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DLIP
  • Introduction
  • Prerequisite
  • Image Processing Basics
    • Notes
      • Thresholding
      • Spatial Filtering
      • Masking with Bitwise Operation
      • Model n Calibration
    • Tutorial
      • Tutorial: Install OpenCV C++
      • Tutorial: Create OpenCV Project
      • Tutorial: C++ basics
      • Tutorial: OpenCV Basics
      • Tutorial: Image Watch for Debugging
      • Tutorial: Spatial Filter
      • Tutorial: Thresholding and Morphology
      • Tutorial: Camera Calibration
      • Tutorial: Color Image Processing
      • Tutorial: Edge Line Circle Detection
      • Tutorial: Corner Detection and Optical Flow
      • Tutorial: OpenCV C++ Cheatsheet
      • Tutorial: Installation for Py OpenCV
      • Tutorial: OpenCv (Python) Basics
    • LAB
      • Lab Report Template
      • Lab Report Grading Criteria
      • LAB Report Instruction
      • LAB: Grayscale Image Segmentation
        • LAB: Grayscale Image Segmentation -Gear
        • LAB: Grayscale Image Segmentation - Bolt and Nut
      • LAB: Color Image Segmentation
        • LAB: Facial Temperature Measurement with IR images
        • LAB: Magic Cloak
      • LAB: Straight Lane Detection and Departure Warning
      • LAB: Dimension Measurement with 2D camera
      • LAB: Tension Detection of Rolling Metal Sheet
  • Deep Learning for Perception
    • Notes
      • Lane Detection with Deep Learning
      • Overview of Deep Learning
        • Object Detection
        • Deep Learning Basics: Introduction
        • Deep Learning State of the Art
        • CNN, Object Detection
      • Perceptron
      • Activation Function
      • Optimization
      • Convolution
      • CNN Overview
      • Evaluation Metric
      • LossFunction Regularization
      • Bias vs Variance
      • BottleNeck Unit
      • Object Detection
      • DL Techniques
        • Technical Strategy by A.Ng
    • Tutorial - PyTorch
      • Tutorial: Install PyTorch
      • Tutorial: Python Numpy
      • Tutorial: PyTorch Tutorial List
      • Tutorial: PyTorch Example Code
      • Tutorial: Tensorboard in Pytorch
      • Tutorial: YOLO in PyTorch
        • Tutorial: Yolov8 in PyTorch
        • Tutorial: Train Yolo v8 with custom dataset
          • Tutorial: Train Yolo v5 with custom dataset
        • Tutorial: Yolov5 in Pytorch (VS code)
        • Tutorial: Yolov3 in Keras
    • LAB
      • Assignment: CNN Classification
      • Assignment: Object Detection
      • LAB: CNN Object Detection 1
      • LAB: CNN Object Detection 2
      • LAB Grading Criteria
    • Tutorial- Keras
      • Train Dataset
      • Train custom dataset
      • Test model
      • LeNet-5 Tutorial
      • AlexNet Tutorial
      • VGG Tutorial
      • ResNet Tutorial
    • Resource
      • Online Lecture
      • Programming tutorial
      • Books
      • Hardware
      • Dataset
      • Useful sites
  • Must Read Papers
    • AlexNet
    • VGG
    • ResNet
    • R-CNN, Fast-RCNN, Faster-RCNN
    • YOLOv1-3
    • Inception
    • MobileNet
    • SSD
    • ShuffleNet
    • Recent Methods
  • DLIP Project
    • Report Template
    • DLIP 2021 Projects
      • Digital Door Lock Control with Face Recognition
      • People Counting with YOLOv4 and DeepSORT
      • Eye Blinking Detection Alarm
      • Helmet-Detection Using YOLO-V5
      • Mask Detection using YOLOv5
      • Parking Space Management
      • Vehicle, Pedestrian Detection with IR Image
      • Drum Playing Detection
      • Turtle neck measurement program using OpenPose
    • DLIP 2022 Projects
      • BakeryCashier
      • Virtual Mouse
      • Sudoku Program with Hand gesture
      • Exercise Posture Assistance System
      • People Counting Embedded System
      • Turtle neck measurement program using OpenPose
    • DLIP Past Projects
  • Installation Guide
    • Installation Guide for Pytorch
      • Installation Guide 2021
    • Anaconda
    • CUDA cuDNN
      • CUDA 10.2
    • OpenCV
      • OpenCV Install and Setup
        • OpenCV 3.4.13 with VS2019
        • OpenCV3.4.7 VS2017
        • MacOS OpenCV C++ in XCode
      • Python OpenCV
      • MATLAB-OpenCV
    • Framework
      • Keras
      • TensorFlow
        • Cheat Sheet
        • Tutorial
      • PyTorch
    • IDE
      • Visual Studio Community
      • Google Codelab
      • Visual Studio Code
        • Python with VS Code
        • Notebook with VS Code
        • C++ with VS Code
      • Jupyter Notebook
        • Install
        • How to use
    • Ubuntu
      • Ubuntu 18.04 Installation
      • Ubuntu Installation using Docker in Win10
      • Ubuntu Troubleshooting
    • ROS
  • Programming
    • Python_Numpy
      • Python Tutorial - Tips
      • Python Tutorial - For Loop
      • Python Tutorial - List Tuple, Dic, Set
    • Markdown
      • Example: API documentation
    • Github
      • Create account
      • Tutorial: Github basic
      • Tutorial: Github Desktop
    • Keras
      • Tutorial Keras
      • Cheat Sheet
    • PyTorch
      • Cheat Sheet
      • Autograd in PyTorch
      • Simple ConvNet
      • MNIST using LeNet
      • Train ConvNet using CIFAR10
  • Resources
    • Useful Resources
    • Github
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On this page
  • Preparation for PyTorch Tutorial
  • PyTorch Installation
  • Check PyTorch Installation and GPU
  • Watch PyTorch Intro Video
  • Follow Quick-Start Tutorial:
  • DLIP Course Tutorials
  • MLP
  • CNN- Classification
  • CNN- Object Detection
  • Useful Sites

