Create app.py

app.py

@@ -0,0 +1,15 @@
+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+model = tf.keras.models.load_model("model.h5")
+
+def predict(img):
+    img = img.resize((224, 224))
+    img_array = np.expand_dims(np.array(img) / 255.0, axis=0)
+    preds = model.predict(img_array)
+    labels = ["cool", "neutral", "warm"]
+    return {labels[i]: float(preds[0][i]) for i in range(3)}
+
+gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label()).launch()