Learn what recall means in object detection and how to calculate it.
Table of Contents
Question
You are using the object detection capability toevaluate the performance metrics of the trained model. You observe that the recall metric has a value of 0.7. What does this mean?
A. The model identified the class in 30% of the images
B. The model predicted correctly 70% of the images
C. The model identified the class in 70% of the images
Answer
C. The model identified the class in 70% of the images
Explanation
Recall metric specifies what percentage of the class predictions made by the model were correct.
The correct answer is C. The model identified the class in 70% of the images.
To understand why, let’s first review what object detection is and how it works. Object detection is a computer vision task that involves locating and identifying objects of interest in an image or video. Object detection models are trained on labeled data, where each object in the image is annotated with a bounding box and a class label. For example, an image of a street scene might have bounding boxes around cars, pedestrians, bicycles, and traffic signs, with corresponding labels indicating their classes.
One of the challenges of object detection is to evaluate the performance of the trained model. There are different metrics that can be used to measure how well the model can detect objects in new images. One of the most common metrics is the mean average precision (mAP), which is the average of the precision and recall values across all classes. Precision is the ratio of true positives (correctly detected objects) to the total number of predicted objects, while recall is the ratio of true positives to the total number of actual objects.
Recall, in particular, measures how many objects of a given class the model can identify in an image. A high recall value means that the model can detect most of the objects of that class, while a low recall value means that the model misses many of them. For example, if there are 10 cars in an image, and the model detects 7 of them, the recall for the car class is 0.7. This means that the model identified the class in 70% of the images, which is the correct answer to the question.
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