Final Project

app.py

@@ -1,7 +1,21 @@
-import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+import tensorflow
+from tensorflow import keras
+from keras.models import load_model
+model1 = load_model("inception.h5")
+
+img_width, img_height = 180, 180
+class_names = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips']
+num_classes = len(class_names)
+
+def predict_image(img):
+    img_4d = img.reshape(-1, img_width, img_height, 3)      # 4D coz model trained on multiple 3Ds
+    prediction = model1.predict(img_4d)[0]
+    return {class_names[i]: float(prediction[i]) for i in range(num_classes)}
+
+
+import gradio as gr
+image = gr.inputs.Image(shape=(img_height, img_width))
+label = gr.outputs.Label(num_top_classes=num_classes)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+gr.Interface(fn=predict_image, inputs=image, outputs=label, title="Flower Classification using InceptionV3", interpretation='default').launch(debug='True', share='True')

inception.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d75cab7598d7b20a3c1e8c2a53b5b87dd60fc71c2ebbdb7f8fda7767ac46981e
+size 94556992