Create README.md

README.md

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+```python
+# please install ppdiffusers develop
+import paddle
+import os
+import gradio as gr
+from PIL import Image
+import qrcode
+
+from ppdiffusers import (
+    StableDiffusionPipeline,
+    DiffusionPipeline,
+    ControlNetModel,
+    DDIMScheduler,
+    DPMSolverMultistepScheduler,
+)
+
+from PIL import Image
+
+qrcode_generator = qrcode.QRCode(
+    version=1,
+    error_correction=qrcode.ERROR_CORRECT_H,
+    box_size=10,
+    border=4,
+)
+
+controlnet = ControlNetModel.from_pretrained(
+    "DionTimmer/controlnet_qrcode-control_v1p_sd15", paddle_dtype=paddle.float16
+)
+
+pipe = DiffusionPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5",
+    controlnet=controlnet,
+    safety_checker=None,
+    paddle_dtype=paddle.float16,
+    custom_pipeline="junnyu/stable_diffusion_controlnet_img2img",
+)
+
+pipe.enable_xformers_memory_efficient_attention()
+pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
+
+
+sd_pipe = StableDiffusionPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-2-1",
+    paddle_dtype=paddle.float16,
+    safety_checker=None,
+)
+
+sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
+sd_pipe.enable_xformers_memory_efficient_attention()
+
+
+def resize_for_condition_image(input_image: Image.Image, resolution: int):
+    input_image = input_image.convert("RGB")
+    W, H = input_image.size
+    k = float(resolution) / min(H, W)
+    H *= k
+    W *= k
+    H = int(round(H / 64.0)) * 64
+    W = int(round(W / 64.0)) * 64
+    img = input_image.resize((W, H), resample=Image.LANCZOS)
+    return img
+
+
+def inference(
+    qr_code_content: str,
+    prompt: str,
+    negative_prompt: str,
+    guidance_scale: float = 10.0,
+    controlnet_conditioning_scale: float = 2.0,
+    strength: float = 0.8,
+    seed: int = -1,
+    init_image: Image.Image  = None,
+    qrcode_image: Image.Image = None,
+):
+    if prompt is None or prompt == "":
+        raise gr.Error("Prompt is required")
+
+    if qrcode_image is None and qr_code_content == "":
+        raise gr.Error("QR Code Image or QR Code Content is required")
+
+    generator = paddle.Generator().manual_seed(seed) if seed != -1 else None
+
+    # hack due to gradio examples
+    if init_image is None or init_image.size == (1, 1):
+        print("Generating random image from prompt using Stable Diffusion")
+        # generate image from prompt
+        out = sd_pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            generator=generator,
+            num_inference_steps=25,
+            num_images_per_prompt=1,
+        )  # type: ignore
+
+        init_image = out.images[0]
+    else:
+        print("Using provided init image")
+        init_image = resize_for_condition_image(init_image, 768)
+
+    if qr_code_content != "" or qrcode_image.size == (1, 1):
+        print("Generating QR Code from content")
+        qr = qrcode.QRCode(
+            version=1,
+            error_correction=qrcode.constants.ERROR_CORRECT_H,
+            box_size=10,
+            border=4,
+        )
+        qr.add_data(qr_code_content)
+        qr.make(fit=True)
+
+        qrcode_image = qr.make_image(fill_color="black", back_color="white")
+        qrcode_image = resize_for_condition_image(qrcode_image, 768)
+    else:
+        print("Using QR Code Image")
+        qrcode_image = resize_for_condition_image(qrcode_image, 768)
+
+    out = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        image=init_image,
+        control_image=qrcode_image,  # type: ignore
+        width=768,  # type: ignore
+        height=768,  # type: ignore
+        guidance_scale=float(guidance_scale),
+        controlnet_conditioning_scale=float(controlnet_conditioning_scale),  # type: ignore
+        generator=generator,
+        strength=float(strength),
+        num_inference_steps=40,
+    )
+    return out.images[0]  # type: ignore
+
+
+with gr.Blocks() as blocks:
+    gr.Markdown(
+        """
+# QR Code AI Art Generator
+model: https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15
+<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">
+<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>
+                """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            qr_code_content = gr.Textbox(
+                label="QR Code Content",
+                info="QR Code Content or URL",
+                value="",
+            )
+            prompt = gr.Textbox(
