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| import io | |
| import hvplot.pandas | |
| import numpy as np | |
| import panel as pn | |
| import param | |
| import PIL | |
| import requests | |
| import torch | |
| from diffusers import StableDiffusionInstructPix2PixPipeline | |
| pn.extension(template="bootstrap") | |
| pn.state.template.main_max_width = "690px" | |
| pn.state.template.accent_base_color = "#F08080" | |
| pn.state.template.header_background = "#F08080" | |
| # Set up device | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| # Model | |
| model_id = "timbrooks/instruct-pix2pix" | |
| if device == "cuda": | |
| pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained( | |
| model_id, torch_dtype=torch.float16 | |
| ) | |
| else: | |
| pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained( | |
| model_id | |
| ) | |
| pipe = pipe.to(device) | |
| def new_image(prompt, image, img_guidance, guidance, steps): | |
| edit = pipe( | |
| prompt, | |
| image=image, | |
| image_guidance_scale=img_guidance, | |
| guidance_scale=guidance, | |
| num_inference_steps=steps, | |
| ).images[0] | |
| return edit | |
| # Panel widgets | |
| file_input = pn.widgets.FileInput(width=600) | |
| prompt = pn.widgets.TextInput( | |
| value="", placeholder="Enter image editing instruction here...", width=600 | |
| ) | |
| img_guidance = pn.widgets.DiscreteSlider( | |
| name="Image guidance scale", options=list(np.arange(1, 10.5, 0.5)), value=1.5 | |
| ) | |
| guidance = pn.widgets.DiscreteSlider( | |
| name="Guidance scale", options=list(np.arange(1, 10.5, 0.5)), value=7 | |
| ) | |
| steps = pn.widgets.IntSlider(name="Inference Steps", start=1, end=100, step=1, value=20) | |
| run_button = pn.widgets.Button(name="Run!", width=600) | |
| # define global variables to keep track of things | |
| convos = [] # store all panel objects in a list | |
| image = None | |
| filename = None | |
| def normalize_image(value, width): | |
| """ | |
| normalize image to RBG channels and to the same size | |
| """ | |
| b = io.BytesIO(value) | |
| image = PIL.Image.open(b).convert("RGB") | |
| aspect = image.size[1] / image.size[0] | |
| height = int(aspect * width) | |
| return image.resize((width, height), PIL.Image.ANTIALIAS) | |
| def get_conversations(_, img, img_guidance, guidance, steps, width=600): | |
| """ | |
| Get all the conversations in a Panel object | |
| """ | |
| global image, filename | |
| prompt_text = prompt.value | |
| prompt.value = "" | |
| # if the filename changes, open the image again | |
| if filename != file_input.filename: | |
| filename = file_input.filename | |
| image = normalize_image(file_input.value, width) | |
| convos.clear() | |
| if prompt_text: | |
| # generate new image | |
| image = new_image(prompt_text, image, img_guidance, guidance, steps) | |
| convos.append(pn.Row("\U0001F60A", pn.pane.Markdown(prompt_text, width=600))) | |
| convos.append(pn.Row("\U0001F916", image)) | |
| return pn.Column(*convos) | |
| # bind widgets to functions | |
| interactive_conversation = pn.bind( | |
| get_conversations, run_button, file_input, img_guidance, guidance, steps | |
| ) | |
| interactive_upload = pn.bind(pn.panel, file_input, width=600) | |
| # layout | |
| pn.Column( | |
| pn.pane.Markdown("## \U0001F60A Upload an image file and start editing!"), | |
| pn.Column(file_input, pn.panel(interactive_upload)), | |
| pn.panel(interactive_conversation, loading_indicator=True), | |
| prompt, | |
| pn.Row(run_button), | |
| pn.Card(img_guidance, guidance, steps, width=600, header="Advance settings"), | |
| ).servable(title="Stablel Diffusion InstructPix2pix Image Editing Chatbot") | |