Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

Related tags

Deep Learningdeep-learningpytorchobject-detectionfew-shot-learning
Overview

Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme)

The official implementation of Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

teaser

The code is built on TFA

Requirements

  • Linux with Python >= 3.6
  • PyTorch >= 1.4
  • torchvision that matches the PyTorch installation
  • CUDA 10.0, 10.1, 10.2
  • GCC >= 4.9

Getting Started

Evaluation with pre-trainied 10-shot final detecor

we provide the pre-trainied 10-shot final detecor

python3 -m tools.test_net --num-gpus 1 \
        --config-file configs/PascalVOC-detection/split1/faster_rcnn_R_101_FPN_ft_all1_10shot.yaml \
        --eval-only

Training & Evaluation in Command Line

To train a base detector, run

python3 -m tools.train_net --num-gpus 1 \
        --config-file configs/PascalVOC-detection/split1/faster_rcnn_R_101_FPN_base1.yaml

fine-tune the detector with novel set

python3 -m tools.ckpt_surgery \
        --src1 checkpoints/coco/faster_rcnn/faster_rcnn_R_101_FPN_base/model_final.pth \
        --method randinit \
        --save-dir checkpoints/coco/faster_rcnn/faster_rcnn_R_101_FPN_all
        --coco

python3 -m tools.train_net --num-gpus 1 \
        --config-file configs/COCO-detection/faster_rcnn_R_101_FPN_ft_all_1shot.yaml \
        --opts MODEL.WEIGHTS $WEIGHTS_PATH

fine-tune the detector with pseudo set

python3 -m tools.genarate_pseudo --num-gpus 1
python3 -m tools.train_feature --num-gpus 1
Owner
GitHub Repository
LinkNet - This repository contains our Torch7 implementation of the network developed by us at e-Lab.

LinkNet This repository contains our Torch7 implementation of the network developed by us at e-Lab. You can go to our blogpost or read the article Lin

e-Lab 158 Nov 11, 2022
Background-Click Supervision for Temporal Action Localization

Background-Click Supervision for Temporal Action Localization This repository is the official implementation of BackTAL. In this work, we study the te

LeYang 221 Oct 09, 2022
Unsupervised Image Generation with Infinite Generative Adversarial Networks

Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da

16 Dec 24, 2021
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage

Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo

Replicate 1.6k Dec 29, 2022
The repository is for safe reinforcement learning baselines.

Safe-Reinforcement-Learning-Baseline The repository is for Safe Reinforcement Learning (RL) research, in which we investigate various safe RL baseline

172 Dec 19, 2022
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.

[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.

VITA 112 Nov 07, 2022
This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

Classifier-Balancing This repository contains code for the paper: Decoupling Representation and Classifier for Long-Tailed Recognition Bingyi Kang, Sa

Facebook Research 820 Dec 26, 2022
Semantic Segmentation with SegFormer on Drone Dataset.

SegFormer_Segmentation Semantic Segmentation with SegFormer on Drone Dataset. You can check out the blog on Medium You can also try out the model with

Praneet 8 Oct 20, 2022
Official Implementation of "Designing an Encoder for StyleGAN Image Manipulation"

Designing an Encoder for StyleGAN Image Manipulation (SIGGRAPH 2021) Recently, there has been a surge of diverse methods for performing image editing

749 Jan 09, 2023
Universal Adversarial Triggers for Attacking and Analyzing NLP (EMNLP 2019)

Universal Adversarial Triggers for Attacking and Analyzing NLP This is the official code for the EMNLP 2019 paper, Universal Adversarial Triggers for

Eric Wallace 248 Dec 17, 2022
FcaNet: Frequency Channel Attention Networks

FcaNet: Frequency Channel Attention Networks PyTorch implementation of the paper "FcaNet: Frequency Channel Attention Networks". Simplest usage Models

327 Dec 27, 2022
Earth Vision Foundation

EVer - A Library for Earth Vision Researcher EVer is a Pytorch-based Python library to simplify the training and inference of the deep learning model.

Zhuo Zheng 34 Nov 26, 2022
TensorFlow ROCm port

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

ROCm Software Platform 622 Jan 09, 2023
Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.

EDVR has been merged into BasicSR. This GitHub repo is a mirror of BasicSR. Recommend to use BasicSR, and open issues, pull requests, etc in BasicSR.

Xintao 1.4k Dec 25, 2022
To provide 100 JAX exercises over different sections structured as a course or tutorials to teach and learn for beginners, intermediates as well as experts

JaxTon 💯 JAX exercises Mission 🚀 To provide 100 JAX exercises over different sections structured as a course or tutorials to teach and learn for beg

Rohan Rao 512 Jan 01, 2023
torchbearer: A model fitting library for PyTorch

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

631 Jan 04, 2023
E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentation

E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentation E2EC: An End-to-End Contour-based Method for High-Quality H

zhangtao 146 Dec 29, 2022
TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)

tf-metal-experiments TensorFlow Metal Backend on Apple Silicon Experiments (just for fun) Setup This is tested on M1 series Apple Silicon SOC only. Te

Timothy Liu 161 Jan 03, 2023
In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm was used to undersampling, SMOTEENN algorithm was applied as a combinatorial approach of over- and undersampling of credit card credit dataset from LendingClub. Machine learning models - BalancedRandomForestClassifier and EasyEnsembleClassifier were used to predict credit risk.

Overview of Credit Card Analysis In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm

Chukwuyem Charles Obuseh 1 Mar 12, 2022
Repository for "Toward Practical Monocular Indoor Depth Estimation" (CVPR 2022)

Toward Practical Monocular Indoor Depth Estimation Cho-Ying Wu, Jialiang Wang, Michael Hall, Ulrich Neumann, Shuochen Su [arXiv] [project site] DistDe

Meta Research 122 Dec 13, 2022