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    Topic
    2 Concepts | 6 Assessments | 255 Learners

    Welcome to the project on Mask R-CNN with OpenCV for Object Detection. In this project, we will learn how to read a pre-trained TensorFlow model for object detection using OpenCV.

    The real-world scenarios have a lot of applications based on object detection. For example, object detection models are used in self-driving cars to recognize where the pedestrians are, where the are vehicles located, where the signals are, etc in the given frame of view. So, it is very important to develop an understanding of how to use a pre-trained object detection model so that we could later customize it based …

    Instructor: Cloudxlab
  • Topic
    1 Concept | 6 Assessments | 48 Learners

    Welcome to the project on Yolov4 with OpenCV for Object Detection. In this project, we will learn how to use a YOLOv4 network pretrained on the MSCOCO dataset for object detection.

    Object detection has applications in various fields, from home automation to self-driving computers. YOLOv4 is one of the recent state-of-art object detection models. This project provides an overview of how to use a YOLOv4 pretrained model.

    Instructor: Cloudxlab