+                label="Prompt",
+                info="Prompt is required. If init image is not provided, then it will be generated from prompt using Stable Diffusion 2.1",
+            )
+            negative_prompt = gr.Textbox(
+                label="Negative Prompt",
+                value="ugly, disfigured, low quality, blurry, nsfw",
+            )
+            with gr.Accordion(label="Init Images (Optional)", open=False):
+                init_image = gr.Image(label="Init Image (Optional)", type="pil")
+
+                qr_code_image = gr.Image(
+                    label="QR Code Image (Optional)",
+                    type="pil",
+                )
+
+            with gr.Accordion(
+                label="Params: The generated QR Code functionality is largely influenced by the parameters detailed below",
+                open=False,
+            ):
+                guidance_scale = gr.Slider(
+                    minimum=0.0,
+                    maximum=50.0,
+                    step=0.01,
+                    value=10.0,
+                    label="Guidance Scale",
+                )
+                controlnet_conditioning_scale = gr.Slider(
+                    minimum=0.0,
+                    maximum=5.0,
+                    step=0.01,
+                    value=2.0,
+                    label="Controlnet Conditioning Scale",
+                )
+                strength = gr.Slider(
+                    minimum=0.0, maximum=1.0, step=0.01, value=0.8, label="Strength"
+                )
+                seed = gr.Slider(
+                    minimum=-1,
+                    maximum=9999999999,
+                    step=1,
+                    value=2313123,
+                    label="Seed",
+                    randomize=True,
+                )
+            with gr.Row():
+                run_btn = gr.Button("Run")
+        with gr.Column():
+            result_image = gr.Image(label="Result Image")
+    run_btn.click(
+        inference,
+        inputs=[
+            qr_code_content,
+            prompt,
+            negative_prompt,
+            guidance_scale,
+            controlnet_conditioning_scale,
+            strength,
+            seed,
+            init_image,
+            qr_code_image,
+        ],
+        outputs=[result_image],
+    )
+
+    gr.Examples(
+        examples=[
+            [
+                "https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator",
+                "billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.",
+                "ugly, disfigured, low quality, blurry, nsfw",
+                13.37,
+                2.81,
+                0.68,
+                2313123,
+                "./examples/hack.png",
+                "./examples/hack.png",
+            ],
+            [
+                "https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator",
+                "beautiful sunset in San Francisco with Golden Gate bridge in the background",
+                "ugly, disfigured, low quality, blurry, nsfw",
+                11.01,
+                2.61,
+                0.66,
+                1423585430,
+                "./examples/hack.png",
+                "./examples/hack.png",
+            ],
+            [
+                "https://huggingface.co",
+                "A flying cat over a jungle",
+                "ugly, disfigured, low quality, blurry, nsfw",
+                13,
+                2.81,
+                0.66,
+                2702246671,
+                "./examples/hack.png",
+                "./examples/hack.png",
+            ],
+            [
+                "",
+                "crisp QR code prominently displayed on a billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.",
+                "ugly, disfigured, low quality, blurry, nsfw",
+                10.0,
+                2.0,
+                0.8,
+                2313123,
+                "./examples/init.jpeg",
+                "./examples/qrcode.png",
+            ],
+        ],
+        fn=inference,
+        inputs=[
+            qr_code_content,
+            prompt,
+            negative_prompt,
+            guidance_scale,
+            controlnet_conditioning_scale,
+            strength,
+            seed,
+            init_image,
+            qr_code_image,
+        ],
+        outputs=[result_image],
+        cache_examples=True,
+    )
+
+blocks.queue(concurrency_count=1, max_size=20)
+blocks.launch(server_name="0.0.0.0", server_port=8235)
+
+```