Laphiler (laphiler)

laphiler

Geek Repo

Company:Baidu Inc.

Location:Beijing

Home Page:https://twitter.com/laphiler

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Laphiler's repositories

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apollo

An open autonomous driving platform

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blackhole

true blackhole

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caffe-tensorflow

Caffe models in TensorFlow

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CodeIgniter

Open Source PHP Framework (originally from EllisLab)

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deep-residual-networks

Deep Residual Learning for Image Recognition

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DeepLabV3-Tensorflow

Reimplementation of DeepLabV3

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DeepLearning

Deep Learning (Python, C, C++, Java, Scala, Go)

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Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

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googletest

Google Test

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handtracking

Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

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hexoapp

hexoapp

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labelImg

:metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images

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laphiler.github.io

my official home page

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Pangolin

Pangolin is a lightweight portable rapid development library for managing OpenGL display / interaction and abstracting video input.

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pointnet

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

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rawfie_interface

A kafka+avro interface with ros

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research

dataset and code for 2016 paper "Learning a Driving Simulator"

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ros_comm

ROS communications-related packages, including core client libraries (roscpp, rospy, roslisp) and graph introspection tools (rostopic, rosnode, rosservice, rosparam).

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TinySTL

TinySTL is a subset of STL(cut some containers and algorithms) and also a superset of STL(add some other containers and algorithms)

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woodbox_mobile_car

The codes of embedded system for robotics experiment in summer school. It can implement the functions are: simple serial control, simple ultrasonic obstacle avoidance and following based on face recognition.

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xman

Blackhole eats everything, even light.

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XNOR-Net

ImageNet classification using binary Convolutional Neural Networks

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Youtube-8M

PaddlePaddle models for Youtube-8M Video Understanding Challenge

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