| import gradio as gr | |
| import torch | |
| from torch import autocast | |
| from diffusers import StableDiffusionPipeline | |
| from datasets import load_dataset | |
| from PIL import Image | |
| import re | |
| import os | |
| auth_token = os.getenv("auth_token") | |
| model_id = "CompVis/stable-diffusion-v1-4" | |
| device = "cpu" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=auth_token, revision="fp16", torch_dtype=torch.float16) | |
| pipe = pipe.to(device) | |
| def infer(prompt, samples, steps, scale, seed): | |
| generator = torch.Generator(device=device).manual_seed(seed) | |
| images_list = pipe( | |
| [prompt] * samples, | |
| num_inference_steps=steps, | |
| guidance_scale=scale, | |
| generator=generator, | |
| ) | |
| images = [] | |
| safe_image = Image.open(r"unsafe.png") | |
| for i, image in enumerate(images_list["sample"]): | |
| if(images_list["nsfw_content_detected"][i]): | |
| images.append(safe_image) | |
| else: | |
| images.append(image) | |
| return images | |
| block = gr.Blocks() | |
| with block: | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row().style(mobile_collapse=False, equal_height=True): | |
| text = gr.Textbox( | |
| label="Enter your prompt", | |
| show_label=False, | |
| max_lines=1, | |
| placeholder="Enter your prompt", | |
| ).style( | |
| border=(True, False, True, True), | |
| rounded=(True, False, False, True), | |
| container=False, | |
| ) | |
| btn = gr.Button("Generate image").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| ) | |
| gallery = gr.Gallery( | |
| label="Generated images", show_label=False, elem_id="gallery" | |
| ).style(grid=[2], height="auto") | |
| advanced_button = gr.Button("Advanced options", elem_id="advanced-btn") | |
| with gr.Row(elem_id="advanced-options"): | |
| samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1) | |
| steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1) | |
| scale = gr.Slider( | |
| label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1 | |
| ) | |
| seed = gr.Slider( | |
| label="Seed", | |
| minimum=0, | |
| maximum=2147483647, | |
| step=1, | |
| randomize=True, | |
| ) | |
| text.submit(infer, inputs=[text, samples, steps, scale, seed], outputs=gallery) | |
| btn.click(infer, inputs=[text, samples, steps, scale, seed], outputs=gallery) | |
| advanced_button.click( | |
| None, | |
| [], | |
| text, | |
| ) | |
| block.launch() |