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Objective: This assignment aims to familiarize you with object detection techniques using OpenCV. You will implement a program that can detect and identify objects in
Objective:
This assignment aims to familiarize you with object detection techniques using OpenCV.
You will implement a program that can detect and identify objects in videos.
Task:
Write a python code that detect the objects in the roadtrafifc.mp video.
Download YoloV pretrained model from the OpenCV package.
Use OpenCV functions to read and load the pretrained model.
Familiarize yourself with the model's configuration parameters and adjust them
as needed.
Define the class labels associated with the model's predictions.
Convert the captured frames to the format expected by the model.
Perform any necessary preprocessing steps eg resizing, normalization
Pass the preprocessed frame to the model for inference.
Parse the model's output, which includes bounding boxes and class predictions.
Draw bounding boxes around detected objects in the frame.
Display the predicted class label and confidence score for each detection.
Display the annotated frame in realtimeObjective:
This assignment aims to familiarize you with object detection techniques using OpenCV.
You will implement a program that can detect and identify objects in videos.
Task:
Write a python code that detect the objects in the roadtrafifc.mp video.
Download YoloV pretrained model from the OpenCV package.
Use OpenCV functions to read and load the pretrained model.
Familiarize yourself with the model's configuration parameters and adjust them
as needed.
Define the class labels associated with the model's predictions.
Convert the captured frames to the format expected by the model.
Perform any necessary preprocessing steps eg resizing, normalization
Pass the preprocessed frame to the model for inference.
Parse the model's output, which includes bounding boxes and class predictions.
Draw bounding boxes around detected objects in the frame.
Display the predicted class label and confidence score for each detection.
Display the annotated frame in realtime
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