2 datasets found
  1. m

    Tracking Plant Growth Using Image Sequence Analysis- Dataset

    • data.mendeley.com
    Updated Jan 10, 2025
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    Yiftah Szoke (2025). Tracking Plant Growth Using Image Sequence Analysis- Dataset [Dataset]. http://doi.org/10.17632/zhc7z5xtg5.1
    Explore at:
    Unique identifier
    https://doi.org/10.17632/zhc7z5xtg5.1
    Dataset updated
    Jan 10, 2025
    Authors
    Yiftah Szoke
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset consists of five subsets with annotated images in COCO format, designed for object detection and tracking plant growth: 1. Cucumber_Train Dataset (for Faster R-CNN) - Includes training, validation, and test images of cucumbers from different angles. - Annotations: Bounding boxes in COCO format for object detection tasks.

    1. Tomato Dataset
    2. Contains images of tomato plants for 24 hours at hourly intervals from a fixed angle.

    3. Annotations: Bounding boxes in COCO format.

    4. Pepper Dataset

    5. Contains images of pepper plants for 24 hours at hourly intervals from a fixed angle.

    6. Annotations: Bounding boxes in COCO format.

    7. Cannabis Dataset

    8. Contains images of cannabis plants for 24 hours at hourly intervals from a fixed angle.

    9. Annotations: Bounding boxes in COCO format.

    10. Cucumber Dataset

    11. Contains images of cucumber plants for 24 hours at hourly intervals from a fixed angle.

    12. Annotations: Bounding boxes in COCO format.

    This dataset supports training and evaluation of object detection models across diverse crops.

  2. m

    Tracking Plant Growth Using Image Sequence Analysis- Datasets

    • data.mendeley.com
    Updated Jan 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yiftah Szoke (2025). Tracking Plant Growth Using Image Sequence Analysis- Datasets [Dataset]. http://doi.org/10.17632/z2fp5kbgbh.1
    Explore at:
    Unique identifier
    https://doi.org/10.17632/z2fp5kbgbh.1
    Dataset updated
    Jan 10, 2025
    Authors
    Yiftah Szoke
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset consists of five subsets with annotated images in COCO format, designed for object detection and tracking plant growth: 1. Cucumber_Train Dataset (for Faster R-CNN) - Includes training, validation, and test images of cucumbers from different angles. - Annotations: Bounding boxes in COCO format for object detection tasks.

    1. Tomato Dataset
    2. Contains images of tomato plants for 24 hours at hourly intervals from a fixed angle.

    3. Annotations: Bounding boxes in COCO format.

    4. Pepper Dataset

    5. Contains images of pepper plants for 24 hours at hourly intervals from a fixed angle.

    6. Annotations: Bounding boxes in COCO format.

    7. Cannabis Dataset

    8. Contains images of cannabis plants for 24 hours at hourly intervals from a fixed angle.

    9. Annotations: Bounding boxes in COCO format.

    10. Cucumber Dataset

    11. Contains images of cucumber plants for 24 hours at hourly intervals from a fixed angle.

    12. Annotations: Bounding boxes in COCO format.

    This dataset supports training and evaluation of object detection models across diverse crops.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Yiftah Szoke (2025). Tracking Plant Growth Using Image Sequence Analysis- Dataset [Dataset]. http://doi.org/10.17632/zhc7z5xtg5.1

Tracking Plant Growth Using Image Sequence Analysis- Dataset

Explore at:
Unique identifier
https://doi.org/10.17632/zhc7z5xtg5.1
Dataset updated
Jan 10, 2025
Authors
Yiftah Szoke
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset consists of five subsets with annotated images in COCO format, designed for object detection and tracking plant growth: 1. Cucumber_Train Dataset (for Faster R-CNN) - Includes training, validation, and test images of cucumbers from different angles. - Annotations: Bounding boxes in COCO format for object detection tasks.

  1. Tomato Dataset
  2. Contains images of tomato plants for 24 hours at hourly intervals from a fixed angle.

  3. Annotations: Bounding boxes in COCO format.

  4. Pepper Dataset

  5. Contains images of pepper plants for 24 hours at hourly intervals from a fixed angle.

  6. Annotations: Bounding boxes in COCO format.

  7. Cannabis Dataset

  8. Contains images of cannabis plants for 24 hours at hourly intervals from a fixed angle.

  9. Annotations: Bounding boxes in COCO format.

  10. Cucumber Dataset

  11. Contains images of cucumber plants for 24 hours at hourly intervals from a fixed angle.

  12. Annotations: Bounding boxes in COCO format.

This dataset supports training and evaluation of object detection models across diverse crops.

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