kadirnar commited on
Commit
ba8c2bf
1 Parent(s): 1d96534
Files changed (2) hide show
  1. app.py +3 -3
  2. demo.py +2 -2
app.py CHANGED
@@ -1,5 +1,5 @@
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  import gradio as gr
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- from demo import SegAutoMaskPredictor
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  def image_app():
@@ -47,7 +47,7 @@ def image_app():
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  output_image = gr.Image()
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  seg_automask_image_predict.click(
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- fn=SegAutoMaskPredictor().image_predict,
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  inputs=[
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  seg_automask_image_file,
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  seg_automask_image_model_type,
@@ -103,7 +103,7 @@ def video_app():
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  output_video = gr.Video()
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  seg_automask_video_predict.click(
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- fn=SegAutoMaskPredictor().video_predict,
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  inputs=[
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  seg_automask_video_file,
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  seg_automask_video_model_type,
 
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  import gradio as gr
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+ from demo import automask_image_app, automask_video_app
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4
 
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  def image_app():
 
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  output_image = gr.Image()
48
 
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  seg_automask_image_predict.click(
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+ fn=automask_image_app,
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  inputs=[
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  seg_automask_image_file,
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  seg_automask_image_model_type,
 
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  output_video = gr.Video()
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  seg_automask_video_predict.click(
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+ fn=automask_video_app,
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  inputs=[
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  seg_automask_video_file,
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  seg_automask_video_model_type,
demo.py CHANGED
@@ -3,7 +3,7 @@ from metaseg import SegAutoMaskPredictor, SegManualMaskPredictor, SahiAutoSegmen
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  # For image
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- def image_app(image_path, model_type, points_per_side, points_per_batch, min_area):
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  SegAutoMaskPredictor().image_predict(
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  source=image_path,
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  model_type=model_type, # vit_l, vit_h, vit_b
@@ -20,7 +20,7 @@ def image_app(image_path, model_type, points_per_side, points_per_batch, min_are
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  # For video
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- def video_app(video_path, model_type, points_per_side, points_per_batch, min_area):
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  SegAutoMaskPredictor().video_predict(
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  source=video_path,
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  model_type=model_type, # vit_l, vit_h, vit_b
 
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  # For image
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+ def automask_image_app(image_path, model_type, points_per_side, points_per_batch, min_area):
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  SegAutoMaskPredictor().image_predict(
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  source=image_path,
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  model_type=model_type, # vit_l, vit_h, vit_b
 
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  # For video
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+ def automask_video_app(video_path, model_type, points_per_side, points_per_batch, min_area):
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  SegAutoMaskPredictor().video_predict(
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  source=video_path,
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  model_type=model_type, # vit_l, vit_h, vit_b