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import gradio as gr |
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import torch |
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from diffusers import StableDiffusionImg2ImgPipeline |
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from .utils.schedulers import SCHEDULER_LIST, get_scheduler_list |
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from .utils.prompt2prompt import generate |
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from .utils.device import get_device |
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from PIL import Image |
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from .download import get_share_js, get_community_loading_icon, CSS |
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IMG2IMG_MODEL_LIST = { |
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"StableDiffusion 1.5" : "runwayml/stable-diffusion-v1-5", |
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"StableDiffusion 2.1" : "stabilityai/stable-diffusion-2-1", |
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"OpenJourney v4" : "prompthero/openjourney-v4", |
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"DreamLike 1.0" : "dreamlike-art/dreamlike-diffusion-1.0", |
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"DreamLike 2.0" : "dreamlike-art/dreamlike-photoreal-2.0" |
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} |
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class StableDiffusionImage2ImageGenerator: |
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def __init__(self): |
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self.pipe = None |
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def load_model(self, model_path, scheduler): |
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model_path = IMG2IMG_MODEL_LIST[model_path] |
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if self.pipe is None: |
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self.pipe = StableDiffusionImg2ImgPipeline.from_pretrained( |
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model_path, safety_checker=None, torch_dtype=torch.float32 |
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) |
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device = get_device() |
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self.pipe = get_scheduler_list(pipe=self.pipe, scheduler=scheduler) |
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self.pipe.to(device) |
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return self.pipe |
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def generate_image( |
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self, |
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image_path: str, |
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model_path: str, |
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prompt: str, |
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negative_prompt: str, |
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num_images_per_prompt: int, |
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scheduler: str, |
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guidance_scale: int, |
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num_inference_step: int, |
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seed_generator=0, |
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): |
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pipe = self.load_model( |
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model_path=model_path, |
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scheduler=scheduler, |
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) |
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if seed_generator == 0: |
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random_seed = torch.randint(0, 1000000, (1,)) |
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generator = torch.manual_seed(random_seed) |
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else: |
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generator = torch.manual_seed(seed_generator) |
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image = Image.open(image_path) |
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images = pipe( |
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prompt, |
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image=image, |
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negative_prompt=negative_prompt, |
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num_images_per_prompt=num_images_per_prompt, |
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num_inference_steps=num_inference_step, |
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guidance_scale=guidance_scale, |
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generator=generator, |
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).images |
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return images |
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def app(): |
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demo = gr.Blocks(css=CSS) |
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with demo: |
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with gr.Row(): |
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with gr.Column(): |
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image2image_image_file = gr.Image( |
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type="filepath", label="Upload",elem_id="image-upload-img2img" |
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).style(height=260) |
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image2image_prompt = gr.Textbox( |
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lines=1, |
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placeholder="Prompt", |
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show_label=False, |
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elem_id="prompt-text-input-img2img", |
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value='' |
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) |
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image2image_negative_prompt = gr.Textbox( |
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lines=1, |
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placeholder="Negative Prompt", |
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show_label=False, |
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elem_id = "negative-prompt-text-input-img2img", |
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value='' |
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) |
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image2image_generate_prompt_button = gr.Button( |
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label="Generate Prompt", |
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type="primary", |
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align="center", |
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value = "Generate Prompt" |
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) |
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image2image_generated_prompt = gr.Textbox( |
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lines=1, |
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placeholder="Generated Prompt", |
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show_label=False, |
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) |
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with gr.Row(): |
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with gr.Column(): |
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image2image_model_path = gr.Dropdown( |
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choices=list(IMG2IMG_MODEL_LIST.keys()), |
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value=list(IMG2IMG_MODEL_LIST.keys())[0], |
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label="Imaget2Image Model Selection", |
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elem_id="model-dropdown-img2img", |
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) |
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image2image_guidance_scale = gr.Slider( |
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minimum=0.1, |
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maximum=15, |
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step=0.1, |
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value=7.5, |
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label="Guidance Scale", |
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elem_id = "guidance-scale-slider-img2img" |
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) |
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image2image_num_inference_step = gr.Slider( |
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minimum=1, |
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maximum=100, |
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step=1, |
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value=50, |
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label="Num Inference Step", |
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elem_id = "num-inference-step-slider-img2img" |
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) |
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with gr.Row(): |
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with gr.Column(): |
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image2image_scheduler = gr.Dropdown( |
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choices=SCHEDULER_LIST, |
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value=SCHEDULER_LIST[0], |
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label="Scheduler", |
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elem_id="scheduler-dropdown-img2img", |
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) |
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image2image_num_images_per_prompt = gr.Slider( |
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minimum=1, |
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maximum=30, |
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step=1, |
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value=1, |
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label="Number Of Images", |
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) |
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image2image_seed_generator = gr.Slider( |
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label="Seed(0 for random)", |
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minimum=0, |
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maximum=1000000, |
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value=0, |
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elem_id="seed-slider-img2img", |
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) |
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image2image_predict_button = gr.Button(value="Generator") |
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with gr.Column(): |
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output_image = gr.Gallery( |
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label="Generated images", |
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show_label=False, |
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elem_id="gallery", |
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).style(grid=(1, 2)) |
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with gr.Group(elem_id="container-advanced-btns"): |
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with gr.Group(elem_id="share-btn-container"): |
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community_icon_html, loading_icon_html = get_community_loading_icon("img2img") |
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community_icon = gr.HTML(community_icon_html) |
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loading_icon = gr.HTML(loading_icon_html) |
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share_button = gr.Button("Save artwork", elem_id="share-btn-img2img") |
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image2image_predict_button.click( |
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fn=StableDiffusionImage2ImageGenerator().generate_image, |
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inputs=[ |
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image2image_image_file, |
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image2image_model_path, |
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image2image_prompt, |
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image2image_negative_prompt, |
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image2image_num_images_per_prompt, |
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image2image_scheduler, |
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image2image_guidance_scale, |
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image2image_num_inference_step, |
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image2image_seed_generator, |
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], |
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outputs=[output_image], |
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) |
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image2image_generate_prompt_button.click( |
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fn=generate, |
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inputs=[image2image_prompt], |
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outputs=[image2image_generated_prompt], |
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) |
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return demo |
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