Python for Computer Vision with OpenCV and Deep Learning [3/2021, ENG]
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Files
| 1 - Course Overview and Introduction | |||
| 1 - Course Overview.mp4 | 14.65 MB | ||
| 1 - Course Overview.srt | 8.63 KB | ||
| 2 - FAQ Frequently Asked Questions.html | 1.68 KB | ||
| 3 - Computer-Vision-with-Python.zip | 306.16 MB | ||
| 3 - Course Curriculum Overview.mp4 | 20.21 MB | ||
| 3 - Course Curriculum Overview.srt | 7.7 KB | ||
| 4 - Download Link for cvcourselinuxyml.txt | 66 B | ||
| 4 - Download for cvcoursemacosyml.txt | 66 B | ||
| 4 - Download for cvcoursewindowsyml.txt | 82 B | ||
| 4 - Getting SetUp for the Course Content.mp4 | 75.63 MB | ||
| 4 - Getting SetUp for the Course Content.srt | 21.22 KB | ||
| 10 - BONUS SECTION THANK YOU | |||
| 92 - BONUS LECTURE.html | 532 B | ||
| 2 - NumPy and Image Basics | |||
| 10 - NumPy and Image Assessment Test Solutions.mp4 | 41.39 MB | ||
| 10 - NumPy and Image Assessment Test Solutions.srt | 15.19 KB | ||
| 5 - Introduction to Numpy and Image Section.mp4 | 1.85 MB | ||
| 5 - Introduction to Numpy and Image Section.srt | 970 B | ||
| 5 - NumPy Docs.txt | 53 B | ||
| 6 - NumPy Arrays.mp4 | 60.14 MB | ||
| 6 - NumPy Arrays.srt | 27.41 KB | ||
| 7 - What is an image.mp4 | 17.45 MB | ||
| 7 - What is an image.srt | 9.22 KB | ||
| 8 - Images and NumPy.mp4 | 50.11 MB | ||
| 8 - Images and NumPy.srt | 17.89 KB | ||
| 9 - NumPy and Image Assessment Test.mp4 | 11 MB | ||
| 9 - NumPy and Image Assessment Test.srt | 5.03 KB | ||
| 3 - Image Basics with OpenCV | |||
| 11 - Introduction to Images and OpenCV Basics.mp4 | 7.79 MB | ||
| 11 - Introduction to Images and OpenCV Basics.srt | 4.46 KB | ||
| 12 - Opening Image files in a notebook.mp4 | 134.81 MB | ||
| 12 - Opening Image files in a notebook.srt | 32.05 KB | ||
| 13 - Opening Image files with OpenCV.mp4 | 62.53 MB | ||
| 13 - Opening Image files with OpenCV.srt | 18.4 KB | ||
| 14 - Drawing on Images Part One Basic Shapes.mp4 | 26.22 MB | ||
| 14 - Drawing on Images Part One Basic Shapes.srt | 16.33 KB | ||
| 15 - Drawing on Images Part Two Text and Polygons.mp4 | 26.92 MB | ||
| 15 - Drawing on Images Part Two Text and Polygons.srt | 15.96 KB | ||
| 16 - Direct Drawing on Images with a mouse Part One.mp4 | 30.76 MB | ||
| 16 - Direct Drawing on Images with a mouse Part One.srt | 15.49 KB | ||
| 17 - Direct Drawing on Images with a mouse Part Two.mp4 | 9.63 MB | ||
| 17 - Direct Drawing on Images with a mouse Part Two.srt | 4.55 KB | ||
| 18 - Direct Drawing on Images with a mouse Part Three.mp4 | 27.6 MB | ||
| 18 - Direct Drawing on Images with a mouse Part Three.srt | 17.24 KB | ||
| 19 - Image Basics Assessment.mp4 | 22.91 MB | ||
| 19 - Image Basics Assessment.srt | 6.4 KB | ||
| 20 - Image Basics Assessment Solutions.mp4 | 93.31 MB | ||
| 20 - Image Basics Assessment Solutions.srt | 20.87 KB | ||
| 4 - Image Processing | |||
| 21 - Introduction to Image Processing.mp4 | 2.01 MB | ||
| 21 - Introduction to Image Processing.srt | 998 B | ||
| 22 - Color Mappings.mp4 | 30.79 MB | ||
| 22 - Color Mappings.srt | 10.31 KB | ||
| 22 - Information on HSL and HSV Color Mappings.txt | 41 B | ||
| 22 - Information on RGB Color Mappings.txt | 45 B | ||
