Team A Wiki Entry on Training Darknet with a Custom Dataset #99
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Team A wiki contribution
Grace's Bonus Wiki Contribution
smbryan
reviewed
Apr 13, 2021
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| This is an article to teach you how to make your own dataset or where to find open-source datasets that are free to use and download. | |||
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Missing header information.
smbryan
reviewed
Apr 13, 2021
| Capture your own images with a camera then create labels for each image that indicates the bounding boxes and IDs of the object class captured. | ||
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| *Option 1:* | ||
| Create labels for all of the images using Yolo_mark [1]. The repo and instructions for use can be found here: <https://github.com/AlexeyAB/Yolo_mark>. These labels will be made in the darknet format. |
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All links need to be in Markdown format. https://guides.github.com/features/mastering-markdown/
smbryan
reviewed
Apr 13, 2021
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| This serves as a tutorial for how to use YOLO and Darknet to train your system to detect classes of objects from a custom dataset. We go over installing darknet dependencies, accessing the darknet repository, configuring your dataset images and labels to work with darknet, editing config files to work with your dataset, training on darknet, and strategies to improve the mAP between training sessions. | |||
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Same comments as open-source-datasets.md
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It looks like you're struggling with the Wiki's standards. The template should help you figure things out: https://raw.githubusercontent.com/RoboticsKnowledgebase/roboticsknowledgebase.github.io/master/_templates/template.md |
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And you're in! Thanks for cleaning that up |
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