Create app.py

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+import tensorflow.keras as keras
+from tensorflow.keras.models import load_model
+ 
+model = load_model('Fusen_dataset.h5')
+classnames = ['Normal', 'Kizu', 'Yogore']
+
+def predict_image(img):
+  img_4d=img.reshape(-1,224, 224,3)
+  prediction=model.predict(img_4d)[0]
+  return {classnames[i]: float(prediction[i]) for i in range(3)}
+                
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label(num_top_classes=3)
+
+gr.Interface(fn=predict_image, inputs=image,  title="ふせん外観検査",
+    description="ふせんの写真を撮って「送信」ボタンを押して下さい！汚れや破れを検出します。",outputs=label,enable_queue=True,interpretation='default').launch()