| 23 - Blending and Pasting Images.mp4 | 81.59 MB | ||
| 23 - Blending and Pasting Images.srt | 23.11 KB | ||
| 24 - Blending and Pasting Images Part Two Masks.mp4 | 88.05 MB | ||
| 24 - Blending and Pasting Images Part Two Masks.srt | 25.29 KB | ||
| 25 - Image Thresholding.mp4 | 180.96 MB | ||
| 25 - Image Thresholding.srt | 28.57 KB | ||
| 25 - Thresholding Images Info.txt | 61 B | ||
| 26 - Blurring and Smoothing.mp4 | 72.87 MB | ||
| 26 - Blurring and Smoothing.srt | 11.36 KB | ||
| 26 - Gaussian Blurring.txt | 43 B | ||
| 26 - Info on Blurring.txt | 58 B | ||
| 27 - Blurring and Smoothing Part Two.mp4 | 347.57 MB | ||
| 27 - Blurring and Smoothing Part Two.srt | 33.68 KB | ||
| 28 - Math Behind Morphology.txt | 53 B | ||
| 28 - Morphological Operators.mp4 | 131.76 MB | ||
| 28 - Morphological Operators.srt | 25.06 KB | ||
| 28 - Really great link on Morphological Operators.txt | 51 B | ||
| 29 - Gradients.mp4 | 126 MB | ||
| 29 - Gradients.srt | 22.31 KB | ||
| 29 - Image Gradients.txt | 44 B | ||
| 29 - Sobel Operators.txt | 44 B | ||
| 30 - Color Histograms.txt | 45 B | ||
| 30 - Histograms Part One.mp4 | 50.39 MB | ||
| 30 - Histograms Part One.srt | 20.4 KB | ||
| 31 - Histograms Part Two Histogram Eqaulization.mp4 | 81.2 MB | ||
| 31 - Histograms Part Two Histogram Eqaulization.srt | 20.7 KB | ||
| 32 - Histograms Part Three Histogram Equalization.mp4 | 113.87 MB | ||
| 32 - Histograms Part Three Histogram Equalization.srt | 13.23 KB | ||
| 33 - Image Processing Assessment.mp4 | 33.28 MB | ||
| 33 - Image Processing Assessment.srt | 6.63 KB | ||
| 34 - Image Processing Assessment Solutions.mp4 | 96.47 MB | ||
| 34 - Image Processing Assessment Solutions.srt | 13.11 KB | ||
| 5 - Video Basics with Python and OpenCV | |||
| 35 - Introduction to Video Basics.mp4 | 3.36 MB | ||
| 35 - Introduction to Video Basics.srt | 1.98 KB | ||
| 36 - Connecting to Camera.mp4 | 95.85 MB | ||
| 36 - Connecting to Camera.srt | 24.32 KB | ||
| 37 - Using Video Files.mp4 | 22.39 MB | ||
| 37 - Using Video Files.srt | 11.57 KB | ||
| 38 - Drawing on Live Camera.mp4 | 60.63 MB | ||
| 38 - Drawing on Live Camera.srt | 27.11 KB | ||
| 39 - Video Basics Assessment.mp4 | 7.26 MB | ||
| 39 - Video Basics Assessment.srt | 3.1 KB | ||
| 40 - Video Basics Assessment Solutions.mp4 | 20.8 MB | ||
| 40 - Video Basics Assessment Solutions.srt | 8.26 KB | ||
| 6 - Object Detection with OpenCV and Python | |||
| 41 - Introduction to Object Detection.mp4 | 14.58 MB | ||
| 41 - Introduction to Object Detection.srt | 4.24 KB | ||
| 42 - Template Matching Wiki.txt | 47 B | ||
| 42 - Template Matching.mp4 | 115.14 MB | ||
| 42 - Template Matching.srt | 29.6 KB | ||
| 43 - Corner Detection Part One Harris Corner Detection.mp4 | 56.74 MB | ||
| 43 - Corner Detection Part One Harris Corner Detection.srt | 23.02 KB | ||
| 43 - Harris Corner Detection Detailed.txt | 52 B | ||
| 44 - Corner Detection Part Two ShiTomasi Detection.mp4 | 50.83 MB | ||
| 44 - Corner Detection Part Two ShiTomasi Detection.srt | 10.78 KB | ||
| 44 - Good Features to Track Original Paper.txt | 58 B | ||
| 45 - Canny Edge Detection.txt | 49 B | ||
| 45 - Edege Detection.txt | 44 B | ||
