ccm commited on
Commit
08c0adb
·
1 Parent(s): bb59e94

Update app.py

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Files changed (1) hide show
  1. app.py +15 -4
app.py CHANGED
@@ -31,18 +31,28 @@ shapes = {
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  "rectangle": rectangle,
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  }
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  def randomize(selection):
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  index = random.randint(0, 9)
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  mask = 255*numpy.array(json.loads(shapes[selection]['Defects'][index]))
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  v = numpy.array(json.loads(shapes[selection]['Strain'][index]))
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- print(v)
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  # Get the color map by name:
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  cm = matplotlib.pyplot.get_cmap('RdBu')
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  measure = max(v.max(), -v.min())
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- print(measure)
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  output = (v / measure)
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- print(cm((numpy.multiply(output[:, :, 0], mask)+1.0)/2.0))
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- return mask, cm((numpy.multiply(output[:, :, 0], mask/255.0)+1.0)/2.0), cm((numpy.multiply(output[:, :, 1], mask/255.0)+1.0)/2.0), cm((numpy.multiply(output[:, :, 2], mask/255.0)+1.0)/2.0)
 
 
 
 
 
 
 
 
 
 
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  with gradio.Blocks() as demo:
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  selection = gradio.Dropdown(["circle", "crescent", "ellipse", "peanut", "triangle", "rectangle"], label="Select defect shape")
@@ -56,5 +66,6 @@ with gradio.Blocks() as demo:
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  eyy = gradio.Image(label="ε-yy")
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  with gradio.Column():
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  exy = gradio.Image(label="ε-xy")
 
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  selection.change(fn=randomize, inputs=[selection], outputs=[mask, exx, eyy, exy])
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  demo.launch(debug=True)
 
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  "rectangle": rectangle,
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  }
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+
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+
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  def randomize(selection):
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  index = random.randint(0, 9)
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  mask = 255*numpy.array(json.loads(shapes[selection]['Defects'][index]))
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  v = numpy.array(json.loads(shapes[selection]['Strain'][index]))
 
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  # Get the color map by name:
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  cm = matplotlib.pyplot.get_cmap('RdBu')
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  measure = max(v.max(), -v.min())
 
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  output = (v / measure)
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+
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+ legend = "<h2>Strain</h2><table style=\"width:100%\"><tr>"
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+ for i in range(11):
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+ color = cm(i/10.0)[:3]
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+ value = -measure + i*2*measure/10
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+ print(sum(list(color)))
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+ hex = matplotlib.colors.to_hex(list(color))
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+ text_color = "black" if sum(list(color)) > 2.0 else "white"
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+ legend = legend + f"<td style=\"background-color: {hex}; color: {text_color}\">{value:+.2e}</td>"
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+ legend = legend + "</tr></table>"
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+
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+ return mask, cm((numpy.multiply(output[:, :, 0], mask/255.0)+1.0)/2.0), cm((numpy.multiply(output[:, :, 1], mask/255.0)+1.0)/2.0), cm((numpy.multiply(output[:, :, 2], mask/255.0)+1.0)/2.0), legend
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  with gradio.Blocks() as demo:
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  selection = gradio.Dropdown(["circle", "crescent", "ellipse", "peanut", "triangle", "rectangle"], label="Select defect shape")
 
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  eyy = gradio.Image(label="ε-yy")
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  with gradio.Column():
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  exy = gradio.Image(label="ε-xy")
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+ gradio.HTML(label="", value="")
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  selection.change(fn=randomize, inputs=[selection], outputs=[mask, exx, eyy, exy])
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  demo.launch(debug=True)