Update app.py
Browse files
app.py
CHANGED
@@ -8,7 +8,7 @@ lora_path = "OedoSoldier/detail-tweaker-lora"
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vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse").to("cuda")
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@spaces.GPU
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def generate_image(prompt, negative_prompt, num_inference_steps=30, guidance_scale=7.0,model="Real6.0"):
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if model == "Real5.0":
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model_id = "SG161222/Realistic_Vision_V5.0_noVAE"
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@@ -35,17 +35,18 @@ def generate_image(prompt, negative_prompt, num_inference_steps=30, guidance_sca
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# Generate the image
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prompt = prompt,
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negative_prompt = negative_prompt,
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cross_attention_kwargs = {"scale":1},
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num_inference_steps = num_inference_steps,
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guidance_scale = guidance_scale,
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width = 720,
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height = 720
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).images[0]
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return
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title = """<h1 align="center">ProFaker</h1>"""
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# Create the Gradio interface
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@@ -72,6 +73,13 @@ with gr.Blocks() as demo:
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value="Real6.0",
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label="Model",
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)
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steps_slider = gr.Slider(
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minimum=1,
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maximum=100,
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@@ -88,13 +96,19 @@ with gr.Blocks() as demo:
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)
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with gr.Column():
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# Output component
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# Connect the interface to the generation function
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generate_button.click(
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fn=generate_image,
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inputs=[prompt, negative_prompt, steps_slider, guidance_slider, model],
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outputs=image_output
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)
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vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse").to("cuda")
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@spaces.GPU
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def generate_image(prompt, negative_prompt, num_inference_steps=30, guidance_scale=7.0,model="Real6.0",num_images_slider=1):
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if model == "Real5.0":
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model_id = "SG161222/Realistic_Vision_V5.0_noVAE"
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# Generate the image
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result = pipe(
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prompt = prompt,
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negative_prompt = negative_prompt,
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cross_attention_kwargs = {"scale":1},
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num_inference_steps = num_inference_steps,
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guidance_scale = guidance_scale,
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width = 720,
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height = 720,
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num_images_per_prompt=num_images
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).images[0]
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return result.images
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title = """<h1 align="center">ProFaker</h1>"""
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# Create the Gradio interface
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value="Real6.0",
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label="Model",
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)
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num_images_slider = gr.Slider( # New slider for number of images
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minimum=1,
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maximum=4,
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value=1,
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step=1,
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label="Number of Images to Generate"
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)
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steps_slider = gr.Slider(
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minimum=1,
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maximum=100,
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)
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with gr.Column():
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# Output component
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gallery = gr.Gallery(
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label="Generated Images",
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show_label=True,
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elem_id="gallery",
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columns=2,
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rows=2
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)
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# Connect the interface to the generation function
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generate_button.click(
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fn=generate_image,
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inputs=[prompt, negative_prompt, steps_slider, guidance_slider, model, num_images_slider],
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outputs=image_output
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)
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