rrighart commited on
Commit
0ba3470
1 Parent(s): 1515748
Files changed (2) hide show
  1. app.py +21 -32
  2. slider.py +14 -0
app.py CHANGED
@@ -1,8 +1,9 @@
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-
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  import gradio as gr
 
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  import torch
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- #############
 
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  def yolov7_inference(
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  image: gr.Image = None,
@@ -16,39 +17,27 @@ def yolov7_inference(
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  results = model([image], size=640)
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  return results.render()[0]
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- inputs = [
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- gr.Image(type="filepath", label="Input"),
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- gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.05, label="Confidence Threshold", interactive=True),
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- ]
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-
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- outputs = [
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- gr.Image(type="filepath"),
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-
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- ]
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-
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- css = ".output_image {height: 40rem !important; width: 100% !important;}"
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-
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- demo = gr.Interface(
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- fn=yolov7_inference,
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- inputs=inputs,
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- outputs=outputs,
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- title="The detection of jar lid defects using Yolov7",
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- description = """
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- This application is detecting damaged jar lids. Type of damages include deformations, holes or scratches. The object detection notebook can be found at <a href="https://www.kaggle.com/rrighart">Kaggle</a>
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- Contact: Ruthger Righart
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- Email: rrighart@googlemail.com
 
 
 
 
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- Web: <a href="https://www.rrighart.com">www.rrighart.com</a>
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- """,
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- article = "<p style='text-align: center'><a href='https://www.rrighart.com' target='_blank'>Webpage</a></p> <p style='text-align: center'><a href='https://www.kaggle.com/code/rrighart/detection-of-product-defects-using-yolov7' target='_blank'>Kaggle</a></p>",
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- examples = [['example1.JPG'], ['example2.JPG'], ['example3.JPG']],
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- #examples = [['example1.JPG', 0.50], ['example2.JPG', 0.50], ['example3.JPG', 0.50]],
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- css=css,
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- cache_examples=True,
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  )
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- demo.queue().launch(server_name="0.0.0.0", server_port=7860, debug=False, inline=True)
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-
 
 
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  import gradio as gr
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+ import os
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  import torch
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+ def update_value(val):
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+ return f'Value is set to {val}'
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  def yolov7_inference(
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  image: gr.Image = None,
 
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  results = model([image], size=640)
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  return results.render()[0]
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+ demo = gr.Blocks()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ with demo:
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+ dd = gr.Interface(
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+ yolov7_inference,
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+ gr.Image(type="pil"),
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+ "image",
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+ title="The detection of jar lid defects using Yolov7",
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+ examples=[
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+ os.path.join(os.path.dirname(__file__), "example1.JPG"),
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+ os.path.join(os.path.dirname(__file__), "example2.JPG"),
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+ os.path.join(os.path.dirname(__file__), "example3.JPG"),
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+ ],
 
 
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  )
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+ md = gr.Markdown("Confidence Threshold")
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+ conf_threshold = gr.Slider(minimum=0, maximum=1, step=0.1, label='Value')
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+ #inp = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.05, label="Value"),
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+ #inp.change(fn=yolov7_inference, inputs=inp, outputs=md)
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+ conf_threshold.change(fn=update_value, inputs=conf_threshold, outputs=md)
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+ demo.launch()
 
slider.py ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import gradio as gr
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+
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+ def update_value(val):
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+ return f'Value is set to {val}'
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+
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+ demo = gr.Blocks()
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+
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+ with demo:
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+ inp = gr.Slider(0, 100, label='Value')
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+ md = gr.Markdown('Select a value')
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+
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+ inp.change(fn=update_value, inputs=inp, outputs=md)
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+
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+ demo.launch()