A simple python module to generate anchor (aka default/prior) boxes for object detection tasks.

Overview

PyBx

WIP

A simple python module to generate anchor (aka default/prior) boxes for object detection tasks. Calculated anchor boxes are returned as ndarrays in pascal_voc format by default.

Installation

pip install pybx

Usage

To calculate the anchor boxes for a single feature size and aspect ratio, given the image size:

from pybx import anchor

image_sz = (300, 300, 3)
feature_sz = (10, 10)
asp_ratio = 1/2.

anchor.bx(image_sz, feature_sz, asp_ratio)

To calculate anchor boxes for multiple feature sizes and aspect ratios:

feature_szs = [(10, 10), (8, 8)]
asp_ratios = [1., 1/2., 2.]

anchor.bxs(image_sz, feature_szs, asp_ratios)

More on visualising the anchor boxes here.

Todo

  • Wrapper class for boxes with vis.draw() method
  • Companion notebook
  • IOU check (return best overlap boxes)
  • Return masks
  • Unit tests
  • Specific tests
    • feature_sz of different aspect ratios
    • image_sz of different aspect ratios
  • Move to setup.py
Comments
  • Build and refactor [nbdev]

    Build and refactor [nbdev]

    A refactored version of pybx built using nbdev.

    Added:

    • documentation page: docs, README.md, example walkthrough file
    • GH workflow tests

    Breaking changes:

    • Need area() and valid() are now properties of BaseBx, so .area and .valid would suffice
    • utils methods refactored to utils and ops
    opened by thatgeeman 0
  • Walkthrough issue for PIL mode.

    Walkthrough issue for PIL mode.

    In the step: Ask VisBx to use random logits with logits=True

    vis.VisBx(image_sz=image_sz, logits=True, feature_sz=feature_sz).show(anchors, labels)
    

    Returns a key error: KeyError: ((1, 1, 3), '<i8') and TypeError: Cannot handle this data type: (1, 1, 3), <i8 with PIL.

    good first issue 
    opened by thatgeeman 0
  • Patch 4: Docs, Improvements, Bug fixes

    Patch 4: Docs, Improvements, Bug fixes

    • Refactored major sections of pybx.basics and the BxType
    • Backwards incompatible!
    • Detailed docstrings for all methods and classes
    • Directly visualize arrays in VisBx()
    • Visualize, iterate, __add__ operations for BaseBx
    • Helper function to set and return BxType (get_bx)
    • Several verbal assertions and bug fixes
    • Fixes #3 #2
    • [dev] Updated tests
    opened by thatgeeman 0
  • TypeError: 'BaseBx' object is not iterable

    TypeError: 'BaseBx' object is not iterable

    Describe the bug draw method of vis module tries to iterate over BaseBx during visualisation

    To Reproduce Steps to reproduce the behavior:

    anns = {'label': 5,
     'x_min': 87.0,
     'y_min': 196.0,
     'x_max': 1013.0,
     'y_max': 2129.0}
    
    from pybx.ops import make_array
    coords, label = make_array(anns)
    
    b = bbx(coords, label)
    vis.draw(img, b)
    
    opened by thatgeeman 0
  • implemented IOU for `BaseBx` and added unittests

    implemented IOU for `BaseBx` and added unittests

    Main commits

    • implemented intersection-over-union (IOU) for BaseBx
    • added unittests for all modules
    • Implemented classmethod and bbx() for BaseBx class to convert all types to BaseBx
    • ops now handles all type conversions (json-array, list-array)
    • bug fixes, best caught:
      • BaseBx method xywh() flipped w and h
      • read keys in order of voc_keys for json annotations)
    • updated README.md and nbs/
    opened by thatgeeman 0
  • Region proposals

    Region proposals

    Is your feature request related to a problem? Please describe. Rather than creating a bunch of anchor boxes based on geometry, create region proposals based on classic signal processing.

    opened by thatgeeman 0
  • Fix notebook (walkthrough)

    Fix notebook (walkthrough)

    Describe the bug

    • [ ] walkthrough link fails
    • [ ] Code import os bug

    To Reproduce Steps to reproduce the behavior:

    1. Go to '...'
    2. Click on '....'
    3. Scroll down to '....'
    4. See error

    Expected behavior A clear and concise description of what you expected to happen.

    Screenshots If applicable, add screenshots to help explain your problem.

    Desktop (please complete the following information):

    • OS: [e.g. iOS]
    • Browser [e.g. chrome, safari]
    • Version [e.g. 22]

    Smartphone (please complete the following information):

    • Device: [e.g. iPhone6]
    • OS: [e.g. iOS8.1]
    • Browser [e.g. stock browser, safari]
    • Version [e.g. 22]

    Additional context Add any other context about the problem here.

    opened by thatgeeman 0
  • Missing sidebar in documentation page

    Missing sidebar in documentation page

    Describe the bug A clear and concise description of what the bug is.

    To Reproduce Steps to reproduce the behavior:

    1. Go to '...'
    2. Click on '....'
    3. Scroll down to '....'
    4. See error

    Expected behavior A clear and concise description of what you expected to happen.

    Screenshots If applicable, add screenshots to help explain your problem.

