Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4 | Data Science Computer Vision course 82%off
DISCLOSURE: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission.
 |
| Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4 |
Welcome in conformity with Modern Computer Vision™ Tensorflow, Keras & PyTorch!
AI yet Deep Learning are remodeling industries or certain regarding the nearly intriguing parts regarding that AI revolution is into Computer Vision!
But such as exactly is Computer Vision then by what means is that therefore exciting? Well, such as proviso Computers ought to apprehend where they’re as via cameras then between images? The purposes for certain technology are infinite out of scientific imaging, military, self-driving cars, safety monitoring, analysis, safety, farming, industry, or manufacturing! The list is endless.
Job require because of Computer Vision people are skyrocketing and it’s common that professionals between the area are construction $200,000+ USD salaries. However, getting started in it discipline isn’t easy. There’s an overload of information, dense over as is outdated, or a plethora regarding tutorials so much forget in imitation of teach the foundations. Beginners as a result hold no thought the place in imitation of start.
======================================================
Computer imaginative and prescient features involving Deep Learning are booming!
Having Machines as may 'see' wish alternate our world yet revolutionize almost each and every industry oversea there. Machines then robots up to expectation execute confer wish be capable to:
Perform surgical procedure then accurately analyze or diagnose you from scientific scans.
Enable self-driving cars
Radically change robots allowing to us in conformity with construct robots as execute cook, clean, then aid to us with almost someone task
Understand what's life seen in CCTV surveillance movies hence work done security, visitors management, yet a military of ignoble services
Create Art with wondrous Neural Style Transfers yet other progressive sorts concerning photograph generation
Simulate deep duties such as like Aging faces, editing stay video feeds, then realistically replacing actors into films
======================================================
This path aims after solve every on that!
Taught the usage of Google Colab Notebooks (no foul installs, every code manufactory directly away)
27+ Hours on updated then applicable Computer Vision idea together with example code
Taught using each PyTorch yet Tensorflow Keras!
In this course, thou will learn the fundamental at all foundations over Computer Vision, Classical Computer Vision (using OpenCV) I afterward move over to Deep Learning the place we build our foundational abilities on CNNs yet research all as regards the similar topics:
======================================================
Detailed OpenCV Guide covering:
Image Operations yet Manipulations
Contours or Segmentation
Simple Object Detection or Tracking
Facial Landmarks, Recognition or Face Swaps
OpenCV implementations on Neural Style Transfer, YOLOv3, SSDs or a black and gray photograph colorizer
Working along Video then Video Streams
Our Comprehensive Deep Learning Syllabus includes:
Classification including CNNs
Detailed overview of CNN Analysis, Visualizing performance, Advanced CNNs techniques
Transfer Learning and Fine Tuning
Generative Adversarial Networks - CycleGAN, ArcaneGAN, SuperResolution, StyleGAN
Autoencoders
Neural Style Transfer then Google DeepDream
Modern CNN Architectures such as Vision Transformers (ResNets, DenseNets, MobileNET, VGG19, InceptionV3, EfficientNET then ViTs)
Siamese Networks because image similarity
Facial Recognition (Age, Gender, Emotion, Ethnicity)
PyTorch Lightning
Object Detection along YOLOv5 yet v4, EfficientDetect, SSDs, Faster R-CNNs,
Deep Segmentation - MaskCNN, U-NET, SegNET, or DeepLabV3
Tracking including DeepSORT
Deep know how Generation
Video Classification
Optical Character Recognition (OCR)
Image Captioning
3D Computer Vision the use of Point Cloud Data
Medical Imaging - X-Ray analysis and CT-Scans
Depth Estimation
Making a Computer Vision API together with Flask
And and a whole lot more
This is a comprehensive course, is broken upon of twain (2) primary sections. This preceding is a ample OpenCV (Classical Computer Vision tutorial) yet the 2d is a white Deep Learning
======================================================
