seawolf2357 commited on
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  1. app.py +81 -2
app.py CHANGED
@@ -1,5 +1,12 @@
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  from googletrans import Translator
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  import gradio as gr
 
 
 
 
 
 
 
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  translator = Translator()
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@@ -8,10 +15,82 @@ def translation(text):
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  res=translation.text
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  return res
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-
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  inp_text = gr.inputs.Textbox(label='Input')
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  output = gr.outputs.Textbox(label='Output')
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- gr.Interface(fn=translation, inputs=inp_text, outputs=output, title='Translation',theme='peach').launch(enable_queue=True)
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  from googletrans import Translator
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  import gradio as gr
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+ import torch
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+ from torch import autocast
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+ from diffusers import StableDiffusionPipeline
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+ from datasets import load_dataset
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+ from PIL import Image
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+ import re
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+ import os
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  translator = Translator()
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  res=translation.text
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  return res
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  inp_text = gr.inputs.Textbox(label='Input')
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  output = gr.outputs.Textbox(label='Output')
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+ gr.Interface(fn=translation, inputs=inp_text, outputs=output, title='Translation',theme='peach')
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+
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+
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+ auth_token = os.getenv("auth_token")
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+ model_id = "CompVis/stable-diffusion-v1-4"
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+ device = "cpu"
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+ pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=auth_token, revision="fp16", torch_dtype=torch.float16)
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+ pipe = pipe.to(device)
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+
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+ def infer(prompt, samples, steps, scale, seed):
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+ generator = torch.Generator(device=device).manual_seed(seed)
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+ images_list = pipe(
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+ [prompt] * 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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+ safe_image = Image.open(r"unsafe.png")
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+ for i, image in enumerate(images_list["sample"]):
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+ if(images_list["nsfw_content_detected"][i]):
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+ images.append(safe_image)
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+ else:
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+ images.append(image)
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+ return images
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+
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+
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+
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+ block = gr.Blocks()
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+
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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(mobile_collapse=False, 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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+ ).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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+ gallery = gr.Gallery(
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+ label="Generated images", show_label=False, elem_id="gallery"
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+ ).style(grid=[2], height="auto")
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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=4, step=1)
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+ steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, 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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+ seed = gr.Slider(
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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(infer, inputs=[text, samples, steps, scale, seed], outputs=gallery)
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+ btn.click(infer, inputs=[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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+
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+ block.launch()
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