Create app.py

app.py

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+import os
+import tensorflow as tf
+import gradio as gr
+import numpy as np
+from PIL import Image
+
+# Define the root directory
+vgg19 = tf.keras.models.load_model("gender_resnet50.h5")
+model = vgg19
+
+def predict_gender(image):
+    image = image.resize((224, 224))
+    image = tf.keras.utils.img_to_array(image)
+    image = image / 255.0
+    pred_arr = np.expand_dims(image, axis=0)
+    result = vgg19.predict(pred_arr)
+    prob = result[0]
+    text_res = "Male" if prob >= 0.5 else "Female"
+    return text_res
+
+# Create the Gradio interface
+interface = gr.Interface(fn=predict_gender, inputs=gr.Image(type="pil"), outputs="text")
+
+# Launch the Gradio interface
+interface.launch(share=True)