Update app.py
Browse files
app.py
CHANGED
@@ -1,21 +1,42 @@
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import gradio as gr
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import torch
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# from diffusers import DiffusionPipeline
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from diffusers import StableDiffusionPipeline
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def generate(prompt, negative_prompts, samples, steps,scale, seed):
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pipeline = StableDiffusionPipeline.from_pretrained("jayparmr/icbinp", use_auth_token="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", torch_dtype=torch.float16)
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pipeline.to("cuda")
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generator = torch.Generator(device="cuda").manual_seed(int(seed))
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images_list = pipeline(
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[prompt] * samples,
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negative_prompt= [negative_prompts] * samples,
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num_inference_steps=steps,
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guidance_scale=scale,
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generator=generator,
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)
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images = []
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print(images_list)
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for i, image in enumerate(images_list["images"]):
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@@ -27,45 +48,34 @@ block = gr.Blocks()
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with block:
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with gr.Group():
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with gr.Box():
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with gr.Row().style(
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text = gr.Textbox(
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label="Enter your prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your prompt",
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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negative_text = gr.Textbox(
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label="Enter your negative prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your negative prompt",
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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btn = gr.Button("Generate image").style(
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margin=False,
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rounded=(False, True, True, False),
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)
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# btn = gr.Button("Generate image").style(
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# margin=False,
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# rounded=(False, True, True, False),
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# )
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gallery = gr.Gallery(
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label="Generated images", show_label=False, elem_id="gallery"
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)
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# advanced_button = gr.Button("Advanced options", elem_id="advanced-btn")
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with gr.Row(elem_id="advanced-options"):
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samples = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1)
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steps = gr.Slider(label="Steps", minimum=1, maximum=
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scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
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)
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label="Seed",
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minimum=0,
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maximum=2147483647,
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step=1
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randomize=True,
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)
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text.submit(generate, inputs=[text,negative_text, samples, steps, scale, seed], outputs=gallery)
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btn.click(generate, inputs=[text,negative_text, samples, steps, scale, seed], outputs=gallery)
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# advanced_button.click(
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# None,
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# [],
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# text,
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# )
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# iface = gr.Interface(fn=generate, inputs="text", outputs="image")
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# iface.launch()
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import gradio as gr
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import torch
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# from diffusers import DiffusionPipeline
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from diffusers import StableDiffusionPipeline
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from diffusers.models import AutoencoderKL
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from diffusers import StableDiffusionPipeline
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def generate(prompt, negative_prompts, samples, steps,scale, seed, width, height):
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pipeline = StableDiffusionPipeline.from_pretrained("jayparmr/icbinp", use_auth_token="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", torch_dtype=torch.float16)
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pipeline.to("cuda")
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generator = torch.Generator(device="cuda").manual_seed(int(seed))
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images_list = pipeline(
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[prompt] * samples,
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negative_prompt= [negative_prompts] * samples,
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num_inference_steps=steps,
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guidance_scale=scale,
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generator=generator,
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width=width,
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height=height
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)
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# vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae")
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# pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", vae=vae).to("cuda")
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# images_list = pipe(
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# [prompt] * samples,
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# negative_prompt= [negative_prompts] * samples,
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# num_inference_steps=steps,
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# guidance_scale=scale
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# )
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print("stop gen")
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images = []
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print(images_list)
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for i, image in enumerate(images_list["images"]):
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with block:
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with gr.Group():
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with gr.Box():
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with gr.Row().style(equal_height=True):
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text = gr.Textbox(
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label="Enter your prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your prompt",
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)
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negative_text = gr.Textbox(
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value="",
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label="Enter your negative prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your negative prompt",
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)
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btn = gr.Button("Generate image")
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gallery = gr.Gallery(
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label="Generated images", show_label=False, elem_id="gallery", width = 768
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)
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# gallery = gr.Image(
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# label="Generated images", elem_id="gallery", width = 768, height = 536
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# )
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with gr.Row(elem_id="advanced-options"):
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samples = gr.Slider(label="Images", minimum=1, maximum=4, value=1, step=1)
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steps = gr.Slider(label="Steps", minimum=1, maximum=500, value=100, step=1)
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width = gr.Slider(label="width", minimum=1, maximum=2048, value=512, step=1)
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height = gr.Slider(label="height", minimum=1, maximum=2048, value=512, step=1)
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scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
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)
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label="Seed",
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minimum=0,
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maximum=2147483647,
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step=1
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)
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text.submit(generate, inputs=[text,negative_text, samples, steps, scale, seed, width, height], outputs=gallery)
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btn.click(generate, inputs=[text,negative_text, samples, steps, scale, seed, width, height], outputs=gallery)
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block.launch()
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