Our deep learning pipeline utilizes advanced image processing and deep learning techniques to accurately identify and quantify stomatal characteristics from microscopic images of leaf surfaces. By applying this pipeline to both control and drought stress conditions, the study sheds light on the variations in stomatal density, size, and distribution. The findings from this study have implications for crop resilience and agricultural practices in the face of changing climate conditions and water scarcity for the native plants of Bangladesh.