Iranian Cars Detection using Yolov5s, PyTorch

Related tags

Deep Learningdetectionpytorchyolov5
Overview

Iranian Cars Detection using Yolov5

media_images_Validation

Train

1-

git clone https://github.com/ultralytics/yolov5
cd yolov5
pip install -r requirements.txt

2- Dataset

../Dataset/images/im0.jpg  # image
../Dataset/labels/im0.txt  # label

3- Create dataset.yaml

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]

path: ../Dataset  # dataset root dir
train: ../Dataset/Train/images  # train images (relative to 'path') 128 images
val: ../Dataset/Val/images  # val images (relative to 'path') 128 images

# Classes
nc: 5  # number of classes
names: ['iranKhodro_dena', 'kia_cerato', 'mazda_3', 'peugeot_206', 'saipa_saina']  # class names

You can change this sections in Yolov5/data/coco128.yaml.

4- Train YOLOv5s on Dataset for 30 epochs using following command:

$ python train.py --img 640 --batch 16 --epochs 30 --data coco128.yaml --weights yolov5s.pt

Inference

!python /yolov5/detect.py --weights /runs/train/exp13/weights/last.pt --img 244 --conf 0.4 --source /data/saipa_saina88.jpg
Owner
Nahid Ebrahimian
AI Graduated Student at Ferdowsi University of Mashhad - Machine Learning Engineer - Research Assistant
Nahid Ebrahimian
GitHub Repository
ScriptProfilerPy - Module to visualize where your python script is slow

ScriptProfiler helps you track where your code is slow It provides: Code lines t

Lucas BLP 3 Jun 02, 2022
Pytorch implementation of SELF-ATTENTIVE VAD, ICASSP 2021

SELF-ATTENTIVE VAD: CONTEXT-AWARE DETECTION OF VOICE FROM NOISE (ICASSP 2021) Pytorch implementation of SELF-ATTENTIVE VAD | Paper | Dataset Yong Rae

97 Dec 23, 2022
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks

Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup

23 Nov 21, 2022
A benchmark dataset for mesh multi-label-classification based on cube engravings introduced in MeshCNN

Double Cube Engravings This script creates a dataset for multi-label mesh clasification, with an intentionally difficult setup for point cloud classif

Yotam Erel 1 Nov 30, 2021
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the

Meta Research 1.1k Jan 03, 2023
HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks

HiFiGAN Denoiser This is a Unofficial Pytorch implementation of the paper HiFi-GAN: High Fidelity Denoising and Dereverberation Based on Speech Deep F

Rishikesh (ऋषिकेश) 134 Dec 27, 2022
AOT (Associating Objects with Transformers) in PyTorch

An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch

162 Dec 14, 2022
CvT2DistilGPT2 is an encoder-to-decoder model that was developed for chest X-ray report generation.

CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1

The Australian e-Health Research Centre 21 Dec 28, 2022
PyTorch implementation of a Real-ESRGAN model trained on custom dataset

Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original

Sber AI 160 Jan 04, 2023
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms This repo contains the source code to reproduce the results in the paper A Close

Costa Huang 73 Dec 24, 2022
[2021][ICCV][FSNet] Full-Duplex Strategy for Video Object Segmentation

Full-Duplex Strategy for Video Object Segmentation (ICCV, 2021) Authors: Ge-Peng Ji, Keren Fu, Zhe Wu, Deng-Ping Fan*, Jianbing Shen, & Ling Shao This

Daniel-Ji 55 Dec 22, 2022
Keep CALM and Improve Visual Feature Attribution

Keep CALM and Improve Visual Feature Attribution Jae Myung Kim1*, Junsuk Choe1*, Zeynep Akata2, Seong Joon Oh1† * Equal contribution † Corresponding a

NAVER AI 90 Dec 07, 2022
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

567 Dec 26, 2022
The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation"

SD-AANet The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation" [arxiv] Overview confi

cv516Buaa 9 Nov 07, 2022
Credit fraud detection in Python using a Jupyter Notebook

Credit-Fraud-Detection - Credit fraud detection in Python using a Jupyter Notebook , using three classification models (Random Forest, Gaussian Naive Bayes, Logistic Regression) from the sklearn libr

Ali Akram 4 Dec 28, 2021
Proposed n-stage Latent Dirichlet Allocation method - A Novel Approach for LDA

n-stage Latent Dirichlet Allocation (n-LDA) Proposed n-LDA & A Novel Approach for classical LDA Latent Dirichlet Allocation (LDA) is a generative prob

Anıl Güven 4 Mar 07, 2022
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting

DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting Created by Yongming Rao*, Wenliang Zhao*, Guangyi Chen, Yansong Tang, Zheng Z

Yongming Rao 322 Dec 31, 2022
[AAAI-2022] Official implementations of MCL: Mutual Contrastive Learning for Visual Representation Learning

Mutual Contrastive Learning for Visual Representation Learning This project provides source code for our Mutual Contrastive Learning for Visual Repres

winycg 48 Jan 02, 2023
Multi-Objective Loss Balancing for Physics-Informed Deep Learning

Multi-Objective Loss Balancing for Physics-Informed Deep Learning Code for ReLoBRaLo. Abstract Physics Informed Neural Networks (PINN) are algorithms

Rafael Bischof 16 Dec 12, 2022
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Anurag Ranjan 110 Nov 02, 2022