I'm evaluating the performance and accuracy in detecting objects for my data set using three deep learning algorithms. In total there are 24,085 images. I measure the performance in terms of time taken to detect the objects. To measure the accuracy, I manually count the number of objects in each image and then calculate recall and precision values for three algorithms.
However, since I'm manually counting to get actual object count, I selected only 30 images. Will that sample be enough to make a conclusion that algorithm 1 is better than others in terms performance and accuracy?