Welcome to the Ultralytics YOLO26 🚀 notebook! <a href="https://github.com/ultralytics/ultralytics">YOLO26</a> is the latest version of the YOLO (You Only Look Once) AI models developed by <a href="https://ultralytics.com">Ultralytics</a>. This notebook serves as the starting point for exploring the various resources available to help you get started with YOLO26 and understand its features and capabilities.

YOLO26 models are fast, accurate, and easy to use, making them ideal for various object detection and image segmentation tasks. They can be trained on large datasets and run on diverse hardware platforms, from CPUs to GPUs.

We hope that the resources in this notebook will help you get the most out of YOLO26. Please browse the YOLO26 <a href="https://docs.ultralytics.com/guides/object-counting/"> Object Counting Docs</a> for details, raise an issue on <a href="https://github.com/ultralytics/ultralytics">GitHub</a> for support, and join our <a href="https://ultralytics.com/discord">Discord</a> community for questions and discussions!

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Setup

pip install ultralytics and dependencies and check software and hardware.

python

!uv pip install ultralytics
import ultralytics

ultralytics.checks()

Object Counting using Ultralytics YOLO26 🚀

What is Object Counting?

Object counting with Ultralytics YOLO11 involves accurate identification and counting of specific objects in videos and camera streams. YOLO11 excels in real-time applications, providing efficient and precise object counting for various scenarios like crowd analysis and surveillance, thanks to its state-of-the-art algorithms and deep learning capabilities.

Advantages of Object Counting?

Resource Optimization: Object counting facilitates efficient resource management by providing accurate counts, and optimizing resource allocation in applications like inventory management.
Enhanced Security: Object counting enhances security and surveillance by accurately tracking and counting entities, aiding in proactive threat detection.
Informed Decision-Making: Object counting offers valuable insights for decision-making, optimizing processes in retail, traffic management, and various other domains.

Real World Applications

Logistics	Aquaculture

Conveyor Belt Packets Counting Using Ultralytics YOLO26	Fish Counting in Sea using Ultralytics YOLO26

python

import cv2

from ultralytics import solutions

# Open the video file
cap = cv2.VideoCapture("path/to/video.mp4")
assert cap.isOpened(), "Error reading video file"

# Get video properties: width, height, and frames per second (fps)
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS))

# Define points for a line or region of interest in the video frame
line_points = [(20, 400), (1080, 400)]  # Line coordinates

# Initialize the video writer to save the output video
video_writer = cv2.VideoWriter("object_counting_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))

# Initialize the Object Counter with visualization options and other parameters
counter = solutions.ObjectCounter(
    show=True,  # Display the image during processing
    region=line_points,  # Region of interest points
    model="yolo26n.pt",  # Ultralytics YOLO26 model file
    line_width=2,  # Thickness of the lines and bounding boxes
)

# Process video frames in a loop
while cap.isOpened():
    success, im0 = cap.read()
    if not success:
        print("Video frame is empty or video processing has been successfully completed.")
        break

    # Use the Object Counter to count objects in the frame and get the annotated image
    results = counter(im0)

    # Write the annotated frame to the output video
    video_writer.write(results.plot_im)

# Release the video capture and writer objects
cap.release()
video_writer.release()

# Close all OpenCV windows
cv2.destroyAllWindows()

Additional Resources

Community Support

For more information on counting objects with Ultralytics, you can explore the comprehensive Ultralytics Object Counting Docs. This guide covers everything from basic concepts to advanced techniques, ensuring you get the most out of counting and visualization.

Ultralytics ⚡ Resources

At Ultralytics, we are committed to providing cutting-edge AI solutions. Here are some key resources to learn more about our company and get involved with our community:

Ultralytics HUB: Simplify your AI projects with Ultralytics HUB, our no-code tool for effortless YOLO training and deployment.
Ultralytics Licensing: Review our licensing terms to understand how you can use our software in your projects.
About Us: Discover our mission, vision, and the story behind Ultralytics.
Join Our Team: Explore career opportunities and join our team of talented professionals.

YOLO26 🚀 Resources

YOLO26 is the latest evolution in the YOLO series, offering state-of-the-art performance in object detection and image segmentation. Here are some essential resources to help you get started with YOLO26:

GitHub: Access the YOLO26 repository on GitHub, where you can find the source code, contribute to the project, and report issues.
Docs: Explore the official documentation for YOLO26, including installation guides, tutorials, and detailed API references.
Discord: Join our Discord community to connect with other users, share your projects, and get help from the Ultralytics team.

These resources are designed to help you leverage the full potential of Ultralytics' offerings and YOLO26. Whether you're a beginner or an experienced developer, you'll find the information and support you need to succeed.