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```python |
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# please install ppdiffusers develop |
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import paddle |
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import os |
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import gradio as gr |
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from PIL import Image |
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import qrcode |
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from ppdiffusers import ( |
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StableDiffusionPipeline, |
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DiffusionPipeline, |
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ControlNetModel, |
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DDIMScheduler, |
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DPMSolverMultistepScheduler, |
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) |
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from PIL import Image |
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qrcode_generator = qrcode.QRCode( |
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version=1, |
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error_correction=qrcode.ERROR_CORRECT_H, |
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box_size=10, |
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border=4, |
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) |
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controlnet = ControlNetModel.from_pretrained( |
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"DionTimmer/controlnet_qrcode-control_v1p_sd15", paddle_dtype=paddle.float16 |
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) |
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pipe = DiffusionPipeline.from_pretrained( |
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"runwayml/stable-diffusion-v1-5", |
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controlnet=controlnet, |
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safety_checker=None, |
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paddle_dtype=paddle.float16, |
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custom_pipeline="junnyu/stable_diffusion_controlnet_img2img", |
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) |
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pipe.enable_xformers_memory_efficient_attention() |
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pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) |
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sd_pipe = StableDiffusionPipeline.from_pretrained( |
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"stabilityai/stable-diffusion-2-1", |
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paddle_dtype=paddle.float16, |
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safety_checker=None, |
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) |
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sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config) |
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sd_pipe.enable_xformers_memory_efficient_attention() |
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def resize_for_condition_image(input_image: Image.Image, resolution: int): |
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input_image = input_image.convert("RGB") |
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W, H = input_image.size |
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k = float(resolution) / min(H, W) |
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H *= k |
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W *= k |
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H = int(round(H / 64.0)) * 64 |
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W = int(round(W / 64.0)) * 64 |
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img = input_image.resize((W, H), resample=Image.LANCZOS) |
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return img |
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def inference( |
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qr_code_content: str, |
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prompt: str, |
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negative_prompt: str, |
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guidance_scale: float = 10.0, |
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controlnet_conditioning_scale: float = 2.0, |
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strength: float = 0.8, |
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seed: int = -1, |
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init_image: Image.Image = None, |
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qrcode_image: Image.Image = None, |
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): |
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if prompt is None or prompt == "": |
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raise gr.Error("Prompt is required") |
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if qrcode_image is None and qr_code_content == "": |
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raise gr.Error("QR Code Image or QR Code Content is required") |
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generator = paddle.Generator().manual_seed(seed) if seed != -1 else None |
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# hack due to gradio examples |
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if init_image is None or init_image.size == (1, 1): |
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print("Generating random image from prompt using Stable Diffusion") |
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# generate image from prompt |
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out = sd_pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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generator=generator, |
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num_inference_steps=25, |
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num_images_per_prompt=1, |
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) # type: ignore |
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init_image = out.images[0] |
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else: |
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print("Using provided init image") |
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init_image = resize_for_condition_image(init_image, 768) |
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if qr_code_content != "" or qrcode_image.size == (1, 1): |
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print("Generating QR Code from content") |
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qr = qrcode.QRCode( |
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version=1, |
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error_correction=qrcode.constants.ERROR_CORRECT_H, |
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box_size=10, |
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border=4, |
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) |
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qr.add_data(qr_code_content) |
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qr.make(fit=True) |
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qrcode_image = qr.make_image(fill_color="black", back_color="white") |
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qrcode_image = resize_for_condition_image(qrcode_image, 768) |
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else: |
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print("Using QR Code Image") |
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qrcode_image = resize_for_condition_image(qrcode_image, 768) |
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out = pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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image=init_image, |
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control_image=qrcode_image, # type: ignore |
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width=768, # type: ignore |
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height=768, # type: ignore |
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guidance_scale=float(guidance_scale), |
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controlnet_conditioning_scale=float(controlnet_conditioning_scale), # type: ignore |
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generator=generator, |
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strength=float(strength), |
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num_inference_steps=40, |
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) |
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return out.images[0] # type: ignore |
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with gr.Blocks() as blocks: |
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gr.Markdown( |
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""" |
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# QR Code AI Art Generator |
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model: https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15 |
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<a href="https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank"> |
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<img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for no queue on your own hardware.</p> |
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""" |
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) |
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with gr.Row(): |
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with gr.Column(): |
