Tensorflow implementation of DeepLabv2

Overview

TF-deeplab

This is a Tensorflow implementation of DeepLab, compatible with Tensorflow 1.2.1.

Currently it supports both training and testing the ResNet 101 version by converting the caffemodel provided by Jay.

Note that the current version is not multi-scale, i.e. only uses the original resolution branch and discarding all layers of 0.5 and 0.75 resolution.

The caffemodel2npy.py is modified from here, and the deeplab_model.py is modified from here.

Example Usage

  • Download the prototxt and caffemodel provided by Jay
  • Convert caffemodel to npy file
python caffemodel2npy.py deploy.prototxt ../deeplab/ResNet101/init.caffemodel ./model/ResNet101_init.npy
python caffemodel2npy.py deploy.prototxt ../deeplab/ResNet101/train_iter_20000.caffemodel ./model/ResNet101_train.npy
python caffemodel2npy.py deploy.prototxt ../deeplab/ResNet101/train2_iter_20000.caffemodel ./model/ResNet101_train2.npy
  • Convert npy file to tfmodel
python npy2tfmodel.py 0 ./model/ResNet101_init.npy ./model/ResNet101_init.tfmodel
python npy2tfmodel.py 0 ./model/ResNet101_train.npy ./model/ResNet101_train.tfmodel
python npy2tfmodel.py 0 ./model/ResNet101_train2.npy ./model/ResNet101_train2.tfmodel
  • Test on a single image
python deeplab_main.py 0 single
  • Test on the PASCAL VOC2012 validation set (you will also want to look at the matlab folder and run EvalSegResults.m after you run the following command)
python deeplab_main.py 0 test
  • To train on the PASCAL VOC2012 train_aug, run
python deeplab_main.py 0 train

Performance

The converted DeepLab ResNet 101 model achieves mean IOU of 73.296% on the validation set of PASCAL VOC2012. Again, this is only with the original resolution branch, which is likely to be the reason for the performance gap (according to the paper this number should be around 75%).

TODO

  • Incorporating 0.5 and 0.75 resolution
Owner
Chenxi Liu
Ph.D. Student in Computer Science
Chenxi Liu
This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S

Facundo Sapienza 6 Aug 04, 2022
PyTorch implementation of paper A Fast Knowledge Distillation Framework for Visual Recognition.

FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f

Zhiqiang Shen 129 Dec 24, 2022
Pixray is an image generation system

Pixray is an image generation system

pixray 883 Jan 07, 2023
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im

Libo Qin 25 Sep 06, 2022
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.

Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.

Ibai Gorordo 35 Sep 07, 2022
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition (NeurIPS 2019)

MLCR This is the source code for paper Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition. Xuesong Niu, Hu Han, Shiguang

Edson-Niu 60 Nov 29, 2022
Versatile Generative Language Model

Versatile Generative Language Model This is the implementation of the paper: Exploring Versatile Generative Language Model Via Parameter-Efficient Tra

Zhaojiang Lin 17 Dec 02, 2022
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017

Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req

Seonghyeon Nam 146 Nov 25, 2022
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)

MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J

DV Lab 115 Dec 23, 2022
Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR)

This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.

Yongchun Zhu 81 Dec 29, 2022
Txt2Xml tool will help you convert from txt COCO format to VOC xml format in Object Detection Problem.

TXT 2 XML All codes assume running from root directory. Please update the sys path at the beginning of the codes before running. Over View Txt2Xml too

Nguyễn Trường Lâu 4 Nov 24, 2022
Code and data for ImageCoDe, a contextual vison-and-language benchmark

ImageCoDe This repository contains code and data for ImageCoDe: Image Retrieval from Contextual Descriptions. Data All collected descriptions for the

McGill NLP 27 Dec 02, 2022
Differentiable Optimizers with Perturbations in Pytorch

Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens

Jake Tuero 54 Jun 22, 2022
[CVPR2021] Invertible Image Signal Processing

Invertible Image Signal Processing This repository includes official codes for "Invertible Image Signal Processing (CVPR2021)". Figure: Our framework

Yazhou XING 281 Dec 31, 2022
[CoRL 2021] A robotics benchmark for cross-embodiment imitation.

x-magical x-magical is a benchmark extension of MAGICAL specifically geared towards cross-embodiment imitation. The tasks still provide the Demo/Test

Kevin Zakka 36 Nov 26, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

46 Nov 09, 2022
ShuttleNet: Position-aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton (AAAI'22)

ShuttleNet: Position-aware Rally Progress and Player Styles Fusion for Stroke Forecasting in Badminton (AAAI 2022) Official code of the paper ShuttleN

Wei-Yao Wang 11 Nov 30, 2022
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

Stanford Intelligent and Interactive Autonomous Systems Group 57 Dec 28, 2022
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods

pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated

Kitware, Inc. 208 Dec 16, 2022
This repo is a C++ version of yolov5_deepsort_tensorrt. Packing all C++ programs into .so files, using Python script to call C++ programs further.

yolov5_deepsort_tensorrt_cpp Introduction This repo is a C++ version of yolov5_deepsort_tensorrt. And packing all C++ programs into .so files, using P

41 Dec 27, 2022