feat: implement demo layout

app.py

@@ -0,0 +1,40 @@
+from transformers import pipeline
+import torch
+from PIL import Image
+import io
+import gradio as gr
+
+accident_detector = pipeline(model="hilmantm/detr-traffic-accident-detection")
+
+import gradio as gr
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Hello!!!
+    Welcome to the live demonstration of our traffic accident detection application! Experience cutting-edge technology designed to enhance road safety and provide real-time accident alerts. Let's explore the capabilities of our innovative solution together.
+    """)
+
+    gr.Markdown("## Detect Accident from Image")
+    with gr.Row():
+      with gr.Column():
+        input_image = gr.Image(label="Input image", type="pil")
+        inp = gr.Textbox(label="Image URL", placeholder="You have image from URL? Drop here")
+      with gr.Column():
+        output_image = gr.Image(label="Output image with predicted accident", type="pil")
+
+    gr.Button(value="Detect Accident")
+
+
+    gr.Markdown("## Detect Accident from Video")
+    with gr.Row():
+      with gr.Column():
+        inp = gr.Textbox(label="Youtube URL", placeholder="You should upload video to youtube and drop the link here")
+      with gr.Column():
+        output_image = gr.Image(label="Output image with predicted accident", type="pil")
+
+    gr.Button(value="Detect Accident")
+    
+
+if __name__ == "__main__":
+    demo.launch(debug=True)