traffic analysis example cleanup

examples/traffic_analysis/README.md

@@ -38,6 +38,24 @@ https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-
 
 ## 🛠️ script arguments
 
+- 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 
+    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 
+    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 
+    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 
+    accuracy, particularly in distinguishing between different objects.
+
 - inference
 
   - `--roboflow_api_key` (optional): The API key for Roboflow services. If not provided 
@@ -59,37 +77,8 @@ https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-
     for the model. Default is 0.7. This value is used to manage object detection 
     accuracy, particularly in distinguishing between different objects.
 
-- 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 
-    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 
-    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 
-    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 
-    accuracy, particularly in distinguishing between different objects.
-
 ## ⚙️ run
 
-- inference
-
-  ```bash
-  python inference_example.py \
-  --roboflow_api_key <ROBOFLOW API KEY> \
-  --source_video_path data/traffic_analysis.mov \
-  --confidence_threshold 0.3 \
-  --iou_threshold 0.5 \
-  --target_video_path data/traffic_analysis_result.mov
-  ```
-
 - ultralytics
 
   ```bash
@@ -101,6 +90,17 @@ https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-
   --target_video_path data/traffic_analysis_result.mov
   ```
 
+- inference
+
+  ```bash
+  python inference_example.py \
+  --roboflow_api_key <ROBOFLOW API KEY> \
+  --source_video_path data/traffic_analysis.mov \
+  --confidence_threshold 0.3 \
+  --iou_threshold 0.5 \
+  --target_video_path data/traffic_analysis_result.mov
+  ```
+
 ## © license
 
 This demo integrates two main components, each with its own licensing:

examples/traffic_analysis/inference_example.py

@@ -188,6 +188,12 @@ if __name__ == "__main__":
         help="Roboflow model ID",
         type=str,
     )
+    parser.add_argument(
+        "--roboflow_api_key",
+        default=None,
+        help="Roboflow API KEY",
+        type=str,
+    )
     parser.add_argument(
         "--source_video_path",
         required=True,
@@ -210,12 +216,6 @@ if __name__ == "__main__":
         "--iou_threshold", default=0.7, help="IOU threshold for the model",
         type=float
     )
-    parser.add_argument(
-        "--roboflow_api_key",
-        default=None,
-        help="Roboflow API key",
-        type=str,
-    )
 
     args = parser.parse_args()