WIP

app.py

@@ -1,30 +1,37 @@
+import os
 import gradio as gr
+import requests
+import base64
+from io import BytesIO
+from PIL import Image
 
+def search_face(image):
+    return image, 1
 
-def process_image_stream(question):
-    return "This is a test response"
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # Search Your Face Online For Free
+    ## For more detailed information, please check on our website.<br/>
+    ## [FaceOnLive: On-premises ID Verification, Biometric Authentication Solution Provider](https://faceonlive.com)    
+    <br>
+    
+    ## For premium support or partnership inquiries, contact us.
+    """
+    )
+    with gr.Row():
+        with gr.Column(scale=1):
+            image = gr.Image(type='filepath', height=480)
+            search_face_button = gr.Button("Search Face")
+        with gr.Column(scale=2):
+            output = gr.Gallery(label="Found Images", columns=[4], object_fit="contain", height="auto")
+            countwg = gr.Number(label="Count")
+    
+    gr.Examples(['examples/1.jpg', 'examples/2.jpg'], inputs=image, cache_examples=True, cache_mode='lazy', fn=search_face, outputs=[output, countwg])
 
-# Updated Gradio interface
-demo = gr.Blocks(theme="soft")
+    search_face_button.click(search_face, inputs=image, outputs=[output, countwg], api_name=False)
+
+    gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FFaceOnLive%2FFace-Search-Online"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FFaceOnLive%2FFace-Search-Online&labelColor=%23ff8a65&countColor=%2337d67a&style=flat&labelStyle=upper" /></a>')
 
-with demo:
-    with gr.Column():  # Changed from Row to Column for better mobile layout
-        gr.Markdown("# Nexa Omni Vision")
-        
-        question = gr.Textbox(
-            label="Question", 
-            placeholder="Ask a question about the image...",
-            value="Describe this image",
-            elem_classes="input-box"  # Added class for CSS targeting
-        )
-        
-        response = gr.Textbox(
-            label="Response", 
-            interactive=False,
-            elem_classes="output-box"  # Added class for CSS targeting
-        )
-    
-    question.submit(fn=process_image_stream, inputs=question, outputs=response)
 
-if __name__ == "__main__":
-    demo.queue().launch(server_name="0.0.0.0", server_port=7860)
+demo.queue(api_open=False).launch(server_name="0.0.0.0", server_port=7860, show_api=False)