Update app.py

app.py

@@ -53,8 +53,8 @@ def predict_image(image):
     # Draw boxes and collect prediction data
     for result in results:
         boxes = result[:4]
-        prob = result[4]
-        prob0 = round(prob, 2)
+        probs = result[4]
+        #prob0 = round(prob, 2)
         classes = int(result[5])
         boxes = boxes/img_size               
 
@@ -65,15 +65,15 @@ def predict_image(image):
             boxes[3] * im_height
         ])
 
-        if prob > 0.2:
+        if probs > 0.2:
             cv2.rectangle(temp_image, (x1, y1), (x2, y2), (0, 0, 255), 2)
-            label_text = f"{classes} {prob0}"
-            cv2.putText(temp_image, label_text, (x1, y1), 0, 0.5, (0, 255, 0), 2)
+            #label_text = f"{classes} {prob0}"
+            cv2.putText(temp_image, str(classes)+" "+str(round(float(probs),2)), (x1, y1), 0, 0.5, (0, 255, 0), 2)
 
             # Store prediction info in a JSON-compatible format
             predictions.append({
                 "class": label_to_class_text[classes],
-                "probability": round(float(prob), 2),
+                "probability": round(float(probs), 3),
                 "coordinates": {
                     "xmin": int(x1),
                     "ymin": int(y1),