Create app.py

app.py

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+import datasets
+import random
+import numpy
+import json
+import gradio
+import matplotlib.pyplot # for colormap
+import matplotlib.colors # for color conversion
+
+vr = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['variable_radius.zip'], split='train')
+
+vn = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['variable_number.zip'], split='train')
+
+circle = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['circle/circle_test.zip'], split="train[:10]")
+
+crescent = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['crescent/crescent_test.zip'], split="train[:10]")
+
+peanut = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['peanut/peanut_test.zip'], split="train[:10]")
+
+ellipse = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['ellipse/ellipse_test.zip'], split="train[:10]")
+
+triangle = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['triangle/triangle_test.zip'], split="train[:10]")
+
+rectangle = datasets.load_dataset("cmudrc/porous-microstructure-strain-fields", data_files=['rectangle/rectangle_test.zip'], split="train[:10]")
+
+shapes = {
+    "circle": circle,
+    "crescent": crescent,
+    "ellipse": ellipse,
+    "peanut": peanut,
+    "triangle": triangle,
+    "rectangle": rectangle,
+}
+
+def randomize(selection):
+    index = random.randint(0, 9)
+    mask = 255*numpy.array(json.loads(shapes[selection]['Defects'][index]))
+    v = numpy.array(json.loads(shapes[selection]['Strain'][index]))
+    print(v)
+    # Get the color map by name:
+    cm = matplotlib.pyplot.get_cmap('RdBu')
+    measure = max(v.max(), -v.min())
+    print(measure)
+    output = (v / measure)
+    print(cm((numpy.multiply(output[:, :, 0], mask)+1.0)/2.0))
+    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)
+
+with gradio.Blocks() as demo:
+    selection = gradio.Dropdown(["circle", "crescent", "ellipse", "peanut", "triangle", "rectangle"], label="Select defect shape")
+    with gradio.Row():
+        with gradio.Column(label="Defects"):
+            mask = gradio.Image()
+        with gradio.Column(label="ε-xx"):
+            exx = gradio.Image()
+    with gradio.Row():
+        with gradio.Column():
+            eyy = gradio.Image(label="ε-yy")
+        with gradio.Column():
+            exy = gradio.Image(label="ε-xy")
+    selection.change(fn=randomize, inputs=[selection], outputs=[mask, exx, eyy, exy])
+demo.launch(debug=True)