| from dotenv import load_dotenv |
| load_dotenv() |
| import prodia |
| import requests |
| import random |
| from datetime import datetime |
| import os |
|
|
|
|
| prodia_key = os.getenv('PRODIA_X_KEY', None) |
| if prodia_key is None: |
| print("Please set PRODIA_X_KEY in .env, closing...") |
| exit() |
| client = prodia.Client(api_key=prodia_key) |
|
|
| def process_input_text2img(prompt, negative_prompt, steps, cfg_scale, number, seed, model, sampler, aspect_ratio, upscale, save=False): |
| images = [] |
| for image in range(number): |
| result = client.txt2img(prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, |
| steps=steps, cfg_scale=cfg_scale, seed=seed, aspect_ratio=aspect_ratio, upscale=upscale) |
| images.append(result.url) |
| if save: |
| date = datetime.now() |
| if not os.path.isdir(f'./outputs/{date.year}-{date.month}-{date.day}'): |
| os.mkdir(f'./outputs/{date.year}-{date.month}-{date.day}') |
| img_data = requests.get(result.url).content |
| with open(f"./outputs/{date.year}-{date.month}-{date.day}/{random.randint(1, 10000000000000)}_{result.seed}.png", "wb") as f: |
| f.write(img_data) |
| return images |
|
|
| def process_input_img2img(init, prompt, negative_prompt, steps, cfg_scale, number, seed, model, sampler, ds, upscale, save): |
| images = [] |
| for image in range(number): |
| result = client.img2img(imageUrl=init, prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, |
| steps=steps, cfg_scale=cfg_scale, seed=seed, denoising_strength=ds, upscale=upscale) |
| images.append(result.url) |
| if save: |
| date = datetime.now() |
| if not os.path.isdir(f'./outputs/{date.year}-{date.month}-{date.day}'): |
| os.mkdir(f'./outputs/{date.year}-{date.month}-{date.day}') |
| img_data = requests.get(result.url).content |
| with open(f"./outputs/{date.year}-{date.month}-{date.day}/{random.randint(1, 10000000000000)}_{result.seed}.png", "wb") as f: |
| f.write(img_data) |
| return images |
|
|
| """ |
| def process_input_control(init, prompt, negative_prompt, steps, cfg_scale, number, seed, model, control_model, sampler): |
| images = [] |
| for image in range(number): |
| result = client.controlnet(imageUrl=init, prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, |
| steps=steps, cfg_scale=cfg_scale, seed=seed, controlnet_model=control_model) |
| images.append(result.url) |
| return images |
| """ |
|
|
| theme = "Base" |
|
|
|
|
| with gr.Blocks(theme=theme) as demo: |
| |
| |
| |
| |
| gr.Markdown(""" |
| # ForgeStudio Large |
| |
| <p></p> |
| |
| |
| """) |
|
|
| with gr.Accordion("🆔 Account", open=False): |
| with gr.Row(): |
| gr.LoginButton(size="sm") |
| gr.LogoutButton(size="sm") |
|
|
|
|
| |
| |
| gr.DuplicateButton(value="Duplicate space for private use") |
|
|
| |
| |
| with gr.Tab(label="txt2img"): |
| with gr.Row(): |
| with gr.Column(): |
| prompt = gr.Textbox(label="Prompt", lines=2, placeholder="beautiful cat, 8k") |
| negative = gr.Textbox(label="Negative Prompt", lines=3, value="text, blurry, fuzziness", placeholder="Add words you don't want to show up in your art...") |
|
|
| with gr.Row(): |
| steps = gr.Slider(label="Steps", value=25, step=1, maximum=50, minimum=5, interactive=True) |
| cfg = gr.Slider(label="CFG Scale", maximum=20, minimum=1, value=7, interactive=True, info="Recommended 7 CFG Scale") |
|
|
| with gr.Row(): |
| num = gr.Slider(label="Number of images", value=1, step=1, maximum=4, minimum=1, interactive=True) |
| seed = gr.Slider(label="Seed", value=-1, step=1, minimum=-1, maximum=4294967295, interactive=True, info="""'-1' is a random seed""") |
|
|
| with gr.Row(): |
| model = gr.Dropdown(label="Model", choices=get_values()[0], value="v1-5-pruned-emaonly.ckpt [81761151]", interactive=True) |
| sampler = gr.Dropdown(label="Sampler", choices=get_values()[1], value="DPM++ SDE Karras", interactive=True) |
|
|
| with gr.Row(): |
| ar = gr.Radio(label="Aspect Ratio", choices=["square", "portrait", "landscape"], value="square", interactive=True) |
| with gr.Column(): |
| upscale = gr.Checkbox(label="upscale", value=True, interactive=True, info="""'True' recommended, improves image quality""") |
