Fix yolov11 object detection inference visualization

notebooks/train-yolo11-object-detection-on-custom-dataset.ipynb

@@ -930,18 +930,19 @@
         "import IPython\n",
         "import inference\n",
         "\n",
-        "model = inference.get_model(dataset.url + \"/\" + dataset.version, userdata.get('ROBOFLOW_API_KEY'))\n",
+        "model_id = project.id.split(\"/\")[1] + \"/\" + dataset.version\n",
+        "model = inference.get_model(model_id, userdata.get('ROBOFLOW_API_KEY'))\n",
         "\n",
-        "# choose random test set image\n",
+        "# Choose random test set image\n",
         "test_set_loc = dataset.location + \"/test/images/\"\n",
         "random_test_image = random.choice(os.listdir(test_set_loc))\n",
         "print(\"running inference on \" + random_test_image)\n",
         "\n",
-        "pred = model.predict(test_set_loc + random_test_image, confidence=40, overlap=30).json()\n",
-        "detections = sv.Detections.from_inference(pred)\n",
-        "\n",
         "image = cv2.imread(test_set_loc + random_test_image)\n",
         "\n",
+        "results = model.infer(image, confidence=0.4, overlap=30)[0]\n",
+        "detections = sv.Detections.from_inference(results)\n",
+        "\n",
         "box_annotator = sv.BoxAnnotator()\n",
         "label_annotator = sv.LabelAnnotator()\n",
         "\n",