Spaces:
Runtime error
Runtime error
| # Edit Anything trained with Stable Diffusion + ControlNet + SAM + BLIP2 | |
| import gradio as gr | |
| from diffusers.utils import load_image | |
| from sam2edit_lora import EditAnythingLoraModel, config_dict | |
| def create_demo(process): | |
| print("The GUI is not fully tested yet. Please open an issue if you find bugs.") | |
| WARNING_INFO = f'''### [NOTE] the model is collected from the Internet for demo only, please do not use it for commercial purposes. | |
| We are not responsible for possible risks using this model. | |
| ''' | |
| block = gr.Blocks() | |
| with block as demo: | |
| with gr.Row(): | |
| gr.Markdown( | |
| "## Generate Your Beauty powered by EditAnything https://github.com/sail-sg/EditAnything ") | |
| with gr.Row(): | |
| with gr.Column(): | |
| source_image = gr.Image( | |
| source='upload', label="Image (Upload an image and cover the region you want to edit with sketch)", type="numpy", tool="sketch") | |
| enable_all_generate = gr.Checkbox( | |
| label='Auto generation on all region.', value=False) | |
| prompt = gr.Textbox( | |
| label="Prompt (Text in the expected things of edited region)") | |
| enable_auto_prompt = gr.Checkbox( | |
| label='Auto generate text prompt from input image with BLIP2: Warning: Enable this may makes your prompt not working.', value=False) | |
| a_prompt = gr.Textbox( | |
| label="Added Prompt", value='best quality, extremely detailed') | |
| n_prompt = gr.Textbox(label="Negative Prompt", | |
| value='longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality') | |
| control_scale = gr.Slider( | |
| label="Mask Align strength (Large value means more strict alignment with SAM mask)", minimum=0, maximum=1, value=1, step=0.1) | |
| run_button = gr.Button(label="Run") | |
| num_samples = gr.Slider( | |
| label="Images", minimum=1, maximum=12, value=2, step=1) | |
| seed = gr.Slider(label="Seed", minimum=-1, | |
| maximum=2147483647, step=1, randomize=True) | |
| with gr.Accordion("Advanced options", open=False): | |
| condition_model = gr.Dropdown(choices=list(config_dict.keys()), | |
| value=list( | |
| config_dict.keys())[1], | |
| label='Model', | |
| multiselect=False) | |
| mask_image = gr.Image( | |
| source='upload', label="(Optional) Upload a predefined mask of edit region if you do not want to write your prompt.", type="numpy", value=None) | |
| image_resolution = gr.Slider( | |
| label="Image Resolution", minimum=256, maximum=768, value=512, step=64) | |
| strength = gr.Slider( | |
| label="Control Strength", minimum=0.0, maximum=2.0, value=1.0, step=0.01) | |
| guess_mode = gr.Checkbox( | |
| label='Guess Mode', value=False) | |
| detect_resolution = gr.Slider( | |
| label="SAM Resolution", minimum=128, maximum=2048, value=1024, step=1) | |
| ddim_steps = gr.Slider( | |
| label="Steps", minimum=1, maximum=100, value=30, step=1) | |
| scale = gr.Slider( | |
| label="Guidance Scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1) | |
| eta = gr.Number(label="eta (DDIM)", value=0.0) | |
| with gr.Column(): | |
| result_gallery = gr.Gallery( | |
| label='Output', show_label=False, elem_id="gallery").style(grid=2, height='auto') | |
| result_text = gr.Text(label='BLIP2+Human Prompt Text') | |
| ips = [condition_model, source_image, enable_all_generate, mask_image, control_scale, enable_auto_prompt, prompt, a_prompt, n_prompt, num_samples, image_resolution, | |
| detect_resolution, ddim_steps, guess_mode, strength, scale, seed, eta] | |
| run_button.click(fn=process, inputs=ips, outputs=[ | |
| result_gallery, result_text]) | |
| # with gr.Row(): | |
| # ex = gr.Examples(examples=examples, fn=process, | |
| # inputs=[a_prompt, n_prompt, scale], | |
| # outputs=[result_gallery], | |
| # cache_examples=False) | |
| with gr.Row(): | |
| gr.Markdown(WARNING_INFO) | |
| return demo | |
| if __name__ == '__main__': | |
| model = EditAnythingLoraModel(base_model_path="stabilityai/stable-diffusion-2-inpainting", | |
| controlmodel_name='LAION Pretrained(v0-4)-SD21', extra_inpaint=False, | |
| lora_model_path=None, use_blip=True) | |
| demo = create_demo(model.process) | |
| demo.queue().launch(server_name='0.0.0.0') | |