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nickrhee's Projects

atlantis icon atlantis

A Benchmark for Semantic Segmentation of Waterbody Images

caffe icon caffe

Caffe: a fast open framework for deep learning.

centernet icon centernet

Object detection, 3D detection, and pose estimation using center point detection:

cocoapi icon cocoapi

Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3

cocojson icon cocojson

Utility scripts for COCO json annotation format

csm icon csm

Community Sensor Model

cvat icon cvat

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

darknet icon darknet

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

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

detectron2 icon detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

extremenet icon extremenet

Bottom-up Object Detection by Grouping Extreme and Center Points

faster-rcnn-rpn icon faster-rcnn-rpn

Region Proposal Network (RPN) of Faster R-CNN implementation in Python and Tensorflow 1.8 with explanations.

hand-digits-recognition icon hand-digits-recognition

Recognize your own handwritten digits with Tensorflow, embedded in a PyQT5 GUI. The Neural Network was trained on MNIST.

java2python icon java2python

Simple but effective library to translate Java source code to Python.

labelme icon labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

libexpat icon libexpat

:herb: Fast streaming XML parser written in C99; migrated from SourceForge to GitHub

mask-rcnn-tensorflow icon mask-rcnn-tensorflow

Fork of Tensorpack to make breaking performance improvements to the Mask RCNN example. Training is approximately 2x faster than the original implementation on AWS.

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