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
Official Implementation of Swapping Autoencoder for Deep Image Manipulation (NeurIPS 2020)

Swapping Autoencoder for Deep Image Manipulation Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang UC

449 Dec 27, 2022
It is modified Tensorflow 2.x version of Mask R-CNN

[TF 2.X] Mask R-CNN for Object Detection and Segmentation [Notice] : The original mask-rcnn uses the tensorflow 1.X version. I modified it for tensorf

Milner 34 Nov 09, 2022
Robust Lane Detection via Expanded Self Attention (WACV 2022)

Robust Lane Detection via Expanded Self Attention (WACV 2022) Minhyeok Lee, Junhyeop Lee, Dogyoon Lee, Woojin Kim, Sangwon Hwang, Sangyoun Lee Overvie

Min Hyeok Lee 18 Nov 12, 2022
Neural machine translation between the writings of Shakespeare and modern English using TensorFlow

Shakespeare translations using TensorFlow This is an example of using the new Google's TensorFlow library on monolingual translation going from modern

Motoki Wu 245 Dec 28, 2022
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Stanford Intelligent Systems Laboratory 9 Jun 06, 2022
Official implementation of VQ-Diffusion

Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis

Microsoft 592 Jan 03, 2023
Object detection and instance segmentation toolkit based on PaddlePaddle.

Object detection and instance segmentation toolkit based on PaddlePaddle.

9.3k Jan 02, 2023
[RSS 2021] An End-to-End Differentiable Framework for Contact-Aware Robot Design

DiffHand This repository contains the implementation for the paper An End-to-End Differentiable Framework for Contact-Aware Robot Design (RSS 2021). I

Jie Xu 60 Jan 04, 2023
This implements one of result networks from Large-scale evolution of image classifiers

Exotic structured image classifier This implements one of result networks from Large-scale evolution of image classifiers by Esteban Real, et. al. Req

54 Nov 25, 2022
Deploy a ML inference service on a budget in less than 10 lines of code.

BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end.

1.3k Dec 25, 2022
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021)

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is

Alexey Nekrasov 189 Dec 26, 2022
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising (CVPR 2020 Oral & TPAMI 2021)

ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v

Kaixuan Wei 359 Jan 01, 2023
Tool for installing and updating MiSTer cores and other files

MiSTer Downloader This tool installs and updates all the cores and other extra files for your MiSTer. It also updates the menu core, the MiSTer firmwa

72 Dec 24, 2022
PyTorch implementation of Densely Connected Time Delay Neural Network

Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne

Ya-Qi Yu 64 Oct 11, 2022
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

48 Nov 30, 2022
Official Datasets and Implementation from our Paper "Video Class Agnostic Segmentation in Autonomous Driving".

Video Class Agnostic Segmentation [Method Paper] [Benchmark Paper] [Project] [Demo] Official Datasets and Implementation from our Paper "Video Class A

Mennatullah Siam 26 Oct 24, 2022
Fast Differentiable Matrix Sqrt Root

Official Pytorch implementation of ICLR 22 paper Fast Differentiable Matrix Square Root

YueSong 42 Dec 30, 2022
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks

MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo

Google 302 Dec 23, 2022
U-Net Implementation: Convolutional Networks for Biomedical Image Segmentation" using the Carvana Image Masking Dataset in PyTorch

U-Net Implementation By Christopher Ley This is my interpretation and implementation of the famous paper "U-Net: Convolutional Networks for Biomedical

Christopher Ley 1 Jan 06, 2022
ICML 21 - Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

49 Jan 03, 2023