Upload app.py

app.py

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+import gradio as gr
+import keras
+from keras.models import load_model
+from tensorflow_addons.layers import InstanceNormalization
+import matplotlib.pyplot as plt
+import numpy as np
+
+model=load_model('g_model_AtoB_002160.h5')
+
+def show_preds_image(image_path):
+    image = plt.imread(image_path)
+    image=np.expand_dims(image,axis=0)
+    outputs = model.predict(image)
+    image=np.squeeze(outputs,axis=0)
+    return image
+ 
+inputs_image = [
+    gr.components.Image(type="filepath", label="Input Image"),
+]
+outputs_image = [
+    gr.components.Image(type="numpy", label="Output Image"),
+]
+interface_image = gr.Interface(
+    fn=show_preds_image,
+    inputs=inputs_image,
+    outputs=outputs_image,
+    title="Pothole detector",
+    examples=path,
+    cache_examples=False,
+)
+
+gr.TabbedInterface(
+    [interface_image],
+    tab_names=['Image inference']
+).queue().launch()
+