Create handler.py

handler.py

@@ -0,0 +1,18 @@
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+model = load_model("my_model.h5")
+emotions = ["Angry", "Disgust", "Fear", "Happy", "Sad", "Surprise", "Neutral"]
+
+def preprocess(image):
+    image = image.convert("L").resize((48, 48))
+    arr = np.array(image) / 255.0
+    arr = np.expand_dims(arr, axis=(0, -1))  # (1, 48, 48, 1)
+    return arr
+
+def predict(image):
+    img = preprocess(image)
+    pred = model.predict(img)
+    label = emotions[np.argmax(pred)]
+    return {"label": label, "score": float(np.max(pred))}