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49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
import gradio as gr
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import numpy as np
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import time
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import os
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from PIL import Image
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import requests
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from io import BytesIO
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def create_gif(images):
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pil_images = []
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for image in images:
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if isinstance(image, str):
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response = requests.get(image)
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image = Image.open(BytesIO(response.content))
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else:
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image = Image.fromarray((image * 255).astype(np.uint8))
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pil_images.append(image)
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fp_out = os.path.join(os.path.dirname(__file__), "image.gif")
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img = pil_images.pop(0)
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img.save(fp=fp_out, format='GIF', append_images=pil_images,
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save_all=True, duration=400, loop=0)
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return fp_out
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def fake_diffusion(steps):
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images = []
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for _ in range(steps):
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time.sleep(1)
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image = np.random.random((600, 600, 3))
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images.append(image)
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yield image, gr.Image.update(visible=False)
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time.sleep(1)
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image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg"
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images.append(image)
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gif_path = create_gif(images)
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yield image, gr.Image.update(value=gif_path, visible=True)
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demo = gr.Interface(fake_diffusion,
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inputs=gr.Slider(1, 10, 3),
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outputs=["image", gr.Image(label="All Images", visible=False)])
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demo.queue()
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if __name__ == "__main__":
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demo.launch()
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