Update README.md

README.md

@@ -43,11 +43,11 @@ In this study, I decided to use YOLOv11 object detection model in order to ident
 # Classes
 
 When annotating images, I specified a total of 5 classes:
-- Avians
-- Pinnipeds
-- Boats
-- Mustelids
-- Humans
+- Avians (count: 1882)
+- Pinnipeds (count: 243)
+- Boats (count: 4)
+- Mustelids (count: 1)
+- Humans (count: 21)
 
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@@ -70,7 +70,7 @@ When annotating images, I specified a total of 5 classes:
 
 ### Interpretation of Results
 
-The model seems to exhibit certain strengths and weaknesses. For example, it is able to correctly identify many classes with decent accuracy, but also has a strong tendency to misidentify objects in the background (such as rocks and waves) as fauna. Additionally, it doesn't have perfect recall as it also has good chance to not count visibly present fauna such as avians and pinnipeds. In addition, the model did not identify any mustelids or boats during testing, which means that it would likely be unable to do so if deployed as is. Overall, a model of this size will need more rigorous training protocols, and will likely need to be deployed using video that does not change as frequently and randomly as the Monterey Bay Live Cam. As for its strengths, the model is excellent at detecting avians perched on the coast, even in cases where there is a high density of them concentrated in an area. Additionally, the metrics of the model suggest that it has a good balanced between Precision and Recall (see Precision-Recall Curve).
+The model seems to exhibit certain strengths and weaknesses. For example, it is able to correctly identify many classes with decent accuracy, but also has a strong tendency to misidentify objects in the background (such as rocks and waves) as fauna. Additionally, it doesn't have perfect recall as it also has good chance to not count visibly present fauna such as avians and pinnipeds. In addition, the model did not identify any mustelids or boats during testing, which means that it would likely be unable to do so if deployed as is. Overall, a model of this size will need more rigorous training protocols (higher amount of images for training and validation), and will likely need to be deployed using video that does not change as frequently and randomly as the Monterey Bay Live Cam. As for its strengths, the model is excellent at detecting avians perched on the coast, even in cases where there is a high density of them concentrated in an area. Additionally, the metrics of the model suggest that it has a good balanced between Precision and Recall (see Precision-Recall Curve).
 
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