Update app.py

app.py

@@ -2,16 +2,16 @@ import gradio as gr
 import tensorflow as tf
 import cv2
 import numpy as np
-from PIL import Image
 
 # Load the model
 model = tf.keras.models.load_model("FER_DATA.keras")
 
 # Define the emotion prediction function
-def predict_emotion(image: Image.Image):
-    image = image.convert("L")  # Convert to grayscale
-    image = image.resize((48, 48))
-    image = np.array(image) / 255.0
+def predict_emotion(image_path):
+    image = cv2.imread(image_path)
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    image = cv2.resize(image, (48, 48))
+    image = image / 255.0
     image = np.expand_dims(image, axis=-1)
     image = np.expand_dims(image, axis=0)
     prediction = model.predict(image)
@@ -22,9 +22,10 @@ def predict_emotion(image: Image.Image):
 # Launch the Gradio interface
 iface = gr.Interface(
     fn=predict_emotion,
-    inputs=gr.Image(type="pil"),
+    inputs=gr.Image(type="filepath"),
     outputs="text",
     title="MoodSync - Emotion Detection"
 )
 
-iface.launch()
+# Make it public
+iface.launch(share=True)