Werli commited on
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06900b2
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1 Parent(s): 37d5f7f

Update app.py

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Files changed (1) hide show
  1. app.py +5 -3
app.py CHANGED
@@ -70,12 +70,14 @@ else:
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  TITLE = "Multi-Tagger"
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  DESCRIPTION = """
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  Multi-Tagger is a powerful and versatile application that integrates two cutting-edge models: Waifu Diffusion and Florence 2. This app is designed to provide comprehensive image analysis and captioning capabilities, making it a valuable tool for AI artists, researchers, and enthusiasts.
 
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  Features:
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  - Supports batch processing of multiple images.
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  - Tags images with multiple categories: general tags, character tags, and ratings.
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  - Displays categorized tags in a structured format.
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  - Includes a separate tab for image captioning using Florence 2. This model supports CUDA, MPS or CPU if one of them is available.
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  - Supports various captioning tasks (e.g., Caption, Detailed Caption, Object Detection), as well it can display output text and images for tasks that generate visual outputs.
 
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  Example image by [me.](https://huggingface.co/Werli)
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  """
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  colormap = ['blue','orange','green','purple','brown','pink','gray','olive','cyan','red',
@@ -213,6 +215,7 @@ class Llama3Reorganize:
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  loadModel: bool = False,
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  ):
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  """Initializes the Llama model.
 
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  Args:
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  repoId: LLAMA model repo.
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  device: Device to use for computation (cpu, cuda, ipu, xpu, mkldnn, opengl, opencl,
@@ -1020,7 +1023,6 @@ with gr.Blocks(title=TITLE, css=css, theme="Werli/Multi-Tagger", fill_width=True
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  [
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  download_file,
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  sorted_general_strings,
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- categorized_output,
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  categorized,
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  rating,
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  character_res,
@@ -1035,7 +1037,7 @@ with gr.Blocks(title=TITLE, css=css, theme="Werli/Multi-Tagger", fill_width=True
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  upload_button.upload(extend_gallery, inputs=[gallery, upload_button], outputs=gallery)
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  # Event to update the selected image when an image is clicked in the gallery
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  selected_image = gr.Textbox(label="Selected Image", visible=False)
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- gallery.select(get_selection_from_gallery, inputs=[gallery, tag_results], outputs=[selected_image, sorted_general_strings, categorized, categorized_output, rating, character_res, general_res, unclassified])
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  # Event to remove a selected image from the gallery
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  remove_button.click(remove_image_from_gallery, inputs=[gallery, selected_image], outputs=gallery)
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  submit.click(
@@ -1053,7 +1055,7 @@ with gr.Blocks(title=TITLE, css=css, theme="Werli/Multi-Tagger", fill_width=True
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  additional_tags_append,
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  tag_results,
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  ],
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- outputs=[download_file, sorted_general_strings, categorized, categorized_output, rating, character_res, general_res, unclassified, tag_results,],
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  )
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  gr.Examples(
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  [["images/1girl.png", VIT_LARGE_MODEL_DSV3_REPO, 0.35, False, 0.85, False]],
 
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  TITLE = "Multi-Tagger"
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  DESCRIPTION = """
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  Multi-Tagger is a powerful and versatile application that integrates two cutting-edge models: Waifu Diffusion and Florence 2. This app is designed to provide comprehensive image analysis and captioning capabilities, making it a valuable tool for AI artists, researchers, and enthusiasts.
73
+
74
  Features:
75
  - Supports batch processing of multiple images.
76
  - Tags images with multiple categories: general tags, character tags, and ratings.
77
  - Displays categorized tags in a structured format.
78
  - Includes a separate tab for image captioning using Florence 2. This model supports CUDA, MPS or CPU if one of them is available.
79
  - Supports various captioning tasks (e.g., Caption, Detailed Caption, Object Detection), as well it can display output text and images for tasks that generate visual outputs.
80
+
81
  Example image by [me.](https://huggingface.co/Werli)
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  """
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  colormap = ['blue','orange','green','purple','brown','pink','gray','olive','cyan','red',
 
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  loadModel: bool = False,
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  ):
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  """Initializes the Llama model.
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+
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  Args:
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  repoId: LLAMA model repo.
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  device: Device to use for computation (cpu, cuda, ipu, xpu, mkldnn, opengl, opencl,
 
1023
  [
1024
  download_file,
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  sorted_general_strings,
 
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  categorized,
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  rating,
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  character_res,
 
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  upload_button.upload(extend_gallery, inputs=[gallery, upload_button], outputs=gallery)
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  # Event to update the selected image when an image is clicked in the gallery
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  selected_image = gr.Textbox(label="Selected Image", visible=False)
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+ gallery.select(get_selection_from_gallery, inputs=[gallery, tag_results], outputs=[selected_image, sorted_general_strings, categorized, rating, character_res, general_res, unclassified])
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  # Event to remove a selected image from the gallery
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  remove_button.click(remove_image_from_gallery, inputs=[gallery, selected_image], outputs=gallery)
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  submit.click(
 
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  additional_tags_append,
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  tag_results,
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  ],
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+ outputs=[download_file, sorted_general_strings, categorized, rating, character_res, general_res, unclassified, tag_results, categorized_output,],
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  )
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  gr.Examples(
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  [["images/1girl.png", VIT_LARGE_MODEL_DSV3_REPO, 0.35, False, 0.85, False]],