An efficient PyTorch library for Global Wheat Detection using YOLOv5. The project is based on this Kaggle competition Global Wheat Detection (2021).

Overview

Global-Wheat-Detection

An efficient PyTorch library for Global Wheat Detection using YOLOv5. The project is based on this Kaggle competition Global Wheat Detection (May-Aug 2020).

Here's a description of the prediction task:

In this competition, you’ll detect wheat heads from outdoor images of wheat plants, including wheat datasets from around the globe. Using worldwide data, you will focus on a generalized solution to estimate the number and size of wheat heads. To better gauge the performance for unseen genotypes, environments, and observational conditions, the training dataset covers multiple regions. You will use more than 3,000 images from Europe (France, UK, Switzerland) and North America (Canada). The test data includes about 1,000 images from Australia, Japan, and China.

Installation

  1. Create a virtual environment via conda.

    conda create -n wheat_detection python=3.7
    conda activate wheat_detection
  2. Install torch and torchvision.

    conda install pytorch cudatoolkit=10.1 torchvision -c pytorch
  3. Install requirements.

    pip install -r requirements.txt

Dataset

An overview is available here: https://www.kaggle.com/c/global-wheat-detection/data.

Wheat heads were from various sources:
head
A few labeled images are as shown: (Blue bounding boxes):
head head

I used the following command to obtain the data:

kaggle competitions download -c global-wheat-detection

refer to pre_precessing.ipynb to preprocess the dataset:

  • Handled the noisy labels (too big/small boxes etc.)
  • Stratified 5 fold split based on source

Get Started

Please refer to YOLOv5.

Results

Following are the results we got from output files while our model was training.

Here is the PR curve of our model:

Acknowledgement

We thank for the inspiration from YOLOv5 and SENet

If you like our work and use the models for your research, please star our work.

Owner
Chuxin Wang
Chuxin Wang
Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms

LESA Introduction This repository contains the official implementation of Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Cont

Chenglin Yang 20 Dec 31, 2021
NeurIPS 2021, self-supervised 6D pose on category level

SE(3)-eSCOPE video | paper | website Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation Xiaolong Li, Yijia Weng,

Xiaolong 63 Nov 22, 2022
This project implements "virtual speed" from heart rate monito

ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple

2 May 20, 2022
SegNet including indices pooling for Semantic Segmentation with tensorflow and keras

SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te

Yuta Kamikawa 172 Dec 23, 2022
Code for Greedy Gradient Ensemble for Visual Question Answering (ICCV 2021, Oral)

Greedy Gradient Ensemble for De-biased VQA Code release for "Greedy Gradient Ensemble for Robust Visual Question Answering" (ICCV 2021, Oral). GGE can

21 Jun 29, 2022
Code and description for my BSc Project, September 2021

BSc-Project Disclaimer: This repo consists of only the additional python scripts necessary to run the agent. To run the project on your own personal d

Matin Tavakoli 20 Jul 19, 2022
Fairness Metrics: All you need to know

Fairness Metrics: All you need to know Testing machine learning software for ethical bias has become a pressing current concern. Recent research has p

Anonymous2020 1 Jan 17, 2022
Ludwig Benchmarking Toolkit

Ludwig Benchmarking Toolkit The Ludwig Benchmarking Toolkit is a personalized benchmarking toolkit for running end-to-end benchmark studies across an

HazyResearch 17 Nov 18, 2022
Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"

Getting Started This repository contains the code used for the following publications: Probabilistic Guarantees for Safe Deep Reinforcement Learning (

Edoardo Bacci 5 Aug 31, 2022
Flax is a neural network ecosystem for JAX that is designed for flexibility.

Flax: A neural network library and ecosystem for JAX designed for flexibility Overview | Quick install | What does Flax look like? | Documentation See

Google 3.9k Jan 02, 2023
quantize aware training package for NCNN on pytorch

ncnnqat ncnnqat is a quantize aware training package for NCNN on pytorch. Table of Contents ncnnqat Table of Contents Installation Usage Code Examples

62 Nov 23, 2022
For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

Edwin Arkel Rios 72 Nov 30, 2022
Using Hotel Data to predict High Value And Potential VIP Guests

Description Using hotel data and AI to predict high value guests and potential VIP guests. Hotel can leverage on prediction resutls to run more effect

HCG 12 Feb 14, 2022
pytorch, hand(object) detect ,yolo v5,手检测

YOLO V5 物体检测,包括手部检测。 项目介绍 手部检测 手部检测示例如下 : 视频示例: 项目配置 作者开发环境: Python 3.7 PyTorch = 1.5.1 数据集 手部检测数据集 该项目数据集采用 TV-Hand 和 COCO-Hand (COCO-Hand-Big 部分) 进

Eric.Lee 11 Dec 20, 2022
Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"

Output Diversified Sampling (ODS) This is the github repository for the NeurIPS 2020 paper "Diversity can be Transferred: Output Diversification for W

50 Dec 11, 2022
This is the repo for the paper "Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement".

Improving the Accuracy-Memory Trade-Off of Random Forests Via Leaf-Refinement This is the repository for the paper "Improving the Accuracy-Memory Trad

3 Dec 29, 2022
DAT4 - General Assembly's Data Science course in Washington, DC

DAT4 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (12/15/14 - 3/16/15). Instructors: Sinan Ozdemir

Kevin Markham 779 Dec 25, 2022
Improving Object Detection by Estimating Bounding Box Quality Accurately

Improving Object Detection by Estimating Bounding Box Quality Accurately Abstrac

2 Apr 14, 2022
Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286

Pytorch-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https

Alexis David Jacq 163 Dec 26, 2022
Tianshou - An elegant PyTorch deep reinforcement learning library.

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on

Tsinghua Machine Learning Group 5.5k Jan 05, 2023