Added samples

.gitattributes

@@ -14,6 +14,11 @@
 *.npy filter=lfs diff=lfs merge=lfs -text
 *.npz filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -te
 *.ot filter=lfs diff=lfs merge=lfs -text
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 *.pb filter=lfs diff=lfs merge=lfs -text

app.py

@@ -50,15 +50,40 @@ def detect_expression(input_image):
     output = visualize(image, dets, fer_res)
     return cv.cvtColor(output, cv.COLOR_BGR2RGB)
 
-# Gradio UI
-demo = gr.Interface(
-    fn=detect_expression,
-    inputs=gr.Image(type="numpy", label="Upload Image"),
-    outputs=gr.Image(type="numpy", label="Facial Expression Result"),
-    title="Facial Expression Recognition (FER) with OpenCV DNN",
-    description="Detects faces and recognizes facial expressions using YuNet + MobileFaceNet ONNX models.",
-    allow_flagging="never"
-)
+# Gradio Interface
+with gr.Blocks(css='''.example * {
+    font-style: italic;
+    font-size: 18px !important;
+    color: #0ea5e9 !important;
+    }''') as demo:
+
+    gr.Markdown("### Facial Expression Recognition (FER) with OpenCV DNN")
+    gr.Markdown("Detects faces and recognizes facial expressions using YuNet + MobileFaceNet ONNX models.")
+
+    with gr.Row():
+        input_image = gr.Image(type="numpy", label="Upload Image")
+        output_image = gr.Image(type="numpy", label="Facial Expression Result")
+
+    # Clear output when new image is uploaded
+    input_image.change(fn=lambda: (None), outputs=output_image)
+
+    with gr.Row():
+        submit_btn = gr.Button("Submit", variant="primary")
+        clear_btn = gr.Button("Clear")
+
+    submit_btn.click(fn=detect_expression, inputs=input_image, outputs=output_image)
+    clear_btn.click(fn=lambda:(None, None), outputs=[input_image, output_image])
+
+    gr.Markdown("Click on any example to try it.", elem_classes=["example"])
+
+    gr.Examples(
+        examples=[
+            ["examples/lena.jpg"],
+            ["examples/gray_face.png"]
+        ],
+        inputs=input_image
+    )
+
 
 if __name__ == "__main__":
     demo.launch()