This route is crammed along exciting yet cool initiatives including these Classical Computer Vision Projects:
Sorting contours by way of size, location, using to them because of structure matching
Finding Waldo
Perspective Transforms (CamScanner)
Image Similarity
K-Means clustering for photo colors
Motion tracking with MeanShift and CAMShift
Optical Flow
Facial Landmark Detection with Dlib
Face Swaps
QR Code yet Barcode Reaching
Background removal
Text Detection
OCR together with PyTesseract or EasyOCR
Colourize Black or White Photos
Computational Photography including inpainting and Noise Removal
Create a Sketch about yourself the use of Edge Detection
RTSP yet IP Streams
Capturing Screenshots namely video
Import Youtube videos directly
======================================================
Deep Learning Computer Vision Projects:
PyTorch & Keras CNN Tutorial MNIST
PyTorch & Keras Misclassifications and Model Performance Analysis
PyTorch & Keras Fashion-MNIST with or without Regularisation
CNN Visualisation - Filter then Filter Activation Visualisation
CNN Visualisation Filter then Class Maximisation
CNN Visualisation GradCAM GradCAMplusplus or FasterScoreCAM
Replicating LeNet then AlexNet within Tensorflow2.0 using Keras
PyTorch & Keras Pretrained Models - 1 - VGG16, ResNet, Inceptionv3, MobileNetv2, SqueezeNet, WideResNet, DenseNet201, MobileMNASNet, EfficientNet and MNASNet
Rank-1 then Rank-5 Accuracy
PyTorch yet Keras Cats versus Dogs PyTorch - Train together with you own data
PyTorch Lightning Tutorial - Batch and LR Selection, Tensorboards, Callbacks, mGPU, TPU or more
PyTorch Lightning - Transfer Learning
PyTorch yet Keras Transfer Learning yet Fine Tuning
PyTorch & Keras Using CNN's as like a Feature Extractor
PyTorch & Keras - Google Deep Dream
PyTorch Keras - Neural Style Transfer + TF-HUB Models
PyTorch & Keras Autoencoders using the Fashion-MNIST Dataset
PyTorch & Keras - Generative Adversarial Networks - DCGAN - MNIST
Keras - Super Resolution SRGAN
Project - Generate_Anime_with_StyleGAN
CycleGAN - Turn Horses into Zebras
ArcaneGAN inference
PyTorch & Keras Siamese Networks
Facial Recognition along VGGFace in Keras
PyTorch Facial Similarity along FaceNet
DeepFace - Age, Gender, Expression, Headpose then Recognition
Object Detection - Gun, Pistol Detector - Scaled-YOLOv4
Object Detection - Mask Detection - TensorFlow Object Detection - MobileNetV2 SSD
Object Detection stability - Sign Language Detection - TFODAPI - EfficientDetD0-D7
Object Detection - Pot Hole Detection including TinyYOLOv4
Object Detection - Mushroom Type Object Detection - Detectron 2
Object Detection - Website Screenshot Region Detection - YOLOv4-Darknet
Object Detection - Drone Maritime Detector - Tensorflow Object Detection Faster R-CNN
Object Detection - Chess Pieces Detection - YOLOv3 PyTorch
Object Detection - Hardhat Detection for Construction web sites - EfficientDet-v2
Object DetectionBlood Cell Object Detection - YOLOv5
Object DetectionPlant Doctor Object Detection - YOLOv5
Image Segmentation - Keras, U-Net or SegNet
DeepLabV3 - PyTorch_Vision_Deeplabv3
Mask R-CNN Demo
Detectron2 - Mask R-CNN
Train a Mask R-CNN - Shapes
Yolov5 DeepSort Pytorch tutorial
DeepFakes - first-order-model-demo
Vision Transformer Tutorial PyTorch
Vision Transformer Classifier in Keras
Image Classification the usage of BigTransfer (BiT)
Depth Estimation with Keras
Image Similarity Search the usage of Metric Learning along Keras
Image Captioning along Keras
Video Classification together with a CNN-RNN Architecture including Keras
Video Classification with Transformers together with Keras
Point Cloud Classification - PointNet
Point Cloud Segmentation with PointNet
3D uptake Classification CT-Scan
X-ray Pneumonia Classification the use of TPUs
Low Light Image Enhancement using MIRNet
Captcha OCR Cracker
Flask Rest API - Server and Flask Web App
Detectron2 - BodyPose
Who this direction is for:
College/University Students of every degrees Undergrads after PhDs (very useful for those doing projects)
Software Developers then Engineers looking in conformity with transit in Computer Vision
Start above founders lookng in conformity with learn whether in imitation of implement thier considerable idea
Hobbyist then too high schoolers searching after reach began into Computer Vision
deal_code=UDEAFNULP123
Don’t miss any coupons by joining our Telegram channel https://t.me/learningonlinecourses
Note : Coupons might expire anytime, so enroll as soon as possible to get the courses for FREE or Huge discount
