https://github.com/norlab-ulaval/PercepTreeV1

Implementation of Grondin et al. 2022 "Tree Detection and Diameter Estimation Based on Deep Learning". Also includes datasets and some of the pretrained models.
https://github.com/norlab-ulaval/PercepTreeV1

computer-vision datasets forestry

Last synced: about 2 months ago
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Implementation of Grondin et al. 2022 "Tree Detection and Diameter Estimation Based on Deep Learning". Also includes datasets and some of the pretrained models.

• Host: GitHub
• URL: https://github.com/norlab-ulaval/PercepTreeV1
• Owner: norlab-ulaval
• License: apache-2.0
• Created: 2022-05-13T00:19:09.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-15T20:17:15.000Z (4 months ago)
• Last Synced: 2024-07-01T18:22:25.894Z (3 months ago)
• Topics: computer-vision, datasets, forestry
• Language: Python
• Homepage:
• Size: 86.3 MB
• Stars: 78
• Watchers: 11
• Forks: 17
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-canadian-robotics - Forest image (PercepTree) datasets - This repository contains two datasets: a 43,000 synthetic forest images and a 100 real image dataset. Both include high-definition RGB images with depth information, bounding box, instance segmentation masks and keypoints annotation. []([[https://github.com/norlab-ulaval/PercepTreeV1/stargazers](https://github.com/norlab-ulaval/PercepTreeV1)](https://github.com/norlab-ulaval/PercepTreeV1)) (Datasets)