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8.5 KiB
Markdown
157 lines
8.5 KiB
Markdown
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---
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comments: true
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description: Learn how to use Ultralytics YOLO11 for precise object counting in specified regions, enhancing efficiency across various applications.
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keywords: object counting, regions, YOLO11, computer vision, Ultralytics, efficiency, accuracy, automation, real-time, applications, surveillance, monitoring
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---
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# Object Counting in Different Regions using Ultralytics YOLO 🚀
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## What is Object Counting in Regions?
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[Object counting](../guides/object-counting.md) in regions with [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics/) involves precisely determining the number of objects within specified areas using advanced [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv). This approach is valuable for optimizing processes, enhancing security, and improving efficiency in various applications.
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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/mzLfC13ISF4"
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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> Object Counting in Different Regions using Ultralytics YOLO11 | Ultralytics Solutions 🚀
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</p>
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## Advantages of Object Counting in Regions?
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- **[Precision](https://www.ultralytics.com/glossary/precision) and Accuracy:** Object counting in regions with advanced computer vision ensures precise and accurate counts, minimizing errors often associated with manual counting.
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- **Efficiency Improvement:** Automated object counting enhances operational efficiency, providing real-time results and streamlining processes across different applications.
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- **Versatility and Application:** The versatility of object counting in regions makes it applicable across various domains, from manufacturing and surveillance to traffic monitoring, contributing to its widespread utility and effectiveness.
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## Real World Applications
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| Retail | Market Streets |
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| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| People Counting in Different Region using Ultralytics YOLO11 | Crowd Counting in Different Region using Ultralytics YOLO11 |
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## Usage Examples
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!!! example "Region counting using Ultralytics YOLO"
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=== "Python"
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```python
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import cv2
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from ultralytics import solutions
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cap = cv2.VideoCapture("path/to/video.mp4")
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assert cap.isOpened(), "Error reading video file"
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# Pass region as list
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# region_points = [(20, 400), (1080, 400), (1080, 360), (20, 360)]
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# Pass region as dictionary
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region_points = {
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"region-01": [(50, 50), (250, 50), (250, 250), (50, 250)],
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"region-02": [(640, 640), (780, 640), (780, 720), (640, 720)],
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}
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# Video writer
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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 = cv2.VideoWriter("region_counting.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))
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# Initialize region counter object
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regioncounter = solutions.RegionCounter(
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show=True, # display the frame
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region=region_points, # pass region points
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model="yolo11n.pt", # model for counting in regions i.e yolo11s.pt
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)
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# Process video
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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 processing is complete.")
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break
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results = regioncounter(im0)
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# print(results) # access the output
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video_writer.write(results.plot_im)
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cap.release()
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video_writer.release()
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cv2.destroyAllWindows() # destroy all opened windows
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```
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!!! tip "Ultralytics Example Code"
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The Ultralytics region counting module is available in our [examples section](https://github.com/ultralytics/ultralytics/blob/main/examples/YOLOv8-Region-Counter/yolov8_region_counter.py). You can explore this example for code customization and modify it to suit your specific use case.
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### `RegionCounter` Arguments
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Here's a table with the `RegionCounter` arguments:
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{% from "macros/solutions-args.md" import param_table %}
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{{ param_table(["model", "region"]) }}
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The `RegionCounter` solution enables the use of object tracking parameters:
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{% from "macros/track-args.md" import param_table %}
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{{ param_table(["tracker", "conf", "iou", "classes", "verbose", "device"]) }}
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Additionally, the following visualization settings are supported:
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{% from "macros/visualization-args.md" import param_table %}
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{{ param_table(["show", "line_width", "show_conf", "show_labels"]) }}
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## FAQ
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### What is object counting in specified regions using Ultralytics YOLO11?
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Object counting in specified regions with [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics) involves detecting and tallying the number of objects within defined areas using advanced computer vision. This precise method enhances efficiency and [accuracy](https://www.ultralytics.com/glossary/accuracy) across various applications like manufacturing, surveillance, and traffic monitoring.
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### How do I run the region based object counting script with Ultralytics YOLO11?
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Follow these steps to run object counting in Ultralytics YOLO11:
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1. Clone the Ultralytics repository and navigate to the directory:
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```bash
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git clone https://github.com/ultralytics/ultralytics
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cd ultralytics/examples/YOLOv8-Region-Counter
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```
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2. Execute the region counting script:
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```bash
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python yolov8_region_counter.py --source "path/to/video.mp4" --save-img
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```
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For more options, visit the [Usage Examples](#usage-examples) section.
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### Why should I use Ultralytics YOLO11 for object counting in regions?
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Using Ultralytics YOLO11 for object counting in regions offers several advantages:
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1. **Real-time Processing:** YOLO11's architecture enables fast inference, making it ideal for applications requiring immediate counting results.
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2. **Flexible Region Definition:** The solution allows you to define multiple custom regions as polygons, rectangles, or lines to suit your specific monitoring needs.
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3. **Multi-class Support:** Count different object types simultaneously within the same regions, providing comprehensive analytics.
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4. **Integration Capabilities:** Easily integrate with existing systems through the Ultralytics Python API or command-line interface.
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Explore deeper benefits in the [Advantages](#advantages-of-object-counting-in-regions) section.
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### What are some real-world applications of object counting in regions?
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Object counting with Ultralytics YOLO11 can be applied to numerous real-world scenarios:
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- **Retail Analytics:** Count customers in different store sections to optimize layout and staffing.
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- **Traffic Management:** Monitor vehicle flow in specific road segments or intersections.
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- **Manufacturing:** Track products moving through different production zones.
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- **Warehouse Operations:** Count inventory items in designated storage areas.
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- **Public Safety:** Monitor crowd density in specific zones during events.
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Explore more examples in the [Real World Applications](#real-world-applications) section and the [TrackZone](../guides/trackzone.md) solution for additional zone-based monitoring capabilities.
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