Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4 | Data Science Computer Vision course 82%off


Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4 | Data Science Computer Vision course 82%off

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Development,Data Science,Computer Vision
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 There’s an overload of information, dense over as is outdated, or a plethora regarding tutorials so much forget in imitation of teach the foundations.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


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 


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