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Build error
enable live conditioning (#2)
Browse files- enable live conditioning (219f54ab9f753d37099cb613ad68703220b44db9)
Co-authored-by: Radamés Ajna <radames@users.noreply.huggingface.co>
app.py
CHANGED
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@@ -3,7 +3,9 @@ import torch
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import dlib
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import numpy as np
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import PIL
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# Only used to convert to gray, could do it differently and remove this big dependency
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import cv2
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@@ -35,6 +37,26 @@ pipe = pipe.to("cuda")
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# Generator seed,
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generator = torch.manual_seed(0)
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def get_bounding_box(image):
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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@@ -119,13 +141,18 @@ def get_conditioning(image):
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return spiga_seg
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def generate_images(
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if
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raise gr.Error("Please provide an image")
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try:
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conditioning = get_conditioning(image)
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output = pipe(
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prompt,
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conditioning,
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@@ -139,11 +166,10 @@ def generate_images(image, prompt, image_video=None):
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def toggle(choice):
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if choice == "
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return gr.update(visible=True, value=None), gr.update(visible=False, value=None)
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return gr.update(visible=False, value=None), gr.update(visible=True, value=
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with gr.Blocks() as blocks:
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gr.Markdown("""
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@@ -151,15 +177,17 @@ with gr.Blocks() as blocks:
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[Check out our blog to see how this was done (and train your own controlnet)](https://huggingface.co/blog/train-your-controlnet)
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""")
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with gr.Row():
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with gr.Column():
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label="How would you like to upload your image?")
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outputs=[
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prompt = gr.Textbox(
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label="Enter your prompt",
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max_lines=1,
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@@ -169,8 +197,10 @@ with gr.Blocks() as blocks:
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with gr.Column():
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gallery = gr.Gallery().style(grid=[2], height="auto")
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run_button.click(fn=generate_images,
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inputs=[image_in_img, prompt,
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outputs=[gallery]
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gr.Examples(fn=generate_images,
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examples=[
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["./examples/pedro-512.jpg",
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@@ -178,7 +208,7 @@ with gr.Blocks() as blocks:
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["./examples/image1.jpg",
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"Highly detailed photograph of a scary clown"],
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["./examples/image0.jpg",
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"Highly detailed photograph of
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],
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inputs=[image_in_img, prompt],
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outputs=[gallery],
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import dlib
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import numpy as np
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import PIL
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import base64
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from io import BytesIO
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from PIL import Image
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# Only used to convert to gray, could do it differently and remove this big dependency
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import cv2
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# Generator seed,
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generator = torch.manual_seed(0)
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canvas_html = "<face-canvas id='canvas-root' style='display:flex;max-width: 500px;margin: 0 auto;'></face-canvas>"
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load_js = """
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async () => {
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const url = "https://huggingface.co/datasets/radames/gradio-components/raw/main/face-canvas.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 (image_in_img, prompt, image_file_live_opt, live_conditioning) => {
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const canvasEl = document.getElementById("canvas-root");
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return [image_in_img, prompt, image_file_live_opt, canvasEl._data]
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}
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"""
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def get_bounding_box(image):
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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return spiga_seg
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def generate_images(image_in_img, prompt, image_file_live_opt='file', live_conditioning=None):
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if image_in_img is None and 'image' not in live_conditioning:
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raise gr.Error("Please provide an image")
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if image_file_live_opt == 'file':
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conditioning = get_conditioning(image_in_img)
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elif image_file_live_opt == 'webcam':
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base64_img = live_conditioning['image']
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image_data = base64.b64decode(base64_img.split(',')[1])
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conditioning = Image.open(BytesIO(image_data)).convert('RGB').resize((512,512))
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try:
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output = pipe(
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prompt,
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conditioning,
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def toggle(choice):
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if choice == "file":
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return gr.update(visible=True, value=None), gr.update(visible=False, value=None)
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elif choice == "webcam":
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return gr.update(visible=False, value=None), gr.update(visible=True, value=canvas_html)
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with gr.Blocks() as blocks:
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gr.Markdown("""
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[Check out our blog to see how this was done (and train your own controlnet)](https://huggingface.co/blog/train-your-controlnet)
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""")
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with gr.Row():
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live_conditioning = gr.JSON(value={}, visible=False)
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with gr.Column():
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image_file_live_opt = gr.Radio(["file", "webcam"], value="file",
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label="How would you like to upload your image?")
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image_in_img = gr.Image(source="upload", visible=True, type="pil")
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canvas = gr.HTML(None, elem_id="canvas_html", visible=False)
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image_file_live_opt.change(fn=toggle,
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inputs=[image_file_live_opt],
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outputs=[image_in_img, canvas],
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queue=False)
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prompt = gr.Textbox(
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label="Enter your prompt",
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max_lines=1,
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with gr.Column():
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gallery = gr.Gallery().style(grid=[2], height="auto")
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run_button.click(fn=generate_images,
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inputs=[image_in_img, prompt, image_file_live_opt, live_conditioning],
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outputs=[gallery],
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_js=get_js_image)
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blocks.load(None, None, None, _js=load_js)
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gr.Examples(fn=generate_images,
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examples=[
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["./examples/pedro-512.jpg",
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["./examples/image1.jpg",
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"Highly detailed photograph of a scary clown"],
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["./examples/image0.jpg",
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"Highly detailed photograph of Madonna"],
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],
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inputs=[image_in_img, prompt],
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outputs=[gallery],
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