| 45 - Edge Detection.mp4 | 87.19 MB | ||
| 45 - Edge Detection.srt | 15.26 KB | ||
| 46 - Grid Detection.mp4 | 25.84 MB | ||
| 46 - Grid Detection.srt | 12.83 KB | ||
| 47 - Contour Detection.mp4 | 36.29 MB | ||
| 47 - Contour Detection.srt | 18.15 KB | ||
| 48 - Feature Matching Part One.mp4 | 129.63 MB | ||
| 48 - Feature Matching Part One.srt | 19.93 KB | ||
| 49 - Feature Matching Part Two.mp4 | 238.16 MB | ||
| 49 - Feature Matching Part Two.srt | 28.37 KB | ||
| 50 - WaterShed Algorithm.txt | 58 B | ||
| 50 - Watershed Algorithm Part One.mp4 | 40.22 MB | ||
| 50 - Watershed Algorithm Part One.srt | 18.86 KB | ||
| 51 - Watershed Algorithm Part Two.mp4 | 105.51 MB | ||
| 51 - Watershed Algorithm Part Two.srt | 32.78 KB | ||
| 52 - Custom Seeds with Watershed Algorithm.mp4 | 105.78 MB | ||
| 52 - Custom Seeds with Watershed Algorithm.srt | 29.83 KB | ||
| 53 - Haar Cascade Features.txt | 47 B | ||
| 53 - Introduction to Face Detection.mp4 | 28.61 MB | ||
| 53 - Introduction to Face Detection.srt | 14.54 KB | ||
| 54 - Face Detection with OpenCV.mp4 | 139.19 MB | ||
| 54 - Face Detection with OpenCV.srt | 21.92 KB | ||
| 55 - Detection Assessment.mp4 | 44.42 MB | ||
| 55 - Detection Assessment.srt | 6.29 KB | ||
| 56 - Detection Assessment Solutions.mp4 | 75.67 MB | ||
| 56 - Detection Assessment Solutions.srt | 10.2 KB | ||
| 7 - Object Tracking | |||
| 57 - 05-Object-Tracking.zip | 16.39 KB | ||
| 57 - Introduction to Object Tracking.mp4 | 1.6 MB | ||
| 57 - Introduction to Object Tracking.srt | 953 B | ||
| 58 - Optical Flow.mp4 | 19.99 MB | ||
| 58 - Optical Flow.srt | 9.32 KB | ||
| 58 - Optical Flow.txt | 42 B | ||
| 59 - Optical Flow Coding with OpenCV Part One.mp4 | 108.29 MB | ||
| 59 - Optical Flow Coding with OpenCV Part One.srt | 28.41 KB | ||
| 60 - Optical Flow Coding with OpenCV Part Two.mp4 | 41.16 MB | ||
| 60 - Optical Flow Coding with OpenCV Part Two.srt | 16.55 KB | ||
| 61 - MeanShift On Wikipedia.txt | 40 B | ||
| 61 - MeanShift and CamShift Tracking Theory.mp4 | 16.29 MB | ||
| 61 - MeanShift and CamShift Tracking Theory.srt | 9.43 KB | ||
| 61 - Meanshift for Image Segmentation.txt | 88 B | ||
| 62 - MeanShift and CamShift Tracking with OpenCV.mp4 | 54.83 MB | ||
| 62 - MeanShift and CamShift Tracking with OpenCV.srt | 21.49 KB | ||
| 63 - BOOSTING Tracker Info.txt | 64 B | ||
| 63 - KCF Tracker.txt | 31 B | ||
| 63 - MIL Tracker Info.txt | 53 B | ||
| 63 - Median Flow Tracker Info.txt | 83 B | ||
| 63 - Overview of various Tracking API Methods.mp4 | 31.66 MB | ||
| 63 - Overview of various Tracking API Methods.srt | 11.79 KB | ||
| 63 - TDL Tracker.txt | 44 B | ||
| 64 - Tracking APIs with OpenCV.mp4 | 32.67 MB | ||
| 64 - Tracking APIs with OpenCV.srt | 11.98 KB | ||
| 8 - Deep Learning for Computer Vision | |||
| 65 - Introduction to Deep Learning for Computer Vision.mp4 | 6.07 MB | ||
| 65 - Introduction to Deep Learning for Computer Vision.srt | 4.03 KB | ||
| 66 - Machine Learning Basics.mp4 | 30.1 MB | ||
| 66 - Machine Learning Basics.srt | 12.45 KB | ||
| 67 - Understanding Classification Metrics.mp4 | 85.4 MB | ||
| 67 - Understanding Classification Metrics.srt | 23.82 KB | ||
| 68 - Introduction to Deep Learning Topics.mp4 | 3.36 MB | ||
