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octavmatu's Projects

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧠 Implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

auto-annotate icon auto-annotate

Auto-Annotate - Automatically annotate your entire image directory by a single command. Also supports Custom Labels.

aws-darknet-docker icon aws-darknet-docker

Docker image to get data from S3 bucket, train a yolo network (ideally on EC2) and save trained weights on S3

cmake-templates icon cmake-templates

Collection of barebone CMake project templates for various specific setups

darknet icon darknet

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

davo icon davo

The implementation of Dynamic Attention-based Visual Odometry.

decision-transformer icon decision-transformer

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

dig icon dig

A library for graph deep learning research

fastannotationtool icon fastannotationtool

A tool using OpenCV to annotate images for image classification, optical character reading, ...

geosegnet icon geosegnet

GeoSegNet:Point Cloud Semantic Segmentation via Geometric Encoder-Decoder Modeling

imgaug icon imgaug

Image augmentation for machine learning experiments.

lptn icon lptn

Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

mask_rcnn icon mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

multical icon multical

Multi-camera calibration using one or more calibration patterns

ntrip icon ntrip

Simple ntrip caster/client/server example programs, using the NTRIP2.0 protocol

orb_slam2 icon orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

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