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  1. Deep Learning for Perception
  2. Tutorial - PyTorch

Tutorial: PyTorch Tutorial List

PreviousTutorial: Python NumpyNextTutorial: PyTorch Example Code

Last updated 11 months ago

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Preparation for PyTorch Tutorial

PyTorch Installation

Install PyTorch

Follow the installatin instruction:

You should install pytorch in a virtual environment

Check PyTorch Installation and GPU

In the Anaconda Promt, type

conda activate py39
python
import torch
torch.__version__
print("cuda" if torch.cuda.is_available() else "cpu")

Watch PyTorch Intro Video

You need to know 'What is Tensor in Pytorch'

Follow Quick-Start Tutorial:


DLIP Course Tutorials

MLP

CNN- Classification

Create a simple CNN model

Using Popular CNN models from torchvision.models

Assignment: Classification

CNN- Object Detection

YOLO v8 in PyTorch

YOLO v5 in PyTorch


Useful Sites

T1:

T2-1:

T2-2-1:

T2-2-2:

T3-1:

T3-2:

T3-3:

T3-4:

T4-1:

T4-2:

T4-1(option1): (in CoLab)

T4-1(option2): (in VS Code, Local PC)

T4-2: (in VS Code, Local PC)

Pytorch tutorial codes:

Pytorch Tutorial List:

See here for more detail
Introduction to PyTorch (20min)
Pytorch Tutorial(ENG)
Pytorch Tutorial(KOR)
Train a simple MLP and Test with loading trained model (MNIST)
Create LeNeT CNN model, Train with opendataset, and Test with loading trained model (CIFAR10)
Create a CNN model(VGG-16) for ImageNet
Create, Train and Test a CNN model(VGG-16) for CIFAR10
Test using Pretrained Model (VGG, Inception, ResNet)
Train Opendataset with Transfer Learning of Pretrained model
(Assignment) Classification with Custom Dataset
(Assignment) Create ResNet-50 model for ImageNet
Pretrained YOLOv5 with COCO dataset
Pretrained YOLOv5 with COCO dataset
Train YOLOv5 with a Custom Dataset
Pytorch-Tutorial
PyTorch Tutorial List
Install and Inference using YOLOv8
Train and Test using Custom Dataset