Udemy – Video Segmentation with Python using Deep Learning Real-Time 2024-2

Video Segmentation with Python using Deep Learning Real-Time, Step into the dynamic realm of computer vision and get ready to be the maestro of moving pixels! Dive into the world of ‘Video Instance Segmentation with Python Using Deep Learning.’ Unleash the magic hidden in each frame, master the art of dynamic storytelling, and decode the dance of pixels with the latest in deep learning techniques. This course is your passport to unlocking the secrets hidden within the pixels of moving images. Whether you’re a novice or an enthusiast eager to delve into the intricacies of video analysis, this journey promises to demystify the world of deep learning in the context of dynamic visual narratives.

Instance segmentation is a computer vision task to detect and segment individual objects at a pixel level. Unlike semantic segmentation, which assigns a class label to each pixel without distinguishing between object instances, instance segmentation aims to differentiate between each unique object instance in the image. Instance segmentation is a computer vision task to detect and segment individual objects at a pixel level. Instance segmentation goes a step further than object detection and involves identifying individual objects and segment them from the rest of the region. The output of an instance segmentation model is a set of masks or contours that outline each object in the image, along with class labels and confidence scores for each object. Instance segmentation is useful when you need to know not only where objects are in an image, but also what their exact shape is. So, Instance segmentation provides a more detailed understanding of the scene by recognizing and differentiating between specific instances of objects. This fine-grained recognition is essential in applications where precise object localization is required. For example In the context of autonomous vehicles, instance segmentation is valuable for understanding the surrounding environment. It helps in identifying and tracking pedestrians, vehicles, and other obstacles with high precision, contributing to safe navigation.

What you’ll learn

• Real-Time Video Instance Segmentation with Python and Pytorch using Deep Learning
• Build, Train, & Test Deep Learning Models on Custom Data & Deploy to Your Own Projects
• Introduction to YOLOv8 and its Deep Learning Architecture
• Video Instance Segmentation using YOLOv8 with Python
• Introduction to Mask RCNN and its Deep Learning Architecture
• Instance Segmentation using Mask RCNN with Python
• Configuration of Custom Vehicles Dataset with Annotations for Instance Segmentation
• HyperParameters Settings for Training Instance Segmentation Models
• Training Instance Segmentation YOLOv8 and Mask RCNN Models on Custom Datasets

Who this course is for

• This course is tailored for aspiring Computer Vision and Deep Learning enthusiasts, students, and researchers eager to delve into the world of Video Instance Segmentation with Python.
• Whether you’re a beginner looking to unlock the mysteries of pixels in motion or a seasoned professional aiming to expand your skill set, this course offers a dynamic learning experience. If you’re passionate about mastering deep learning techniques for video analysis and Instance Segmentation, this course is designed just for you.

Specificatoin of Video Segmentation with Python using Deep Learning Real-Time

• Publisher : Udemy
• Teacher : Dr. Mazhar Hussain , AI & Computer Science School
• Language : English
• Level : All Levels
• Number of Course : 20
• Duration : 2 hours and 18 minutes

Content on 2024-4

Requirements

• A Google Gmail account is required to get started with Google Colab to write Python Code
• Python Programming experience is an advantage but not required

Pictures

Sample Clip

Installation Guide

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Quality: 1080p

Download Links

Download Part 1 – 1 GB

Download Part 2 – 401 MB

File size

1.39 GB