app.py

app.py

@@ -0,0 +1,18 @@
+import gradio as gr
+import numpy as np
+import cv2
+from tensorflow.keras.models import load_model
+
+model = load_model("emotion_model.h5")
+emotion_labels = ['Angry', 'Disgust', 'Fear', 'Happy', 'Neutral', 'Sad', 'Surprise']
+
+def detect_emotion(image):
+    gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    face = cv2.resize(gray, (48, 48))
+    face = face.reshape(1, 48, 48, 1) / 255.0
+    prediction = model.predict(face)
+    emotion = emotion_labels[np.argmax(prediction)]
+    return emotion
+
+iface = gr.Interface(fn=detect_emotion, inputs=gr.Image(type="numpy", shape=(224, 224)), outputs="text")
+iface.launch()