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Create app.py
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app.py
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#This code is from: https://huggingface.co/spaces/diffusers/controlnet-3d-pose
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import gradio as gr
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canvas_html = '<pose-maker/>'
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load_js = """
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async () => {
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const url = "https://huggingface.co/datasets/mishig/gradio-components/raw/main/mannequinAll.js"
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fetch(url)
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.then(res => res.text())
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.then(text => {
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const script = document.createElement('script');
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script.type = "module"
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script.src = URL.createObjectURL(new Blob([text], { type: 'application/javascript' }));
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document.head.appendChild(script);
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});
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}
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"""
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get_js_image = """
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async (canvas, prompt) => {
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const poseMakerEl = document.querySelector("pose-maker");
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const imgBase64 = poseMakerEl.captureScreenshotDepthMap();
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return [imgBase64, prompt]
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}
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"""
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js_change_rotation_axis = """
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async (axis) => {
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const poseMakerEl = document.querySelector("pose-maker");
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poseMakerEl.changeRotationAxis(axis);
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}
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"""
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js_pose_template = """
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async (pose) => {
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const poseMakerEl = document.querySelector("pose-maker");
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poseMakerEl.setPose(pose);
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}
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"""
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def generate_images(canvas):
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base64_img = canvas
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image_data = base64.b64decode(base64_img.split(',')[1])
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input_img = Image.open(BytesIO(image_data)).convert(
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'RGB').resize((512, 512))
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input_img = input_img.filter(ImageFilter.GaussianBlur(radius=2))
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input_img = get_canny_filter(input_img)
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return input_image
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def placeholder_fn(axis):
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pass
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with gr.Blocks() as b:
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canvas = gr.HTML(canvas_html, elem_id="canvas_html", visible=True)
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rotation_axis = gr.Radio(choices=["x", "y", "z"], value="x", label="Joint rotation axis")
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pose_template = gr.Radio(choices=["regular", "ballet", "handstand", "split", "kick", "chilling"], value="regular", label="Pose template")
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run_button = gr.Button("Generate")
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rotation_axis.change(fn=placeholder_fn,
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inputs=[rotation_axis],
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outputs=[],
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queue=False,
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_js=js_change_rotation_axis)
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pose_template.change(fn=placeholder_fn,
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inputs=[pose_template],
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outputs=[],
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queue=False,
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_js=js_pose_template)
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run_button.click(fn=generate_images,
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inputs=[canvas],
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outputs=[gr.Image()],
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_js=get_js_image)
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b.launch()
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