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Retrained YOLOv3 by C.R.A.W.LAB at Univ of Louisiana at Lafayette

This is a retrained YOLOv3 implementation. Only ~500 labeled images were used to identify Maritime RobotX Challenge (robotx.org) objects. More images are being collected and will be used for further training.
YOLOv3 + GrabCut by C.R.A.W.LAB at Univ of Louisiana at Lafayette

Using YOLOv3 to find the bounding boxes and the OpenCV-bundled version of GrabCut to do segmentation within those bounding boxes (after enlarging them 25%). Red boxes are YOLOv3 bonuding boxes. Shaded black is what GrabCut thought was the foreground.
RetinaNet Inference in Gazebo by C.R.A.W.LAB at Univ of Louisiana at Lafayette

RetunaNet seems to work *just* okay, like YOLOv3.
Tiny YOLOv3 on RobotX Images by C.R.A.W.LAB at Univ of Louisiana at Lafayette

Tiny YOLOv3 (pjreddie.com/darknet/yolo/) transfer learning on RobotX images.
YOLOv3 Inference in Gazebo by C.R.A.W.LAB at Univ of Louisiana at Lafayette

YOLOv3 seems to work okay in Gazebo simulation of the RobotX environment (via: bitbucket.org/osrf/vmrc/overview).
YOLOv3 on Full Dataset by C.R.A.W.LAB at Univ of Louisiana at Lafayette

YOLOv3 transfer learning training using 2583 images from RobotX and other maritime sources.
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YOLOv3 Inference in Gazebo by C.R.A.W.LAB at Univ of Louisiana at Lafayette

YOLOv3 seems to work okay in Gazebo simulation of the RobotX environment (via: bitbucket.org/osrf/vmrc/overview).
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YOLOV3 by TankuNeko
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YOLOv3 looks at rotoballe by Peter Windridge

A sample of round bale photos from Flickr group rotoballe were manually annotated and used to train a YOLOv3 deep CNN. Here is a sample from the test set.
YOLOv3 seeing people in RotoBalle photos by Peter Windridge

Flickr API used to feed low res photos from RotoBalle to YOLOv3. Still needs tuning but there are actually fewer false positives than there look in this image (in some cases a person is hiding and poking their head round or something). Near term goal is build a tool to auto-remove non rotoballe photos from the group.