| 68 - Introduction to Deep Learning Topics.srt | 2.35 KB | ||
| 69 - Understanding a Neuron.mp4 | 11.9 MB | ||
| 69 - Understanding a Neuron.srt | 8.4 KB | ||
| 70 - Understanding a Neural Network.mp4 | 24.43 MB | ||
| 70 - Understanding a Neural Network.srt | 10.06 KB | ||
| 71 - Cost Functions.mp4 | 11.04 MB | ||
| 71 - Cost Functions.srt | 5.48 KB | ||
| 72 - Gradient Descent and Back Propagation.mp4 | 11.21 MB | ||
| 72 - Gradient Descent and Back Propagation.srt | 5.59 KB | ||
| 73 - Keras Basics.mp4 | 95.95 MB | ||
| 73 - Keras Basics.srt | 27.26 KB | ||
| 74 - MNIST Data Overview.mp4 | 12.83 MB | ||
| 74 - MNIST Data Overview.srt | 7.59 KB | ||
| 75 - Convolutional Neural Networks Overview Part One.mp4 | 123.43 MB | ||
| 75 - Convolutional Neural Networks Overview Part One.srt | 29.67 KB | ||
| 76 - Convolutional Neural Networks Overview Part Two.mp4 | 26.49 MB | ||
| 76 - Convolutional Neural Networks Overview Part Two.srt | 6.79 KB | ||
| 77 - Keras Convolutional Neural Networks with MNIST.mp4 | 79.79 MB | ||
| 77 - Keras Convolutional Neural Networks with MNIST.srt | 26.75 KB | ||
| 78 - Keras Convolutional Neural Networks with CIFAR10.mp4 | 88.3 MB | ||
| 78 - Keras Convolutional Neural Networks with CIFAR10.srt | 18.18 KB | ||
| 79 - LINK FOR CATS AND DOGS ZIP.html | 263 B | ||
| 79 - LINK FOR CATS AND DOGS ZIP.txt | 82 B | ||
| 80 - Deep Learning on Custom Images Part One.mp4 | 60.42 MB | ||
| 80 - Deep Learning on Custom Images Part One.srt | 24.09 KB | ||
| 81 - Deep Learning on Custom Images Part Two.mp4 | 160.94 MB | ||
| 81 - Deep Learning on Custom Images Part Two.srt | 31.55 KB | ||
| 82 - Deep Learning and Convolutional Neural Networks Assessment.mp4 | 12.22 MB | ||
| 82 - Deep Learning and Convolutional Neural Networks Assessment.srt | 4.66 KB | ||
| 83 - Deep Learning and Convolutional Neural Networks Assessment Solutions.mp4 | 51.1 MB | ||
| 83 - Deep Learning and Convolutional Neural Networks Assessment Solutions.srt | 10.36 KB | ||
| 84 - Introduction to YOLO v3.mp4 | 11.16 MB | ||
| 84 - Introduction to YOLO v3.srt | 5.23 KB | ||
| 85 - Link for Weights h5 file same as link in article and next lecture.txt | 82 B | ||
| 85 - YOLO Weights Download.html | 300 B | ||
| 86 - Link for weights h5 file same as link from previous lecture.txt | 82 B | ||
| 86 - YOLO v3 with Python.mp4 | 211 MB | ||
| 86 - YOLO v3 with Python.srt | 29.83 KB | ||
| 9 - Capstone Project | |||
| 87 - 07-Capstone-Project.zip | 16.73 KB | ||
| 87 - Introduction to CapStone Project.mp4 | 9.73 MB | ||
| 87 - Introduction to CapStone Project.srt | 1.35 KB | ||
| 88 - Capstone Part One Variables and Background function.mp4 | 27.01 MB | ||
| 88 - Capstone Part One Variables and Background function.srt | 12.56 KB | ||
| 89 - Capstone Part Two Segmentation.mp4 | 22.82 MB | ||
| 89 - Capstone Part Two Segmentation.srt | 8.82 KB | ||
| 90 - Capstone Part Three Counting and ConvexHull.mp4 | 61.04 MB | ||
| 90 - Capstone Part Three Counting and ConvexHull.srt | 21.22 KB | ||
| 91 - Capstone Part Four Bringing it all together.mp4 | 58.49 MB | ||
| 91 - Capstone Part Four Bringing it all together.srt | 18.52 KB |
Description
Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Machine/Deep Learning, Neural Networks
