Missed a couple README updates with last commit

README.md

@@ -59,6 +59,11 @@ Supervision was designed to be model agnostic. Just plug in any classification,
 5
 ```
 
+<details>
+<summary>
+Example with Infernce
+</summary>
+
 Running with [Inference](https://github.com/roboflow/inference) can improve speed but requires a [Roboflow API key](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key).
 
 ```python
@@ -72,9 +77,12 @@ Running with [Inference](https://github.com/roboflow/inference) can improve spee
 >>> detections = sv.Detections.from_inference(result)
 
 >>> len(detections)
-5
+>>> 5
+
 ```
 
+</details>
+
 ### annotators
 
 Supervision offers a wide range of highly customizable [annotators](https://supervision.roboflow.com/annotators/), allowing you to compose the perfect visualization for your use case.

examples/count_people_in_zone/inference_example.py

@@ -86,7 +86,7 @@ def detect(
             for filtering.
     """
     results = model.infer(frame)[0]
-    detections = sv.Detections.from_roboflow(results)
+    detections = sv.Detections.from_inference(results)
     filter_by_class = detections.class_id == 0
     filter_by_confidence = detections.confidence > confidence_threshold
     return detections[filter_by_class & filter_by_confidence]