app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from keras.models import load_model,Sequential
+model = load_model("./Model_2.h5")
+class_names = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips']
+
+def predict_image(img):
+  img_4d=img.reshape(-1,331,331,3)
+  prediction=model.predict(img_4d)[0]
+  return {class_names[i]: float(prediction[i]) for i in range(5)}
+
+image = gr.inputs.Image(shape=(331,331))
+label = gr.outputs.Label(num_top_classes=5)
+iface = gr.Interface(fn=predict_image, 
+             inputs=image, 
+             outputs=label, 
+             interpretation='default', 
+             title = 'Flower Recognition App', 
+             description= 'Get probability for input image among 5 classes')
+iface.launch()