diff --git a/examples/traffic_analysis/README.md b/examples/traffic_analysis/README.md
index c57a1ad5..3c882805 100644
--- a/examples/traffic_analysis/README.md
+++ b/examples/traffic_analysis/README.md
@@ -41,40 +41,40 @@ https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-
 - ultralytics
 
   - `--source_weights_path`: Required. Specifies the path to the YOLO model's weights
-    file, which is essential for the object detection process. This file contains the 
+    file, which is essential for the object detection process. This file contains the
     data that the model uses to identify objects in the video.
 
   - `--source_video_path`: Required. The path to the source video file that will be
     analyzed. This is the input video on which traffic flow analysis will be performed.
-  - `--target_video_path` (optional): The path to save the output video with 
-    annotations. If not specified, the processed video will be displayed in real-time 
+  - `--target_video_path` (optional): The path to save the output video with
+    annotations. If not specified, the processed video will be displayed in real-time
     without being saved.
-  - `--confidence_threshold` (optional): Sets the confidence threshold for the YOLO 
-    model to filter detections. Default is `0.3`. This determines how confident the 
+  - `--confidence_threshold` (optional): Sets the confidence threshold for the YOLO
+    model to filter detections. Default is `0.3`. This determines how confident the
     model should be to recognize an object in the video.
   - `--iou_threshold` (optional): Specifies the IOU (Intersection Over Union) threshold
-    for the model. Default is 0.7. This value is used to manage object detection 
+    for the model. Default is 0.7. This value is used to manage object detection
     accuracy, particularly in distinguishing between different objects.
 
 - inference
 
-  - `--roboflow_api_key` (optional): The API key for Roboflow services. If not provided 
-    directly, the script tries to fetch it from the `ROBOFLOW_API_KEY` environment 
-    variable. Follow [this guide](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key) 
+  - `--roboflow_api_key` (optional): The API key for Roboflow services. If not provided
+    directly, the script tries to fetch it from the `ROBOFLOW_API_KEY` environment
+    variable. Follow [this guide](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key)
     to acquire your `API KEY`.
-  - `--model_id` (optional): Designates the Roboflow model ID to be used. The default 
-    value is `"vehicle-count-in-drone-video/6"`. 
+  - `--model_id` (optional): Designates the Roboflow model ID to be used. The default
+    value is `"vehicle-count-in-drone-video/6"`.
 
   - `--source_video_path`: Required. The path to the source video file that will be
     analyzed. This is the input video on which traffic flow analysis will be performed.
-  - `--target_video_path` (optional): The path to save the output video with 
-    annotations. If not specified, the processed video will be displayed in real-time 
+  - `--target_video_path` (optional): The path to save the output video with
+    annotations. If not specified, the processed video will be displayed in real-time
     without being saved.
-  - `--confidence_threshold` (optional): Sets the confidence threshold for the YOLO 
-    model to filter detections. Default is `0.3`. This determines how confident the 
+  - `--confidence_threshold` (optional): Sets the confidence threshold for the YOLO
+    model to filter detections. Default is `0.3`. This determines how confident the
     model should be to recognize an object in the video.
   - `--iou_threshold` (optional): Specifies the IOU (Intersection Over Union) threshold
-    for the model. Default is 0.7. This value is used to manage object detection 
+    for the model. Default is 0.7. This value is used to manage object detection
     accuracy, particularly in distinguishing between different objects.
 
 ## ⚙️ run
@@ -105,12 +105,12 @@ https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-
 
 This demo integrates two main components, each with its own licensing:
 
-- ultralytics: The object detection model used in this demo, YOLOv8, is distributed 
+- ultralytics: The object detection model used in this demo, YOLOv8, is distributed
   under the [AGPL-3.0 license](https://github.com/ultralytics/ultralytics/blob/main/LICENSE).
   You can find more details about this license here.
 
-- supervision: The analytics code that powers the zone-based analysis in this demo is 
-  based on the Supervision library, which is licensed under the 
+- supervision: The analytics code that powers the zone-based analysis in this demo is
+  based on the Supervision library, which is licensed under the
   [MIT license](https://github.com/roboflow/supervision/blob/develop/LICENSE.md). This
   makes the Supervision part of the code fully open source and freely usable in your
   projects.