Duplicate from patrickvonplaten/instruct-pix2pix

Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
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+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
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+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.wasm filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+title: Instruct Pix2Pix Web-UI
+emoji: 🎯
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: 3.15.0
+app_file: app.py
+pinned: true
+license: mit
+duplicated_from: patrickvonplaten/instruct-pix2pix
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler
+import gradio as gr
+import torch
+from PIL import Image
+import time
+import psutil
+import random
+# from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
+
+
+start_time = time.time()
+current_steps = 15
+
+pipe = DiffusionPipeline.from_pretrained("timbrooks/instruct-pix2pix", torch_dtype=torch.float16, safety_checker=None)
+pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+
+device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶"
+
+if torch.cuda.is_available():
+    pipe = pipe.to("cuda")
+
+
+def error_str(error, title="Error"):
+    return (
+        f"""#### {title}
+            {error}"""
+        if error
+        else ""
+    )
+
+
+def inference(
+    prompt,
+    text_guidance_scale,
+    image_guidance_scale,
+    image,
+    steps,
+    neg_prompt="",
+    width=512,
+    height=512,
+    seed=0,
+):
+    print(psutil.virtual_memory())  # print memory usage
+
+    if seed == 0:
+        seed = random.randint(0, 2147483647)
+
+    generator = torch.Generator("cuda").manual_seed(seed)
+
+    try:
+        ratio = min(height / image.height, width / image.width)
+        image = image.resize((int(image.width * ratio), int(image.height * ratio)), Image.LANCZOS)
+
+        result = pipe(
+            prompt,
+            negative_prompt=neg_prompt,
+            image=image,
+            num_inference_steps=int(steps),
+            image_guidance_scale=image_guidance_scale,
+            guidance_scale=text_guidance_scale,
+            generator=generator,
+        )
+
+        # return replace_nsfw_images(result)
+        return result.images, f"Done. Seed: {seed}"
+    except Exception as e:
+        return None, error_str(e)
+
+
+def replace_nsfw_images(results):
+    for i in range(len(results.images)):
+        if results.nsfw_content_detected[i]:
+            results.images[i] = Image.open("nsfw.png")
+    return results.images
+
+
+with gr.Blocks(css="style.css") as demo:
+    gr.HTML(
+        f"""
+            <div class="finetuned-diffusion-div">
+              <div>
+                <h1>Instruct-Pix2Pix Diffusion</h1>
+              </div>
+              <p>
+               Demo for Instruct-Pix2Pix Diffusion: https://github.com/timothybrooks/instruct-pix2pix
+              </p>
+              <p>
+               Running on <b>{device}</b>
+              </p>
+              <p>You can also duplicate this space and upgrade to gpu by going to settings:<br>
+              <a style="display:inline-block" href="https://huggingface.co/spaces/patrickvonplaten/finetuned_diffusion?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></p>
+            </div>
+        """
+    )
+    with gr.Row():
+        with gr.Column(scale=55):
+            with gr.Group():
+                with gr.Box(visible=False) as custom_model_group:
+                    gr.HTML(
+                        "<div><font size='2'>Custom models have to be downloaded first, so give it some time.</font></div>"
+                    )
+
+                with gr.Row():
+                    prompt = gr.Textbox(
+                        label="Prompt",
+                        show_label=False,
+                        max_lines=2,
+                        placeholder="Enter prompt.",
+                    ).style(container=False)
+                    generate = gr.Button(value="Generate").style(
+                        rounded=(False, True, True, False)
+                    )
+
+                # image_out = gr.Image(height=512)
+                gallery = gr.Gallery(
+                    label="Generated images", show_label=False, elem_id="gallery"
+                ).style(grid=[2], height="auto")
+
+            state_info = gr.Textbox(label="State", show_label=False, max_lines=2).style(
+                container=False
+            )
+            error_output = gr.Markdown()
+
+        with gr.Column(scale=45):
+            with gr.Tab("Options"):
+                with gr.Group():
+                    neg_prompt = gr.Textbox(
+                        label="Negative prompt",
+                        placeholder="What to exclude from the image",
+                    )
+
+                    n_images = gr.Slider(
+                        label="Images", value=1, minimum=1, maximum=4, step=1
+                    )
+
+                    with gr.Row():
+                        steps = gr.Slider(
+                            label="Steps",
+                            value=current_steps,
+                            minimum=2,
+                            maximum=75,
+                            step=1,
+                        )
+
+                    with gr.Row():
+                        width = gr.Slider(
+                            label="Width", value=512, minimum=64, maximum=1024, step=8
+                        )
+                        height = gr.Slider(
+                            label="Height", value=512, minimum=64, maximum=1024, step=8
+                        )
+
+                    seed = gr.Slider(
+                        0, 2147483647, label="Seed (0 = random)", value=0, step=1
+                    )
+
+                with gr.Group():
+                    image = gr.Image(
+                        label="Image", height=256, tool="editor", type="pil"
+                    )
+                    text_guidance_scale = gr.Slider(
+                        label="Text Guidance Scale", minimum=1.0, value=5.5, maximum=15, step=0.1
+                    )
+                    image_guidance_scale = gr.Slider(
+                        label="Image Guidance Scale",
+                        minimum=1.0,
+                        maximum=15,
+                        step=0.1,
+                        value=1.5,
+                    )
+
+    inputs = [
+        prompt,
+        text_guidance_scale,
+        image_guidance_scale,
+        image,
+        steps,
+        neg_prompt,
+        width,
+        height,
+        seed,
+    ]
+    outputs = [gallery, error_output]
+    prompt.submit(inference, inputs=inputs, outputs=outputs)
+    generate.click(inference, inputs=inputs, outputs=outputs)
+
+    ex = gr.Examples(
+        [
+            ["turn him into a cyborg", 7.5, 1.2, "./statue.jpg", 20]
+        ],
+        inputs=[prompt, text_guidance_scale, image_guidance_scale, image, steps],
+        outputs=outputs,
+        fn=inference,
+        cache_examples=True,
+    )
+
+print(f"Space built in {time.time() - start_time:.2f} seconds")
+
+demo.queue(concurrency_count=1)
+demo.launch()

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+torchvision==0.13.1+cu113
+git+https://github.com/huggingface/diffusers.git
+git+https://github.com/huggingface/transformers
+scipy
+ftfy
+psutil
+accelerate
+safetensors

style.css

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+.finetuned-diffusion-div div{
+    display:inline-flex;
+    align-items:center;
+    gap:.8rem;
+    font-size:1.75rem
+}
+.finetuned-diffusion-div div h1{
+    font-weight:900;
+    margin-bottom:7px
+}
+.finetuned-diffusion-div p{
+    margin-bottom:10px;
+    font-size:94%
+}
+a{
+    text-decoration:underline
+}
+.tabs{
+    margin-top:0;
+    margin-bottom:0
+}
+#gallery{
+    min-height:20rem
+}

utils.py

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+def is_google_colab():
+    try:
+        import google.colab
+        return True
+    except:
+        return False