Using the below precision recall graph where recall is on x-axis and precision is on y-axis can I use this formula to calculate the number of predictions for a given precision, recall threshold ?

These calculations are based on orange trend line.

Assuming this model has been trained on 100 instances and is a binary classifier.

At recall value 0.2 there (0.2 * 100) = 20 relevant instances. At recall value 0.2 the precision = .95 so the number of true positives (20 * .95) = 19. Is this a correct method to calculate the number of true positives from precision-recall graph ?