Update app.py

app.py

@@ -58,11 +58,21 @@ def predict(frame):
 
     return frameClone, probs
 
-inp = gr.components.Image(sources="webcam", label="Your face")
+# Define Gradio input and output components
+image_input = gr.components.Image(type='file', label="Upload Image or Video")
+image_output = gr.components.Image(label="Predicted Emotion")
+label_output = gr.components.Label(num_top_classes=2, label="Top 2 Probabilities")
+
+inp = [
+        gr.components.Image(sources="webcam", label="Your face"),
+        gr.components.Image(type='file', label="Upload Image or Video")
+      ]
 out = [
-    gr.components.Image(label="Predicted Emotion"),
-    gr.components.Label(num_top_classes=2, label="Top 2 Probabilities")
-]
+        gr.components.Image(label="Predicted Emotion"),
+        gr.components.Label(num_top_classes=2, label="Top 2 Probabilities")
+        ]
+
+
 title = "Facial Emotion Recognition"
 description = "How well can this model predict your emotions? Take a picture with your webcam, and it will guess if" \
               " you are: happy, sad, angry, disgusted, scared, surprised, or neutral."
@@ -71,3 +81,10 @@ thumbnail = "https://raw.githubusercontent.com/gradio-app/hub-emotion-recognitio
 # gr.Interface(predict, inp, out, capture_session=True, title=title, thumbnail=thumbnail,
 #              description=description).launch(inbrowser=True)
 gr.Interface(fn=predict, inputs=inp, outputs=out, title=title, thumbnail=thumbnail).launch()
+
+
+
+
+# # Launch Gradio interface
+# gr.Interface(fn=predict, inputs=image_input, outputs=[image_output, label_output],
+#              title="Facial Emotion Recognition", description="How well can this model predict your emotions?").launch()