diego2554 commited on
Commit
df195bf
1 Parent(s): 9a02640

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +31 -38
app.py CHANGED
@@ -1,11 +1,8 @@
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- ## Modified from Akhaliq Hugging Face Demo
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- ## https://huggingface.co/akhaliq
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-
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  import gradio as gr
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  import os
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  import cv2
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- def inference(file, mask, model, alpha, segmentation_strength):
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  im = cv2.imread(file, cv2.IMREAD_COLOR)
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  cv2.imwrite(os.path.join("input.png"), im)
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@@ -19,56 +16,52 @@ def inference(file, mask, model, alpha, segmentation_strength):
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  input = i.read()
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  output = remove(
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  input,
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- session=new_session(model),
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- only_mask=(True if mask == "Mask only" else False),
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- alpha=alpha,
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- segmentation_strength=segmentation_strength
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  )
 
 
 
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  o.write(output)
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  return os.path.join("output.png")
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-
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- title = "RemBG_Super"
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- description = "Gradio demo for RemBG. erase the background of any image, To use it, simply upload your image and adjust the sliders and choose a eraser plugin from the U2net library."
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  article = "<p style='text-align: center;'><a href='https://github.com/danielgatis/rembg' target='_blank'>Github Repo</a></p>"
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  gr.Interface(
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  inference,
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  [
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  gr.inputs.Image(type="filepath", label="Input"),
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- gr.Row([
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- gr.inputs.Radio(
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- [
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- "Default",
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- "Mask only"
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- ],
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- type="value",
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- default="Default",
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- label="Choices"
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- ),
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- gr.inputs.Dropdown([
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- "u2net",
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- "u2netp",
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- "u2net_human_seg",
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- "u2net_cloth_seg",
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- "silueta",
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- "isnet-general-use",
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- "isnet-anime",
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- "sam",
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  ],
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  type="value",
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  default="isnet-general-use",
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  label="Models"
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- ),
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- ]),
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- gr.Row([
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- gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Alpha (Transparency)"),
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- gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.5, label="Segmentation Strength"),
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- ]),
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  ],
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  gr.outputs.Image(type="filepath", label="Output"),
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  title=title,
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  description=description,
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  article=article,
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- examples=[["lion.png", "Default", "u2net", 0.5, 0.5], ["girl.jpg", "Default", "u2net", 0.5, 0.5], ["anime-girl.jpg", "Default", "isnet-anime", 0.5, 0.5]],
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  enable_queue=True
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- ).launch()
 
 
 
 
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  import gradio as gr
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  import os
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  import cv2
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+ def inference(file, mask, model):
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  im = cv2.imread(file, cv2.IMREAD_COLOR)
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  cv2.imwrite(os.path.join("input.png"), im)
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  input = i.read()
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  output = remove(
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  input,
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+ session = new_session(model),
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+ only_mask = (True if mask == "Mask only" else False)
 
 
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  )
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+
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+
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+
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  o.write(output)
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  return os.path.join("output.png")
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+
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+ title = "RemBG"
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+ description = "Gradio demo for RemBG. To use it, simply upload your image and wait. Read more at the link below."
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  article = "<p style='text-align: center;'><a href='https://github.com/danielgatis/rembg' target='_blank'>Github Repo</a></p>"
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+
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  gr.Interface(
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  inference,
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  [
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  gr.inputs.Image(type="filepath", label="Input"),
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+ gr.inputs.Radio(
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+ [
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+ "Default",
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+ "Mask only"
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+ ],
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+ type="value",
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+ default="Default",
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+ label="Choices"
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+ ),
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+ gr.inputs.Dropdown([
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+ "u2net",
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+ "u2netp",
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+ "u2net_human_seg",
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+ "u2net_cloth_seg",
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+ "silueta",
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+ "isnet-general-use",
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+ "isnet-anime",
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+ "sam",
 
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  ],
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  type="value",
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  default="isnet-general-use",
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  label="Models"
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+ ),
 
 
 
 
 
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  ],
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  gr.outputs.Image(type="filepath", label="Output"),
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  title=title,
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  description=description,
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  article=article,
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+ examples=[["lion.png", "Default", "u2net"], ["girl.jpg", "Default", "u2net"], ["anime-girl.jpg", "Default", "isnet-anime"]],
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  enable_queue=True
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+ ).launch()