mariarivaille/Diffusion_Models_Course_Space

1import gradio as gr2import numpy as np3from infer import infer, CONTROLNET_MODE, MAX_SEED4 5MAX_IMAGE_SIZE = 10246 7examples = [8    "The image of a cartoonish mouse with clown red round nose and white curly hair. The mouse is gray with big pink ears and a black pointed nose. It has a simple design, the background color is white. The style of the image is reminiscent of a sticker or a digital illustration.",9    "The image of a cartoonish mouse eating from a red bowl of yellow triangle chips, her cheeks are full. The mouse is gray with big pink ears, small white eyes and a black pointed nose. It has a simple design, the background color is white. The style of the image is reminiscent of a sticker or a digital illustration.",10    "The image of a cartoonish mouse with red hearts instead of eyes meaning that the mouse is in love with something. The mouse is gray with big pink ears and a black pointed nose. It has a simple design, the background color is white. The style of the image is reminiscent of a sticker or a digital illustration.",11    "The image of a cartoonish mouse with sunglasses and smiling. The mouse is gray with big pink ears and a black pointed nose. It has a simple design, the background color is white. The style of the image is reminiscent of a sticker or a digital illustration.",12]13 14css = """15#col-container {16    margin: 0 auto;17    max-width: 640px;18}19"""20 21def on_checkbox_change(use_advanced):22    visible = use_advanced23    return (gr.update(visible=visible, interactive=visible),24            gr.update(visible=visible, interactive=visible),25            gr.update(visible=visible, interactive=visible))26 27with gr.Blocks(css=css) as demo:28    with gr.Column(elem_id="col-container"):29        gr.Markdown(" # Maria Lashina T2I Rat Stickers Generation App")30 31        MODEL_LIST = [32            "CompVis/stable-diffusion-v1-4",33            "stable-diffusion-v1-5/stable-diffusion-v1-5",34            "Maria_Lashina_LoRA"35        ]36        with gr.Row():37            model_id = gr.Dropdown(38                label="Model",39                choices=MODEL_LIST40            )41 42        with gr.Row():43            prompt = gr.Text(44                label="Prompt",45                show_label=False,46                max_lines=1,47                placeholder="Enter your prompt",48                container=False,49            )50 51            run_button = gr.Button("Run", scale=0, variant="primary")52 53        result = gr.Image(label="Result", show_label=False)54 55        with gr.Accordion("Advanced Settings", open=False):56            negative_prompt = gr.Text(57                label="Negative prompt",58                max_lines=1,59                # placeholder="Enter a negative prompt",60                value="bad anatomy, disfigured, poorly drawn face, ugly, low quality, blurry, distortion",61                visible=True,62            )63 64            with gr.Row():65                delete_background = gr.Checkbox(label="Delete background?")66 67            use_controlnet = gr.Checkbox(label="Use ControlNet")68            control_strength = gr.Slider(69                label="ControlNet strength",70                minimum=0,71                maximum=1,72                step=0.1,73                value=0.8,74                visible=False75            )76            controlnet_mode = gr.Dropdown(CONTROLNET_MODE.keys(), label="ControlNet mode", visible=False)77            controlnet_image = gr.Image(label="ControlNet image", visible=False)78            use_controlnet.change(on_checkbox_change, use_controlnet, [control_strength, controlnet_mode, controlnet_image])79 80            use_ip_adapter = gr.Checkbox(label="Use IPAdapter")81            ip_adapter_scale = gr.Slider(82                label="IPAdapter scale",83                minimum=0,84                maximum=1,85                step=0.1,86                value=0.8,87                visible=False88            )89            ip_adapter_image = gr.Image(label="IPAdapter image", visible=False)90            use_ip_adapter.change(on_checkbox_change, use_ip_adapter, [ip_adapter_scale, ip_adapter_image])91 92            seed = gr.Slider(93                label="Seed",94                minimum=0,95                maximum=MAX_SEED,96                step=1,97                value=42,98            )99 100            randomize_seed = gr.Checkbox(label="Randomize seed", value=False)101 102            with gr.Row():103                width = gr.Slider(104                    label="Width",105                    minimum=256,106                    maximum=MAX_IMAGE_SIZE,107                    step=32,108                    value=512,  # Replace with defaults that work for your model109                )110 111                height = gr.Slider(112                    label="Height",113                    minimum=256,114                    maximum=MAX_IMAGE_SIZE,115                    step=32,116                    value=512,  # Replace with defaults that work for your model117                )118 119            with gr.Row():120                guidance_scale = gr.Slider(121                    label="Guidance scale",122                    minimum=0.0,123                    maximum=15.0,124                    step=1.0,125                    value=8.0,  # Replace with defaults that work for your model126                )127 128                lora_scale = gr.Slider(129                    label="LoRA scale",130                    minimum=0.0,131                    maximum=1.0,132                    step=0.1,133                    value=0.8,  # Replace with defaults that work for your model134                )135 136                num_inference_steps = gr.Slider(137                    label="Number of inference steps",138                    minimum=1,139                    maximum=50,140                    step=1,141                    value=30,  # Replace with defaults that work for your model142                )143 144        gr.Examples(examples=examples, inputs=[prompt])145    gr.on(146        triggers=[run_button.click, prompt.submit],147        fn=infer,148        inputs=[149            model_id,150            prompt,151            negative_prompt,152            seed,153            randomize_seed,154            width,155            height,156            guidance_scale,157            lora_scale,158            num_inference_steps,159            use_controlnet,160            control_strength,161            controlnet_mode,162            controlnet_image,163            use_ip_adapter,164            ip_adapter_scale,165            ip_adapter_image,166            delete_background167        ],168        outputs=[result, seed],169    )170 171if __name__ == "__main__":172    demo.launch(share=True, debug=True)173