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Aubo i5 Dual Arm Collaborative Robot - RealSense D435 - 3D Object Pose Estimation - ROS
YOLO ROS: Real-Time Object Detection for ROS
Deep Object Pose Estimation (DOPE) – ROS inference (CoRL 2018) (forked version for Intel RealSenseD435 camera)
Image augmentation for machine learning experiments.
Put objects on a plane. Use depth camera to find them and add label (for training Yolo).
Real-time Object Grasp Detection ROS package for YOLOv3
Minimal PyTorch implementation of YOLOv3
Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.
YOLOv5 in PyTorch > ONNX > CoreML > TFLite
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