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+---
+comments: true
+description: Distance Calculation Using Ultralytics YOLOv8
+keywords: Ultralytics, YOLOv8, Object Detection, Distance Calculation, Object Tracking, Notebook, IPython Kernel, CLI, Python SDK
+---
+
+# Distance Calculation using Ultralytics YOLOv8 🚀
+
+## What is Distance Calculation?
+
+Measuring the gap between two objects is known as distance calculation within a specified space. In the case of [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics), the bounding box centroid is employed to calculate the distance for bounding boxes highlighted by the user.
+
+<p align="center">
+  <br>
+  <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LE8am1QoVn4"
+    title="YouTube video player" frameborder="0"
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+    allowfullscreen>
+  </iframe>
+  <br>
+  <strong>Watch:</strong> Distance Calculation using Ultralytics YOLOv8
+</p>
+
+## Visuals
+
+|                                                  Distance Calculation using Ultralytics YOLOv8                                                  |                                                                
+|:-----------------------------------------------------------------------------------------------------------------------------------------------:|
+| ![Ultralytics YOLOv8 Distance Calculation](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/6b6b735d-3c49-4b84-a022-2bf6e3c72f8b) |
+
+## Advantages of Distance Calculation?
+
+- **Localization Precision:** Enhances accurate spatial positioning in computer vision tasks.
+- **Size Estimation:** Allows estimation of physical sizes for better contextual understanding.
+- **Scene Understanding:** Contributes to a 3D understanding of the environment for improved decision-making.
+
+???+ tip "Distance Calculation"
+
+    - Click on any two bounding boxes with Left Mouse click for distance calculation
+
+!!! Example "Distance Calculation using YOLOv8 Example"
+
+    === "Video Stream"
+
+        ```python
+        from ultralytics import YOLO
+        from ultralytics.solutions import distance_calculation
+        import cv2
+
+        model = YOLO("yolov8n.pt")
+        names = model.model.names
+
+        cap = cv2.VideoCapture("path/to/video/file.mp4")
+        assert cap.isOpened(), "Error reading video file"
+        w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))
+
+        # Video writer
+        video_writer = cv2.VideoWriter("distance_calculation.avi",
+                                       cv2.VideoWriter_fourcc(*'mp4v'),
+                                       fps,
+                                       (w, h))
+
+        # Init distance-calculation obj
+        dist_obj = distance_calculation.DistanceCalculation()
+        dist_obj.set_args(names=names, view_img=True)
+
+        while cap.isOpened():
+            success, im0 = cap.read()
+            if not success:
+                print("Video frame is empty or video processing has been successfully completed.")
+                break
+
+            tracks = model.track(im0, persist=True, show=False)
+            im0 = dist_obj.start_process(im0, tracks)
+            video_writer.write(im0)
+
+        cap.release()
+        video_writer.release()
+        cv2.destroyAllWindows()
+
+        ```
+
+???+ tip "Note"
+
+    - Mouse Right Click will delete all drawn points
+    - Mouse Left Click can be used to draw points
+
+### Optional Arguments `set_args`
+
+| Name             | Type   | Default         | Description                                            |
+|------------------|--------|-----------------|--------------------------------------------------------|
+| `names`          | `dict` | `None`          | Classes names                                          |
+| `view_img`       | `bool` | `False`         | Display frames with counts                             |
+| `line_thickness` | `int`  | `2`             | Increase bounding boxes thickness                      |
+| `line_color`     | `RGB`  | `(255, 255, 0)` | Line Color for centroids mapping on two bounding boxes |
+| `centroid_color` | `RGB`  | `(255, 0, 255)` | Centroid color for each bounding box                   |
+
+### Arguments `model.track`
+
+| Name      | Type    | Default        | Description                                                 |
+|-----------|---------|----------------|-------------------------------------------------------------|
+| `source`  | `im0`   | `None`         | source directory for images or videos                       |
+| `persist` | `bool`  | `False`        | persisting tracks between frames                            |
+| `tracker` | `str`   | `botsort.yaml` | Tracking method 'bytetrack' or 'botsort'                    |
+| `conf`    | `float` | `0.3`          | Confidence Threshold                                        |
+| `iou`     | `float` | `0.5`          | IOU Threshold                                               |
+| `classes` | `list`  | `None`         | filter results by class, i.e. classes=0, or classes=[0,2,3] |
+| `verbose` | `bool`  | `True`         | Display the object tracking results                         |