Init commit

Signed-off-by: Aisuko <urakiny@gmail.com>

app.py

@@ -0,0 +1,217 @@
+import torch
+import gradio as gr
+from PIL import Image
+import qrcode
+
+
+from diffusers import (
+    StableDiffusionControlNetImg2ImgPipeline,
+    ControlNetModel,
+    DDIMScheduler,
+    DPMSolverMultistepScheduler,
+    DEISMultistepScheduler,
+    HeunDiscreteScheduler,
+    EulerDiscreteScheduler,
+)
+
+controlnet = ControlNetModel.from_pretrained(
+    "DionTimmer/controlnet_qrcode-control_v1p_sd15", torch_dtype=torch.float16
+)
+
+pipe= StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5",
+    controlnet=controlnet,
+    use_safetensors=True,
+    torch_dtype=torch.float16,
+).to("cuda")
+
+
+SAMPLER_MAP={
+    "DPM++ Karras SDE": lambda config: DPMSolverMultistepScheduler.from_config(config, use_karras=True, algorithm_type="sde-dpmsolver++"),
+    "DPM++ Karras": lambda config: DPMSolverMultistepScheduler.from_config(config, use_karras=True),
+    "Heun": lambda config: HeunDiscreteScheduler.from_config(config),
+    "Euler": lambda config: EulerDiscreteScheduler.from_config(config),
+    "DDIM": lambda config: DDIMScheduler.from_config(config),
+    "DEIS": lambda config: DEISMultistepScheduler.from_config(config),
+}
+
+
+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 = None,
+    qrcode_image: Image.Image | None = None,
+    sampler = "DPM++ Karras SDE",
+):
+    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")
+
+    pipe.scheduler = SAMPLER_MAP[sampler](pipe.scheduler.config)
+
+    generator = torch.manual_seed(seed) if seed != -1 else torch.Generator()
+
+    if qr_code_content != "" or qrcode_image.size == (1, 1):
+        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 = qrcode_image.resize((768, 768))
+    else:
+        qrcode_image = qrcode_image.resize((768, 768))
+
+    # hack due to gradio examples
+    init_image = qrcode_image
+
+    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
+
+def inference_ui_demo():
+    return None
+
+# https://www.kaggle.com/code/aisuko/text-to-image-qr-code-generator/notebook
+# image=inference(qr_code_content="https://www.kaggle.com/aisuko",
+#     prompt="A sky view of a colorful lakes and rivers flowing through the mountains",
+#     negative_prompt="ugly, disfigured, low quality, blurry, nsfw",
+#     guidance_scale=7.5,
+#     controlnet_conditioning_scale=1.3,
+#     strength=0.9,
+#     seed=5392011833,
+#     init_image=None,
+#     qrcode_image=None,
+#     sampler="DPM++ Karras SDE")
+
+with gr.Blocks() as blocks:
+    gr.Markdown(
+        """
+        # QR Code Image to Image UI Demo
+
+        This code cannot be runable because of the low resource. So, it is aimed to show the the componnets of the UI only.
+        
+        If you want to run the Code, please go to Kaggle <a href="https://www.kaggle.com/code/aisuko/text-to-image-qr-code-generator/notebook" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
+        """
+    )
+
+    with gr.Row():
+        with gr.Column():
+            qrcode_content=gr.Textbox(
+                label="QR Code Content",
+                info="QR Code Content or URL",
+                value="",
+            )
+            with gr.Accordion(label="QR Code Image (Optional)", open=False):
+                qr_code_image=gr.Image(
+                    label="QR Code Image (Optional). Leave blank to automatically generate QR Code",
+                    type="pil",
+                )
+            
+            prompt=gr.Textbox(
+                label="Prompt",
+                info="Prompt that guides the generation towards",
+            )
+
+            negative_prompt=gr.Textbox(
+                label="Negative Prompt",
+                value="ugly, disfigured, low quality, blurry, nsfw",
+            )
+
+            use_qr_code_as_init_image=gr.Checkbox(
+                label="Use QR code as init image",
+                value=True,
+                interactive=False,
+                info="Whether init image should be QR code. Unclick to pass init image or generate init image with Stable Diffusion 1.5"
+            )
+
+            with gr.Accordion(label="Init Image (Optional)", open=False) as init_image_acc:
+                init_image=gr.Image(
+                    label="Init Image (Optional). Leave blank to generate image with SD 1.5",
+                    type="pil",
+                )
+
+            with gr.Accordion(
+                label="Params: The generated QR Code functionality is largely influenced by the parameters detailed below",
+                open=True,):
+
+                controlnet_conditioning_scale=gr.Slider(
+                    minimum=0.0,
+                    maximum=5.0,
+                    step=0.1,
+                    value=1.1,
+                    label="Controlnet Conditioning Scale",
+                )
+                strength=gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.1,
+                    value=0.9,
+                    label="Strength",
+                )
+                guidance_scale=gr.Slider(
+                    minimum=0.0,
+                    maximum=10.0,
+                    step=0.1,
+                    value=7.5,
+                    label="Guidance Scale",
+                )
+                sampler=gr.Dropdown(
+                    choices=list(SAMPLER_MAP.keys()),
+                    value="DPM++ Karras SDE",
+                    label="Sampler"
+                )
+                seed=gr.Slider(
+                    minimum=-1,
+                    maximum=9999999999,
+                    step=1,
+                    value=2313123,
+                    label="Seed",
+                    randomize=True,
+                )
+            with gr.Row():
+                btn=gr.Button("Run")
+        with gr.Column():
+            result_image=gr.Image(label="Result Image")
+
+    btn.click(
+        inference_ui_demo,
+        inputs=[
+            qrcode_content,
+            prompt,
+            negative_prompt,
+            guidance_scale,
+            controlnet_conditioning_scale,
+            strength,
+            seed,
+            init_image,
+            qr_code_image,
+            sampler,
+        ],
+        outputs=[result_image],
+    )
+
+blocks.queue(concurrency_count=1, max_size=2)
+blocks.launch()

requirements.txt

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+diffusers==0.23.1
+torch==2.1.1
+gradio==4.7.1
+Pillow==10.1.0
+qrcode==7.4.2