Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import keras
+import tensorflow
+from keras.models import model_from_json
+import numpy as np
+
+
+def predict_age_gender(image):
+    json_file = open('final_mobilenet.json', 'r')
+    loaded_file_json = json_file.read()
+    json_file.close()
+
+    model = model_from_json(loaded_file_json)
+    model.load_weights('final_mobilenet.h5')
+
+
+#     img_pixels = image.img_to_array(image)
+#     img = tf.reshape(image, shape=(-1, 128, 128, 3))
+    img_pixels = np.expand_dims(image, axis=0)
+    img_pixels = image.astype('float')
+    img_pixels = img_pixels.reshape((1, 128, 128, 3))
+    img_pixels /= 255
+
+    predict = model.predict(img_pixels)
+    gender_predict = predict[0]
+    age_predict = predict[1]
+    return {'Gender': ['Fmale' if gender_predict > 0.5 else 'Male'], 'Age': age_predict[0][0]}
+
+
+iface = gr.Interface(predict_age_gender, gr.Image(), gr.Text())
+iface.launch(share=True)