    Desktop (please complete the following information):

    • OS: [e.g. iOS]
    • Browser [e.g. chrome, safari]
    • Version [e.g. 22]

    Smartphone (please complete the following information):

    • Device: [e.g. iPhone6]
    • OS: [e.g. iOS8.1]
    • Browser [e.g. stock browser, safari]
    • Version [e.g. 22]

    Additional context Add any other context about the problem here.

    opened by thatgeeman 0
Releases(v0.3.0)
  • v0.3.0(Nov 20, 2022)

    A refactored version of pybx built using nbdev.

    Added:

    • documentation page: docs, README.md, example walkthrough file
    • GH workflow tests

    Breaking changes:

    • Need area() and valid() are now properties of BaseBx, so .area and .valid would suffice
    • utils methods refactored to utils and ops
    Source code(tar.gz)
    Source code(zip)
  • v0.2.1(Jan 21, 2022)

    What's Changed

    • Patch 5: Minor fixes by @thatgeeman in https://github.com/thatgeeman/pybx/pull/5
    • Patch 4: Docs, Improvements, Bug fixes by @thatgeeman in https://github.com/thatgeeman/pybx/pull/4

    Full Changelog: https://github.com/thatgeeman/pybx/compare/v0.1.4...v0.2.1

    Source code(tar.gz)
    Source code(zip)
  • v0.1.4(Jan 18, 2022)

    What's Changed

    • implemented IOU for BaseBx and added unittests by @thatgeeman in https://github.com/thatgeeman/pybx/pull/1

    New Contributors

    • @thatgeeman made their first contribution in https://github.com/thatgeeman/pybx/pull/1

    Full Changelog: https://github.com/thatgeeman/pybx/compare/v0.1.3...v0.1.4

    Source code(tar.gz)
    Source code(zip)
Owner
thatgeeman
Physics PhD. Previously @CharlesSadron @CNRS @unistra. Computer Vision.
thatgeeman
Si Adek Keras is software VR dangerous object detection.

Si Adek Python Keras Sistem Informasi Deteksi Benda Berbahaya Keras Python. Version 1.0 Developed by Ananda Rauf Maududi. Developed date: 24 November

Ananda Rauf 1 Dec 21, 2021
Universal Probability Distributions with Optimal Transport and Convex Optimization

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

Rianne van den Berg 172 Dec 13, 2022
PyTorch implementation for NED. It can be used to manipulate the facial emotions of actors in videos based on emotion labels or reference styles.

Neural Emotion Director (NED) - Official Pytorch Implementation Example video of facial emotion manipulation while retaining the original mouth motion

Foivos Paraperas 89 Dec 23, 2022
ML-based medical imaging using Azure

Disclaimer This code is provided for research and development use only. This code is not intended for use in clinical decision-making or for any other

Microsoft Azure 68 Dec 23, 2022
Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

An official implementation of paper Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

11 Nov 23, 2022
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation

DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1

Qing Xu 20 Dec 09, 2022
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3

Dan Hendrycks 464 Dec 27, 2022
Blender Add-On for slicing meshes with planes

MeshSlicer Blender Add-On for slicing meshes with multiple overlapping planes at once. This is a simple Blender addon to slice a silmple mesh with mul

52 Dec 12, 2022
The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22

SiamTPN Introduction This is the official implementation of the SiamTPN (WACV2022). The tracker intergrates pyramid feature network and transformer in

Robotics and Intelligent Systems Control @ NYUAD 28 Nov 25, 2022
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.

KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as

Will McNally 664 Dec 30, 2022
Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

MilaGraph 136 Dec 21, 2022
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)

RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar

Yu Zhang 5 Feb 10, 2022
Simultaneous Demand Prediction and Planning

Simultaneous Demand Prediction and Planning Dependencies Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML Data POI: data/poi Road network

Yizong Wang 1 Sep 01, 2022
FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset (CVPR2022)

FaceVerse FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset Lizhen Wang, Zhiyuan Chen, Tao Yu, Chenguang

Lizhen Wang 219 Dec 28, 2022
Pytorch implementation of Hinton's Dynamic Routing Between Capsules

pytorch-capsule A Pytorch implementation of Hinton's "Dynamic Routing Between Capsules". https://arxiv.org/pdf/1710.09829.pdf Thanks to @naturomics fo

Tim Omernick 625 Oct 27, 2022
Fast and Simple Neural Vocoder, the Multiband RNNMS

Multiband RNN_MS Fast and Simple vocoder, Multiband RNN_MS. Demo Quick training How to Use System Details Results References Demo ToDO: Link super gre

tarepan 5 Jan 11, 2022
上海交通大学全自动抢课脚本,支持准点开抢与抢课后持续捡漏两种模式。2021/06/08更新。

Welcome to Course-Bullying-in-SJTU-v3.1! 2021/6/8 紧急更新v3.1 更新说明 为了更好地保护用户隐私,将原来用户名+密码的登录方式改为微信扫二维码+cookie登录方式,不再需要配置使用pytesseract。在使用扫码登录模式时,请稍等,二维码将马

87 Sep 13, 2022
Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL

A method to solve the Higgs boson challenge using Least Squares - Novae This project is the Project 1 of EPFL CS-433 Machine Learning. The project is

Giacomo Orsi 1 Nov 09, 2021
Self-Supervised Speech Pre-training and Representation Learning Toolkit.

What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site

s3prl 1.6k Jan 08, 2023
The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction".

LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". See below for an overview of

杨攀 93 Jan 07, 2023