Delete diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_app.py

diffusion_webui/diffusion_models/controlnet/controlnet_inpaint/controlnet_inpaint_app.py

@@ -1,206 +0,0 @@
-import cv2
-import gradio as gr
-import numpy as np
-import torch
-from diffusers import (
-    ControlNetModel,
-    StableDiffusionControlNetPipeline,
-)
-from PIL import Image
-
-from diffusion_webui.utils.model_list import (
-    controlnet_canny_model_list,
-    stable_model_list,
-)
-from diffusion_webui.utils.scheduler_list import (
-    SCHEDULER_LIST,
-    get_scheduler_list,
-)
-
-# https://github.com/mikonvergence/ControlNetInpaint
-
-class StableDiffusionControlInpaintNetCannyGenerator:
-    def __init__(self):
-        self.pipe = None
-
-    def controlnet_canny_inpaint(
-        self,
-        image_path: str,
-    ):
-        image = image_path["image"].convert("RGB").resize((512, 512))
-        image = np.array(image)
-
-        image = cv2.Canny(image, 100, 200)
-        image = image[:, :, None]
-        image = np.concatenate([image, image, image], axis=2)
-        image = Image.fromarray(image)
-
-        return image
-
-    def load_model(self, stable_model_path, controlnet_model_path, scheduler):
-        if self.pipe is None:
-            controlnet = ControlNetModel.from_pretrained(
-                controlnet_model_path, torch_dtype=torch.float16
-            )
-            self.pipe = StableDiffusionControlNetPipeline.from_pretrained(
-                pretrained_model_name_or_path=stable_model_path,
-                controlnet=controlnet,
-                safety_checker=None,
-                torch_dtype=torch.float16,
-            )
-
-        self.pipe = get_scheduler_list(pipe=self.pipe, scheduler=scheduler)
-        self.pipe.to("cuda")
-        self.pipe.enable_xformers_memory_efficient_attention()
-
-        return self.pipe
-
-    def generate_image(
-        self,
-        image_path: str,
-        stable_model_path: str,
-        controlnet_model_path: str,
-        prompt: str,
-        negative_prompt: str,
-        num_images_per_prompt: int,
-        guidance_scale: int,
-        num_inference_step: int,
-        scheduler: str,
-        seed_generator: int,
-    ):
-
-        image = self.controlnet_canny_inpaint(image_path=image_path)
-
-        pipe = self.load_model(
-            stable_model_path=stable_model_path,
-            controlnet_model_path=controlnet_model_path,
-            scheduler=scheduler,
-        )
-
-        if seed_generator == 0:
-            random_seed = torch.randint(0, 1000000, (1,))
-            generator = torch.manual_seed(random_seed)
-        else:
-            generator = torch.manual_seed(seed_generator)
-
-        output = pipe(
-            prompt=prompt,
-            image=image,
-            negative_prompt=negative_prompt,
-            num_images_per_prompt=num_images_per_prompt,
-            num_inference_steps=num_inference_step,
-            guidance_scale=guidance_scale,
-            generator=generator,
-        ).images
-
-        return output
-
-    def app():
-        with gr.Blocks():
-            with gr.Row():
-                with gr.Column():
-                    controlnet_canny_inpaint_image_file = gr.Image(
-                    source="upload",
-                    tool="sketch",
-                    elem_id="image_upload",
-                    type="pil",
-                    label="Upload",
-                )
-
-                    controlnet_canny_inpaint_prompt = gr.Textbox(
-                        lines=1, placeholder="Prompt", show_label=False
-                    )
-
-                    controlnet_canny_inpaint_negative_prompt = gr.Textbox(
-                        lines=1,
-                        show_label=False,
-                        placeholder="Negative Prompt",
-                    )
-                    with gr.Row():
-                        with gr.Column():
-                            controlnet_canny_inpaint_stable_model_id = (
-                                gr.Dropdown(
-                                    choices=stable_model_list,
-                                    value=stable_model_list[0],
-                                    label="Stable Model Id",
-                                )
-                            )
-
-                            controlnet_canny_inpaint_guidance_scale = gr.Slider(
-                                minimum=0.1,
-                                maximum=15,
-                                step=0.1,
-                                value=7.5,
-                                label="Guidance Scale",
-                            )
-
-                            controlnet_canny_inpaint_num_inference_step = (
-                                gr.Slider(
-                                    minimum=1,
-                                    maximum=100,
-                                    step=1,
-                                    value=50,
-                                    label="Num Inference Step",
-                                )
-                            )
-                            controlnet_canny_inpaint_num_images_per_prompt = (
-                                gr.Slider(
-                                    minimum=1,
-                                    maximum=10,
-                                    step=1,
-                                    value=1,
-                                    label="Number Of Images",
-                                )
-                            )
-                        with gr.Row():
-                            with gr.Column():
-                                controlnet_canny_inpaint_model_id = gr.Dropdown(
-                                    choices=controlnet_canny_model_list,
-                                    value=controlnet_canny_model_list[0],
-                                    label="Controlnet Model Id",
-                                )
-                                controlnet_canny_inpaint_scheduler = (
-                                    gr.Dropdown(
-                                        choices=SCHEDULER_LIST,
-                                        value=SCHEDULER_LIST[0],
-                                        label="Scheduler",
-                                    )
-                                )
-
-                                controlnet_canny_inpaint_seed_generator = (
-                                    gr.Slider(
-                                        minimum=0,
-                                        maximum=1000000,
-                                        step=1,
-                                        value=0,
-                                        label="Seed Generator",
-                                    )
-                                )
-
-                    controlnet_canny_inpaint_predict = gr.Button(
-                        value="Generator"
-                    )
-
-                with gr.Column():
-                    output_image = gr.Gallery(
-                        label="Generated images",
-                        show_label=False,
-                        elem_id="gallery",
-                    ).style(grid=(1, 2))
-
-            controlnet_canny_inpaint_predict.click(
-                fn=StableDiffusionControlInpaintNetCannyGenerator().generate_image,
-                inputs=[
-                    controlnet_canny_inpaint_image_file,
-                    controlnet_canny_inpaint_stable_model_id,
-                    controlnet_canny_inpaint_model_id,
-                    controlnet_canny_inpaint_prompt,
-                    controlnet_canny_inpaint_negative_prompt,
-                    controlnet_canny_inpaint_num_images_per_prompt,
-                    controlnet_canny_inpaint_guidance_scale,
-                    controlnet_canny_inpaint_num_inference_step,
-                    controlnet_canny_inpaint_scheduler,
-                    controlnet_canny_inpaint_seed_generator,
-                ],
-                outputs=[output_image],
-            )