Update app.py

app.py

@@ -5,6 +5,7 @@ import os
 from sahi.slicing import slice_image
 import numpy as np
 import cv2
+from PIL import Image, ImageDraw
 
 # Inisialisasi Roboflow (for model path)
 rf = Roboflow(api_key="Otg64Ra6wNOgDyjuhMYU")
@@ -95,8 +96,27 @@ def detect_objects(image):
     # Aplikasikan NMS untuk menghapus duplikat deteksi
     postprocessed_predictions = apply_nms(all_predictions, iou_threshold=0.5)
 
-    # Annotate gambar dengan hasil prediksi
-    annotated_image = model.annotate_image_with_predictions(temp_file_path, postprocessed_predictions)
+    # Annotate gambar dengan hasil prediksi menggunakan OpenCV
+    img = cv2.imread(temp_file_path)
+    for prediction in postprocessed_predictions:
+        class_name = prediction['class']
+        bbox = prediction['bbox']
+        confidence = prediction['confidence']
+        
+        # Unpack the bounding box coordinates
+        x, y, w, h = map(int, bbox)
+
+        # Draw the bounding box and label on the image
+        color = (0, 255, 0)  # Green color for the box
+        thickness = 2
+        cv2.rectangle(img, (x, y), (x + w, y + h), color, thickness)
+
+        label = f"{class_name}: {confidence:.2f}"
+        cv2.putText(img, label, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, thickness)
+
+    # Convert the image from BGR to RGB for PIL compatibility
+    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    annotated_image = Image.fromarray(img_rgb)
 
     # Simpan gambar hasil annotasi
     output_image_path = "/tmp/prediction.jpg"