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131 lines
6.9 KiB
131 lines
6.9 KiB
--- |
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comments: true |
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description: Learn how to calculate distances between objects using Ultralytics YOLOv8 for accurate spatial positioning and scene understanding. |
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keywords: Ultralytics, YOLOv8, distance calculation, computer vision, object tracking, spatial positioning |
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--- |
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# Distance Calculation using Ultralytics YOLOv8 |
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## What is Distance Calculation? |
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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](https://www.ultralytics.com/glossary/bounding-box) centroid is employed to calculate the distance for bounding boxes highlighted by the user. |
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<p align="center"> |
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<br> |
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<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LE8am1QoVn4" |
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title="YouTube video player" frameborder="0" |
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" |
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allowfullscreen> |
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</iframe> |
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<br> |
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<strong>Watch:</strong> Distance Calculation using Ultralytics YOLOv8 |
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</p> |
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## Visuals |
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| Distance Calculation using Ultralytics YOLOv8 | |
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| :---------------------------------------------------------------------------------------------------------------------------: | |
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## Advantages of Distance Calculation? |
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- **Localization [Precision](https://www.ultralytics.com/glossary/precision):** Enhances accurate spatial positioning in [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks. |
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- **Size Estimation:** Allows estimation of object size for better contextual understanding. |
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???+ tip "Distance Calculation" |
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- Click on any two bounding boxes with Left Mouse click for distance calculation |
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!!! example "Distance Calculation using YOLOv8 Example" |
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=== "Video Stream" |
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```python |
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import cv2 |
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from ultralytics import YOLO, solutions |
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model = YOLO("yolov8n.pt") |
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names = model.model.names |
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cap = cv2.VideoCapture("path/to/video/file.mp4") |
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assert cap.isOpened(), "Error reading video file" |
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w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)) |
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# Video writer |
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video_writer = cv2.VideoWriter("distance_calculation.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) |
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# Init distance-calculation obj |
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dist_obj = solutions.DistanceCalculation(names=names, view_img=True) |
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while cap.isOpened(): |
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success, im0 = cap.read() |
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if not success: |
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print("Video frame is empty or video processing has been successfully completed.") |
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break |
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tracks = model.track(im0, persist=True, show=False) |
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im0 = dist_obj.start_process(im0, tracks) |
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video_writer.write(im0) |
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cap.release() |
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video_writer.release() |
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cv2.destroyAllWindows() |
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``` |
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???+ note |
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- Mouse Right Click will delete all drawn points |
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- Mouse Left Click can be used to draw points |
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???+ warning "Distance is Estimate" |
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Distance will be an estimate and may not be fully accurate, as it is calculated using 2-dimensional data, which lacks information about the object's depth. |
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### Arguments `DistanceCalculation()` |
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| `Name` | `Type` | `Default` | Description | |
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| ---------------- | ------- | --------------- | --------------------------------------------------------- | |
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| `names` | `dict` | `None` | Dictionary of classes names. | |
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| `view_img` | `bool` | `False` | Flag to indicate if the video stream should be displayed. | |
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| `line_thickness` | `int` | `2` | Thickness of the lines drawn on the image. | |
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| `line_color` | `tuple` | `(255, 255, 0)` | Color of the lines drawn on the image (BGR format). | |
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| `centroid_color` | `tuple` | `(255, 0, 255)` | Color of the centroids drawn (BGR format). | |
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### Arguments `model.track` |
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{% include "macros/track-args.md" %} |
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## FAQ |
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### How do I calculate distances between objects using Ultralytics YOLOv8? |
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To calculate distances between objects using [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics), you need to identify the bounding box centroids of the detected objects. This process involves initializing the `DistanceCalculation` class from Ultralytics' `solutions` module and using the model's tracking outputs to calculate the distances. You can refer to the implementation in the [distance calculation example](#distance-calculation-using-ultralytics-yolov8). |
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### What are the advantages of using distance calculation with Ultralytics YOLOv8? |
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Using distance calculation with Ultralytics YOLOv8 offers several advantages: |
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- **Localization Precision:** Provides accurate spatial positioning for objects. |
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- **Size Estimation:** Helps estimate physical sizes, contributing to better contextual understanding. |
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- **Scene Understanding:** Enhances 3D scene comprehension, aiding improved decision-making in applications like autonomous driving and surveillance. |
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### Can I perform distance calculation in real-time video streams with Ultralytics YOLOv8? |
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Yes, you can perform distance calculation in real-time video streams with Ultralytics YOLOv8. The process involves capturing video frames using [OpenCV](https://www.ultralytics.com/glossary/opencv), running YOLOv8 [object detection](https://www.ultralytics.com/glossary/object-detection), and using the `DistanceCalculation` class to calculate distances between objects in successive frames. For a detailed implementation, see the [video stream example](#distance-calculation-using-ultralytics-yolov8). |
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### How do I delete points drawn during distance calculation using Ultralytics YOLOv8? |
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To delete points drawn during distance calculation with Ultralytics YOLOv8, you can use a right mouse click. This action will clear all the points you have drawn. For more details, refer to the note section under the [distance calculation example](#distance-calculation-using-ultralytics-yolov8). |
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### What are the key arguments for initializing the DistanceCalculation class in Ultralytics YOLOv8? |
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The key arguments for initializing the `DistanceCalculation` class in Ultralytics YOLOv8 include: |
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- `names`: Dictionary mapping class indices to class names. |
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- `view_img`: Flag to indicate if the video stream should be displayed. |
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- `line_thickness`: Thickness of the lines drawn on the image. |
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- `line_color`: Color of the lines drawn on the image (BGR format). |
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- `centroid_color`: Color of the centroids (BGR format). |
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For an exhaustive list and default values, see the [arguments of DistanceCalculation](#arguments-distancecalculation).
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