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Apple Counting on Conveyor Belt using Ultralytics YOLO11

Accurate counting of apples in agricultural setups plays a significant role in yield estimation, supply chain optimization, and resource planning. Leveraging computer vision and AI, we can automate this process with impressive accuracy and efficiency.

Apple Counting on Conveyor Belt using Ultralytics YOLO11

Hardware, Model and Dataset Information

  • CPU: Intel® Core™ i5-10400 CPU @ 2.90GHz.
  • GPU: NVIDIA RTX 3050 for real-time processing tasks.
  • RAM: 64 GB RAM and 1TB HardDisk
  • Model: A fine-tuned Ultralytics YOLO11 model was utilized for object detection and counting.
  • Dataset: The dataset used in this project is proprietary and was annotated in-house by our team.

Real-World Applications for Fruit Counting

  • Yield Estimation: Accurately counting fruits like apples, oranges, or bananas helps farmers forecast harvest sizes, allowing for better planning and resource allocation to meet market demands.
  • Harvesting Optimization: Automated fruit counting aids in identifying the optimal harvest time, ensuring maximum yield and quality while reducing labor costs and wastage.
  • Sorting and Grading: Fruit counting systems integrated with sorting lines improve efficiency in grading fruits by size, weight, or ripeness, directly impacting pricing and market appeal.
  • Supply Chain Management: Real-time fruit counts enable precise tracking and packaging, streamlining logistics and reducing spoilage during transportation to markets or retailers.

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