Pytorch ImageNet1k Loader with Bounding Boxes.

Last update: Oct 15, 2022

Related tags

Overview

ImageNet 1K Bounding Boxes

For some experiments, you might wanna pass only the background of imagenet images vs passing only the foreground. Here, I've included the code to extract the meta-data for the bounding box, cleaning up the the downloaded stuff, and then changing ImageNet Loader to support only the images that have box annotations.

How to use:

from costum_imagenet import BackgroundForegroundImageNet
tr = trans.Compose([trans.Resize(224), trans.CenterCrop(224), trans.ToTensor(), ])
dataset = BackgroundForegroundImageNet(root='./data/imagenet/train', download=True, transform=tr)
x, b, f, y = dataset[0]
torchvision.utils.save_image(torch.stack([x, b, f]), 'test1.png')

Example:

If you set the value download=True, the bounding boxes and the indices of imagenet train split that have the bounding boxes will be downloaded. But if for some reason you want to create your own bounding boxes from the scratch, here's the steps for doing it:

Restarting from the scratch

Downloading: First download the data from here:

wget "https://image-net.org/data/bboxes_annotations.tar.gz"

Extract the File:

tar -xvf bboxes_annotations.tar.gz

Extract every subfolder:

cd bboxes_annotations
ls | grep .tar.gz | while read f ; do tar -xvf "${f}" ; done

Convert dataset to JS:

python read_xml.py

Clean the extra 50GB extracted files:

rm *.tar.gz
ls | grep "n.*" | while read f ; do rm -rf "${f}"  ; done

Get Indices that have bounding boxes:

python get_indices.py

Then simply pass the path to the files boxes.pt and indices.pt to your BackgroundForegroundImageNet constructor

dataset = BackgroundForegroundImageNet(root='.', download=False, boxes='boxes.pt', indices='indices.pt')

You might also like...

This code finds bounding box of a single human mouth.

This code finds bounding box of a single human mouth. In comparison to other face segmentation methods, it is relatively insusceptible to open mouth conditions, e.g., yawning, surgical robots, etc. The mouth coordinates are found in a more certified way using two independent algorithms. Therefore, the algorithm can be used in more sensitive applications.

4 Nov 27, 2022

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

147 Dec 5, 2022

Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in

390 Dec 31, 2022

Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera.

Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera. This project prepares training and testing data for various deep learning projects such as 6D object pose estimation projects singleshotpose, as well as object detection and instance segmentation projects.

305 Dec 16, 2022

Improving Object Detection by Estimating Bounding Box Quality Accurately

Pytorch ImageNet1k Loader with Bounding Boxes.

Related tags

Overview

ImageNet 1K Bounding Boxes

How to use:

Example:

Restarting from the scratch

You might also like...

This code finds bounding box of a single human mouth.

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera.

Improving Object Detection by Estimating Bounding Box Quality Accurately

LQM - Improving Object Detection by Estimating Bounding Box Quality Accurately

An essential implementation of BYOL in PyTorch + PyTorch Lightning

RealFormer-Pytorch Implementation of RealFormer using pytorch

Generic template to bootstrap your PyTorch project with PyTorch Lightning, Hydra, W&B, and DVC.

Releases(files)

files(Jan 23, 2022)

Owner

Amin Ghiasi

🚩🚩🚩

Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices

Unofficial Implementation of MLP-Mixer in TensorFlow

LSTMs (Long Short Term Memory) RNN for prediction of price trends

Have you ever wondered how cool it would be to have your own A.I

ICLR 2021, Fair Mixup: Fairness via Interpolation

When are Iterative GPs Numerically Accurate?

Cascading Feature Extraction for Fast Point Cloud Registration (BMVC 2021)

This program can detect your face and add an Christams hat on the top of your head

UnpNet - Rethinking 3-D LiDAR Point Cloud Segmentation(IEEE TNNLS)

DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph

Cours d'Algorithmique Appliquée avec Python pour BTS SIO SISR

A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21

In the AI for TSP competition we try to solve optimization problems using machine learning.

SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis

Python library for tracking human heads with FLAME (a 3D morphable head model)

The personal repository of the work: *DanceNet3D: Music Based Dance Generation with Parametric Motion Transformer*.

An implementation of MobileFormer

PyTorch wrappers for using your model in audacity!

The personal repository of the work: DanceNet3D: Music Based Dance Generation with Parametric Motion Transformer.