Update app.py

app.py

@@ -5,6 +5,7 @@ import tempfile
 import os
 import requests
 from sahi.predict import get_sliced_prediction  # SAHI slicing inference
+import supervision as sv  # For annotating images with results
 
 # Muat variabel lingkungan dari file .env
 load_dotenv()
@@ -30,10 +31,10 @@ def detect_objects(image):
         result = get_sliced_prediction(
             temp_file_path,
             model,
-            slice_height=256,  # Adjust as needed
-            slice_width=256,   # Adjust as needed
-            overlap_height_ratio=0.2,  # Adjust as needed
-            overlap_width_ratio=0.2   # Adjust as needed
+            slice_height=256,  # Adjust slice height as needed
+            slice_width=256,   # Adjust slice width as needed
+            overlap_height_ratio=0.2,  # Adjust overlap height ratio as needed
+            overlap_width_ratio=0.2   # Adjust overlap width ratio as needed
         )
 
         # Menghitung jumlah objek per kelas
@@ -56,6 +57,19 @@ def detect_objects(image):
         result.export_visuals(export_dir="/tmp/")  # Export visuals for display
         output_image_path = "/tmp/prediction_visual.png"  # Assuming the visual output is saved here
 
+        # Annotating the image with the detections (optional)
+        label_annotator = sv.LabelAnnotator()
+        box_annotator = sv.BoxAnnotator()
+
+        annotated_image = box_annotator.annotate(
+            scene=image.copy(), detections=result.object_prediction_list)
+        
+        annotated_image = label_annotator.annotate(
+            scene=annotated_image, detections=result.object_prediction_list)
+
+        # Save the annotated image
+        annotated_image.save(output_image_path)
+
     except requests.exceptions.HTTPError as http_err:
         # Menangani kesalahan HTTP
         result_text = f"HTTP error occurred: {http_err}"