|
|
| with gr.Row(): |
| run_btn = gr.Button("Generate", variant="primary") |
| with gr.Column(): |
| result_image = gr.Gallery(label="Result Image(s)", show_download_button=False, show_share_button=True) |
|
|
| with gr.Accordion("📑 Examples", open=False): |
| with gr.Row(): |
| gr.Examples( |
| |
| examples=[ |
| |
| ["A high tech solarpunk utopia in the Amazon rainforest"], |
| ["A pikachu fine dining with a view to the Eiffel Tower"], |
| ["A mecha robot in a favela in expressionist style"], |
| ["an insect robot preparing a delicious meal"], |
| ["A small cabin on top of a snowy mountain in the style of Disney, artstation"] |
| ], |
| |
| inputs=[prompt], |
| cache_examples=False, |
| ) |
| |
| run_btn.click( |
| process_input_text2img, |
| inputs=[ |
| prompt, |
| negative, |
| steps, |
| cfg, |
| num, |
| seed, |
| model, |
| sampler, |
| ar, |
| upscale |
| ], |
| outputs=[result_image], |
| ) |
|
|
| with gr.Tab(label="img2img"): |
| with gr.Row(): |
| with gr.Column(): |
| prompt = gr.Textbox(label="Prompt", lines=2, placeholder="beautiful cat, 8k") |
|
|
| with gr.Row(): |
| negative = gr.Textbox(label="Negative Prompt", lines=3, placeholder="Add words you don't want to show up in your art...") |
|
|
| gr.Markdown(""" |
| |
| <p></p> |
| |
| ⚠️ Attention, only images generated by ForgeStudio Large are accepted, that is, first generate an image in the txt2img section, and then insert a link to this image in the Init Image URL, for example: https://images.prodia.xyz/image.png |
| |
| """) |
| |
| init_image = gr.Textbox(label="Init Image Url", lines=3, placeholder="https://images.prodia.xyz/d372060f-673d-486d-b3a8-f2c8a33f25f3.png") |
|
|
|
|
| with gr.Row(): |
| steps = gr.Slider(label="Steps", value=25, step=1, maximum=50, minimum=1, interactive=True) |
| cfg = gr.Slider(label="CFG Scale", maximum=20, minimum=1, value=7, interactive=True, info="Recommended 7 CFG Scale") |
|
|
| with gr.Row(): |
| num = gr.Slider(label="Number of images", value=1, step=1, maximum=4, minimum=1, interactive=True) |
| seed = gr.Slider(label="Seed", value=-1, step=1, minimum=-1, maximum=4294967295, interactive=True, info="""'-1' is a random seed""") |
|
|
| with gr.Row(): |
| model = gr.Dropdown(label="Model", choices=get_values()[0], value="v1-5-pruned-emaonly.ckpt [81761151]", interactive=True) |
| sampler = gr.Dropdown(label="Sampler", choices=get_values()[1], value="DPM++ 2M Karras", interactive=True) |
|
|
| with gr.Row(): |
| ds = gr.Slider(label="Denoising strength", maximum=0.9, minimum=0.1, value=0.5, interactive=True) |
| with gr.Column(): |
| upscale = gr.Checkbox(label="upscale", value=True, interactive=True, info="""'True' recommended, improves image quality""") |
| |
|
|
| with gr.Row(): |
| run_btn = gr.Button("Generate", variant="primary") |
| with gr.Column(): |
| result_image = gr.Gallery(label="Result Image(s)") |
| run_btn.click( |
| process_input_img2img, |
| inputs=[ |
| init_image, |
| prompt, |
| negative, |
| steps, |
| cfg, |
| num, |
| seed, |
| model, |
| sampler, |
| ds, |
| upscale |
| ], |
| outputs=[result_image], |
| ) |
| with gr.Tab(label="Others"): |
| with gr.Tab(label="Image Tools"): |
| with gr.Accordion("Remove Background", open=False): |
| with gr.Row(): |
| gr.load("hardon-server/remove-background-on-image-def", src="spaces") |
| with gr.Accordion("Flip Image", open=False): |
| with gr.Row(): |
| gr.load("hardon-server/image_flip", src="spaces") |
| with gr.Accordion("Sepia Filter", open=False): |
| with gr.Row(): |
| gr.load("hardon-server/sepia_filter", src="spaces") |
| with gr.Tab(label="GANs"): |
| with gr.Accordion("RANGAN", open=False): |
| with gr.Row(): |
| gr.load("hardon-server/projected_gan1", src="spaces") |
| |
|
|
|
|
| |
| |
| with gr.Tab(label="Gallery"): |
|
|
| gr.load("nateraw/stable_diffusion_gallery", src="spaces") |
| |
| with gr.Tab(label="License"): |
|
|
| gr.load("4com/4com-license", src="spaces") |
|
|
| if __name__ == "__main__": |
| demo.launch(show_api=False, enable_queue=False, debug=False, share=False, show_error=False) |
