Update app.py

app.py

@@ -5,6 +5,8 @@ from supervision import Detections
 from PIL import Image
 import numpy as np
 import cv2
+import base64
+import io
 
 # Download and load the model
 model_path = hf_hub_download(repo_id="arnabdhar/YOLOv8-Face-Detection", filename="model.pt")
@@ -29,7 +31,12 @@ def detect_faces(image):
     # Convert back to PIL image
     result_image = Image.fromarray(cv2.cvtColor(image_cv, cv2.COLOR_BGR2RGB))
     
-    return result_image, num_faces
+    # Convert to base64 for API use
+    buffered = io.BytesIO()
+    result_image.save(buffered, format="PNG")
+    img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
+    
+    return result_image, num_faces, img_str
 
 # Gradio Interface
 demo = gr.Interface(
@@ -37,11 +44,12 @@ demo = gr.Interface(
     inputs=gr.Image(type="pil", label="Upload Image"),
     outputs=[
         gr.Image(type="pil", label="Detected Faces"),
-        gr.Number(label="Face Count")
+        gr.Number(label="Face Count"),
+        gr.Textbox(label="Base64 Encoded Image")
     ],
     title="Face Detection with YOLOv8",
     description="Drag and drop an image or click to upload. The model will detect faces using YOLOv8.",
     live=False
 )
 
-demo.launch()
+demo.launch()