Installing and Setting Up Keras Implementation of YOLO

Learning Objectives Discover how to install the necessary tools for object detection using YOLO in Keras Get the...

Content Provider

Stone River eLearning

Duration

10 mins

Mode Of Delivery

Online

Course Validity

12 months

Course Level

Advanced

Certification By

Go1 - KRACKiN
  • ( ₹9999 ₹3499)
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Description



Learning Objectives



Discover how to install the necessary tools for object detection using YOLO in Keras




  • Get the right keras-yolo3 git repository

  • Setup the keras-yolo3 project

  • Test if you can perform the YOLO detection on a new image using one of the project’s script



This video forms part of the course Hands-On Deep Learning for Computer Vision



Course Overview



Machine Learning, and Deep learning techniques in particular, are changing the way computers see and interact with the World. From augmented and mixed-reality applications to just gathering data, these new techniques are revolutionizing a lot of industries This course is designed to give you a hands-on learning experience by going from the basic concepts to the most current in-depth Deep Learning methods for Computer Vision in use today.In this course, you will be introduced to the concept of deep learning and a variety of popular and effective techniques for image classification, detection, segmentation and generation. You will learn to build your own neural network and classify images accordingly. You will be taken through popular techniques such as Deep Dream (to generate psychedelic, surreal images), Style Transfer (to transfer styles between images), and Neural Doodle, to generate an image that matches a doodled sketch.By the end of this course, you will be able to use computer vision and deep learning to encode, classify, detect, and style images for the real world.



Target Audience



This course is for Python developers, with some OpenCV experience, who want to incorporate deep learning techniques into their computer vision work. Basic Python and Computer Vision knowledge is assumed.




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