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albumentations icon albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

augly icon augly

A data augmentations library for audio, image, text, and video.

auv-modeling-and-sim icon auv-modeling-and-sim

This submission contains the files used in this video on modeling, simulation and control of an Autonomous Underwater vehicle - https://www.mathworks.com/videos/modeling-and-simulation-of-an-autonomous-underwater-vehicle-1586937688878.html. This submission models a 6-DoF autonomous underwater vehicle (AUV) and a position and velocity controller for the AUV. You can switch between low and high fidelity sensor and environment models based on your application needs.

auv_gnc icon auv_gnc

Guidance, Navigation, and Control library for AUVs

awesome-object-detection icon awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

cabin_auv_ws icon cabin_auv_ws

A simple demo for rov/auv underwater object tracking based on ros

cnn-explainer icon cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.

copytranslator icon copytranslator

Foreign language reading and translation assistant based on copy and translate.

cv-detect-robot icon cv-detect-robot

🔥🔥🔥🔥🔥🔥docker+nvidia-docker2+yolov5+YOLOX+yolo+deepsort+tensorRT+ros+deepstream+jetson+nano+TX2+NX for High-performance deployment(高性能部署)

cvat icon cvat

Powerful and efficient Computer Vision Annotation Tool (CVAT)

darknet-loss-drawer icon darknet-loss-drawer

This repository is developed on the basis of pyqt5, mainly through the log files generated during the running of Darknet, and then draw loss files.

deepdiy icon deepdiy

Deep learning based tool for image processing. No need for Programing and GPU.

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

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