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eaglep91's Projects

android-yolo icon android-yolo

Real-time object detection on Android using the YOLO network with TensorFlow

caffe2-ios icon caffe2-ios

Caffe2 on iOS Real-time Demo. Test with Your Own Model and Photos.

examples icon examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

improved-gan icon improved-gan

code for the paper "Improved Techniques for Training GANs"

interview_problems icon interview_problems

Example coding interview problems found through online resources, Cracking the Code book, mentors and colleagues. An additional robust resource for example interview questions and solutions is at https://github.com/mmihaljevic/algortihms_challenges.

lstm icon lstm

Minimal, clean example of lstm neural network training in python, for learning purposes.

mask_rcnn icon mask_rcnn

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

py-faster-rcnn icon py-faster-rcnn

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

pytorch_mask_rcnn icon pytorch_mask_rcnn

Converted from [tf+keras version MASK-RCNN](https://github.com/matterport/Mask_RCNN)

r-fcn icon r-fcn

R-FCN: Object Detection via Region-based Fully Convolutional Networks

refinenet icon refinenet

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

refinenet-image-segmentation icon refinenet-image-segmentation

a tensorflow implement of refinenet ,RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

s2vt icon s2vt

Tensorflow implement of paper: Sequence to Sequence: Video to Text

seg_every_thing icon seg_every_thing

Code release for Hu et al., Learning to Segment Every Thing. in CVPR, 2018.

superglue_training icon superglue_training

This repository contains the training code for SuperGlue. Uses COCO dataset by generating random homographies.

tensorflow_poems icon tensorflow_poems

中文古诗自动作诗机器人,屌炸天,基于tensorflow1.4 api,正在积极维护升级中,快star,保持更新!

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