Laudando-Associates-LLC/d-fine-nano
Object Detection
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Updated
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image_id
int32 1
118
| image
imagewidth (px) 1.92k
1.92k
| annotated_image
imagewidth (px) 1.92k
1.92k
| resolution
sequence | bboxes
sequencelengths 0
13
| category_ids
sequencelengths 0
13
|
|---|---|---|---|---|---|
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End of preview. Expand
in Data Studio
Pucks dataset
Dataset Overview
The Pucks Dataset is part of the L&Aser surrogate target recognition pipeline developed by Laudando & Associates LLC. This dataset contains high-resolution field images annotated with bounding boxes around small circular surrogate targets (“pucks”) used to simulate real weed targets for the L&Aser weeding system.
Contents
Raw RGB images collected in field conditions using a NVIDIA Jetson and monocular camera
Bounding boxes in COCO-style format generated using a neural network
Annotated visual overlays for quick inspection
Preview Format
This dataset is optimized for visual inspection on the Hugging Face Hub, with an additional annotated_image column for rapid validation. The raw COCO JSON and images are included in their original form for reproducibility and training.
Example Use
from datasets import load_dataset
ds = load_dataset("Laudando-Associates-LLC/pucks", split="train")
img = ds[0]["image"]
ann = ds[0]["bboxes"]
Recording Date
The data was originally collected in ROS 2 bag format in April 2024 during controlled field trials conducted by Laudando & Associates LLC. This dataset is a stripped-down version containing only the extracted RGB images and their corresponding object detection annotations.
License
This dataset is provided under the L&Aser Dataset Replication License (Version 1.0). See LICENSE for full terms.
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Models trained or fine-tuned on Laudando-Associates-LLC/pucks