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Update app.py
Browse files
app.py
CHANGED
@@ -34,15 +34,10 @@ MAX_IMAGE_SIZE = 1024
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def generate_image(uploaded_image):
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# Open the uploaded image
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image = Image.open(uploaded_image)
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# Run the image through the Stable Diffusion pipeline
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with torch.no_grad():
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output = pipe(image, guidance_scale=7.5)["sample"][0]
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return output
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def infer(
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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@@ -50,7 +45,7 @@ def infer(base_img, prompt, negative_prompt, seed, randomize_seed, width, height
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generator = torch.Generator().manual_seed(seed)
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image = pipe(
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image =
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prompt = prompt,
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negative_prompt = negative_prompt,
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guidance_scale = guidance_scale,
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@@ -90,8 +85,9 @@ with gr.Blocks(css=css) as demo:
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with gr.Row():
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with gr.Row():
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prompt = gr.Text(
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@@ -168,7 +164,7 @@ with gr.Blocks(css=css) as demo:
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run_button.click(
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fn = infer,
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inputs = [
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outputs = [result]
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)
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def generate_image(uploaded_image):
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# Open the uploaded image
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image = Image.open(uploaded_image)
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return output
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def infer(image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, strength):
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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generator = torch.Generator().manual_seed(seed)
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image = pipe(
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image = image,
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prompt = prompt,
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negative_prompt = negative_prompt,
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guidance_scale = guidance_scale,
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with gr.Row():
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image = gr.Interface(fn=generate_image, inputs=gr.Image(), "image")
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gr.Interface(sepia, gr.Image(), "image")
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with gr.Row():
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prompt = gr.Text(
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run_button.click(
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fn = infer,
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inputs = [image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, strength],
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outputs = [result]
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)
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