Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX.

Overview

ONNX-ImageNet-1K-Object-Detector

Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX. The repository combines a class agnostic object localizer to first detect the objects in the image, and next a ResNet50 model trained on ImageNet is used to label each box.

Imagenet 1K Object Detection Original image: https://commons.wikimedia.org/wiki/File:Il_cuore_di_Como.jpg

Why

There are a lot of object detection models, but since most of them are trained in the COCO dataset, most of them can only detect a maximum of 80 classes. This repository proposes a "quick and dirty" solution to be able to detect the 1000 objects available in the ImageNet dataset.

โ— Important โ—

  • This model uses a lightweight class agnostic object localizer to first detect the objects. Therefore, this repository is not going to behave as well as other object detection models in complex scenes. In those cases, the object localizer will fail quickly and therefore no objects will be detected.
  • The ResNet50 clasifier is fast in a desktop GPU, however, since it needs to run for each of the detected boxes, the performance might be affected for images with many objects.

Requirements

  • Check the requirements.txt file.

Installation

pip install -r requirements.txt

ONNX model

  • Class Agnostic Object Localizer: The original model from TensorflowHub (link at the bottom) was converted to different formats (including .onnx) by PINTO0309, the models can be found in his repository. This repository will automatically download the model if the model is not found in the models folder.

  • ResNet50 Classifier: The original model from PaddleClas (link at the bottom) was converted to ONNX format using a similar procedure as the one described in this article by PINTO0309. This repository will automatically download the model.

How to use

  • Image inference:
python image_object_detection.py
  • Video inference:
python video_object_detection.py
  • Webcam inference:
python video_object_detection.py

Examples

Macaque Detection

Macaque Detection Original image: https://commons.wikimedia.org/wiki/File:Onsen_Monkey.JPG

Christmas Stocking Detection

Christmas Stocking Detection Original image: https://unsplash.com/photos/paSqTlm3DsA

Burrito Detection

Burrito Detection Original image: https://commons.wikimedia.org/wiki/File:Breakfast_burrito_(cropped).jpg

Bridge Detection

Bridge Detection Original image: https://commons.wikimedia.org/wiki/File:Bayonne_Bridge_Collins_Pk_jeh-2.JPG

[Inference video Example]

1k.detector.output_Trim.mp4

Original video: https://www.pexels.com/video/a-medusa-jellyfish-swimming-gracefully-underwater-2731905/ (by Vova Krasilnikov)

References

Owner
Ibai Gorordo
Passionate about sensors, technology and their potential to help people.
Ibai Gorordo
null

DeformingThings4D dataset Video | Paper DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of human

208 Jan 03, 2023
ERISHA is a mulitilingual multispeaker expressive speech synthesis framework. It can transfer the expressivity to the speaker's voice for which no expressive speech corpus is available.

ERISHA: Multilingual Multispeaker Expressive Text-to-Speech Library ERISHA is a multilingual multispeaker expressive speech synthesis framework. It ca

Ajinkya Kulkarni 43 Nov 27, 2022
OpenDILab RL Kubernetes Custom Resource and Operator Lib

DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w

OpenDILab 205 Dec 29, 2022
Image Recognition using Pytorch

PyTorch Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot practice and contributing in

Sarat Chinni 1 Nov 02, 2021
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec

10 Dec 16, 2022
Losslandscapetaxonomy - Taxonomizing local versus global structure in neural network loss landscapes

Taxonomizing local versus global structure in neural network loss landscapes Int

Yaoqing Yang 8 Dec 30, 2022
Lane assist for ETS2, built with the ultra-fast-lane-detection model.

Euro-Truck-Simulator-2-Lane-Assist Lane assist for ETS2, built with the ultra-fast-lane-detection model. This project was made possible by the amazing

36 Jan 05, 2023
DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

DeepMetaHandles (CVPR2021 Oral) [paper] [animations] DeepMetaHandles is a shape deformation technique. It learns a set of meta-handles for each given

Liu Minghua 73 Dec 15, 2022
High frequency AI based algorithmic trading module.

Flow Flow is a high frequency algorithmic trading module that uses machine learning to self regulate and self optimize for maximum return. The current

59 Dec 14, 2022
This is the official pytorch implementation for our ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering" on VQA Task

๐ŸŒˆ ERASOR (RA-L'21 with ICRA Option) Official page of "ERASOR: Egocentric Ratio of Pseudo Occupancy-based Dynamic Object Removal for Static 3D Point C

Hyungtae Lim 225 Dec 29, 2022
It's A ML based Web Site build with python and Django to find the breed of the dog

ML-Based-Dog-Breed-Identifier This is a Django Based Web Site To Identify the Breed of which your DOG belogs All You Need To Do is to Follow These Ste

Sanskar Dwivedi 2 Oct 12, 2022
PolyGlot, a fuzzing framework for language processors

PolyGlot, a fuzzing framework for language processors Build We tested PolyGlot on Ubuntu 18.04. Get the source code: git clone https://github.com/s3te

Software Systems Security Team at Penn State University 79 Dec 27, 2022
Deep Learning and Reinforcement Learning Library for Scientists and Engineers ๐Ÿ”ฅ

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

TensorLayer Community 7.1k Dec 27, 2022
This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners.

LiST (Lite Self-Training) This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners. LiST is short for Lite S

Microsoft 28 Dec 07, 2022
DockStream: A Docking Wrapper to Enhance De Novo Molecular Design

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

AstraZeneca - Molecular AI 72 Jan 02, 2023
StarGAN v2-Tensorflow - Simple Tensorflow implementation of StarGAN v2

Official Tensorflow implementation Open ! - Clova AI StarGAN v2 โ€” Un-official TensorFlow Implementation [Paper] [Pytorch] : Diverse Image Synthesis f

Junho Kim 110 Jul 02, 2022
Polynomial-time Meta-Interpretive Learning

Louise - polynomial-time Program Learning Getting help with Louise Louise's author can be reached by email at Stassa Patsantzis 64 Dec 26, 2022

ใ€ŒPyTorch Implementation of AnimeGANv2ใ€ใ‚’็”จใ„ใฆใ€็”Ÿๆˆใ—ใŸ้ก”็”ปๅƒใ‚’ๅ…ƒใฎ็”ปๅƒใซไธŠๆ›ธใใ™ใ‚‹ใƒ‡ใƒข

AnimeGANv2-Face-Overlay-Demo PyTorch Implementation of AnimeGANv2ใ‚’็”จใ„ใฆใ€็”Ÿๆˆใ—ใŸ้ก”็”ปๅƒใ‚’ๅ…ƒใฎ็”ปๅƒใซไธŠๆ›ธใใ™ใ‚‹ใƒ‡ใƒขใงใ™ใ€‚

KazuhitoTakahashi 21 Oct 18, 2022
Raindrop strategy for Irregular time series

Graph-Guided Network For Irregularly Sampled Multivariate Time Series Overview This repository contains processed datasets and implementation code for

Zitnik Lab @ Harvard 74 Jan 03, 2023
A SAT-based sudoku solver

SAT Sudoku solver A SAT-based Sudoku solver made in the context of a small project in the "Logic Problem Solving" class in the first year at the Polyt

Alexandre Malfreyt 5 Apr 15, 2022