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qr_code_content = gr.Textbox( |
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label="QR Code Content", |
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info="QR Code Content or URL", |
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value="", |
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) |
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prompt = gr.Textbox( |
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label="Prompt", |
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info="Prompt is required. If init image is not provided, then it will be generated from prompt using Stable Diffusion 2.1", |
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) |
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negative_prompt = gr.Textbox( |
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label="Negative Prompt", |
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value="ugly, disfigured, low quality, blurry, nsfw", |
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) |
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with gr.Accordion(label="Init Images (Optional)", open=False): |
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init_image = gr.Image(label="Init Image (Optional)", type="pil") |
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qr_code_image = gr.Image( |
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label="QR Code Image (Optional)", |
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type="pil", |
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) |
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with gr.Accordion( |
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label="Params: The generated QR Code functionality is largely influenced by the parameters detailed below", |
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open=False, |
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): |
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guidance_scale = gr.Slider( |
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minimum=0.0, |
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maximum=50.0, |
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step=0.01, |
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value=10.0, |
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label="Guidance Scale", |
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) |
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controlnet_conditioning_scale = gr.Slider( |
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minimum=0.0, |
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maximum=5.0, |
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step=0.01, |
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value=2.0, |
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label="Controlnet Conditioning Scale", |
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) |
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strength = gr.Slider( |
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minimum=0.0, maximum=1.0, step=0.01, value=0.8, label="Strength" |
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) |
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seed = gr.Slider( |
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minimum=-1, |
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maximum=9999999999, |
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step=1, |
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value=2313123, |
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label="Seed", |
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randomize=True, |
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) |
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with gr.Row(): |
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run_btn = gr.Button("Run") |
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with gr.Column(): |
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result_image = gr.Image(label="Result Image") |
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run_btn.click( |
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inference, |
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inputs=[ |
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qr_code_content, |
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prompt, |
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negative_prompt, |
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guidance_scale, |
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controlnet_conditioning_scale, |
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strength, |
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seed, |
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init_image, |
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qr_code_image, |
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], |
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outputs=[result_image], |
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) |
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gr.Examples( |
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examples=[ |
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[ |
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"https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator", |
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"billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.", |
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"ugly, disfigured, low quality, blurry, nsfw", |
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13.37, |
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2.81, |
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0.68, |
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2313123, |
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"./examples/hack.png", |
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"./examples/hack.png", |
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], |
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[ |
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"https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator", |
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"beautiful sunset in San Francisco with Golden Gate bridge in the background", |
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"ugly, disfigured, low quality, blurry, nsfw", |
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11.01, |
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2.61, |
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0.66, |
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1423585430, |
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"./examples/hack.png", |
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"./examples/hack.png", |
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], |
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[ |
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"https://huggingface.co", |
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"A flying cat over a jungle", |
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"ugly, disfigured, low quality, blurry, nsfw", |
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13, |
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2.81, |
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0.66, |
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2702246671, |
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"./examples/hack.png", |
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"./examples/hack.png", |
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], |
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[ |
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"", |
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"crisp QR code prominently displayed on a billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.", |
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"ugly, disfigured, low quality, blurry, nsfw", |
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10.0, |
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2.0, |
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0.8, |
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2313123, |
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"./examples/init.jpeg", |
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"./examples/qrcode.png", |
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], |
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], |
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fn=inference, |
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inputs=[ |
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qr_code_content, |
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prompt, |
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negative_prompt, |
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guidance_scale, |
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controlnet_conditioning_scale, |
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strength, |
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seed, |
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init_image, |
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qr_code_image, |
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], |
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outputs=[result_image], |
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cache_examples=True, |
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) |
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blocks.queue(concurrency_count=1, max_size=20) |
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blocks.launch(server_name="0.0.0.0", server_port=8235) |
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``` |