Python for Computer Vision with OpenCV and Deep Learning
Год выпуска: 3/2021
Производитель: Udemy
Сайт производителя: https://udemy.com/course/python-for-computer-vision-with-opencv-and-deep-learning/
Автор: Jose Portilla, Pierian Training
Продолжительность: 14h 4m 26s
Тип раздаваемого материала: Видеоурок
Язык: Английский
Субтитры: Английский
Описание:
Learn the latest techniques in computer vision with Python , OpenCV , and Deep Learning!
What you'll learn Understand basics of NumPy
Manipulate and open Images with NumPy
Use OpenCV to work with image files
Use Python and OpenCV to draw shapes on images and videos
Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
Create Color Histograms with OpenCV
Open and Stream video with Python and OpenCV
Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python Requirements Must have clear understanding of Python Basics
Windows 10 or MacOS or Ubuntu
Must have Install Permissions on Computer
WebCam if you want to learn the video streaming content Description
Welcome to the ultimate online course on Python for Computer Vision!
This course is your best resource for learning how to use the Python programming language for Computer Vision.
We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data.
The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision.
Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more.
As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data.
In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come.
We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more.
Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.
Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.
[spoiler="This course covers all this and more, including the following topics:"]
NumPy
Images with NumPy
Image and Video Basics with NumPy
Color Mappings
Blending and Pasting Images
Image Thresholding
Blurring and Smoothing
Morphological Operators
Gradients
Histograms
Streaming video with OpenCV
Object Detection
Template Matching
Corner, Edge, and Grid Detection
Contour Detection
Feature Matching
WaterShed Algorithm
Face Detection
Object Tracking
Optical Flow
Deep Learning with Keras
Keras and Convolutional Networks
Customized Deep Learning Networks
State of the Art YOLO Networks
and much more!
[/spoiler]
Feel free to message me on Udemy if you have any questions about the course!
Thanks for checking out the course page, and I hope to see you inside!
Jose
Who this course is for: Python Developers interested in Computer Vision and Deep Learning. This course is not for complete python beginners. Формат видео: MP4
Видео: avc, 1920x1080, 16:9, 30.000 к/с, 2391 кб/с
Аудио: aac lc sbr, 44.1 кгц, 62.8 кб/с, 2 аудио
[spoiler="Изменения/Changes"]
Version 2019/9 compared to 2019/2 about 200 MB increase in size is. The number of courses and time, change certain it is not.
Version 2021/3 compared to 2019/9, the duration has decreased by 2 minutes. The course quality has been changed from 720p to 1080p.
[/spoiler]
[spoiler="MediaInfo"]
General
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[/spoiler]
[spoiler="Скриншоты"]
[/spoiler]
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