Aerial photogrammetry offers the insights necessary to guide projects, and it is a powerful tool for civil and construction engineers. Using rapid computer vision (C.V.) photogrammetry development, structure from motion (SfM) algorithms became an integral part of the photogrammetry technique. Integrating SfM algorithms and photogrammetry through the so-called print-grammetry technique allows the creation of real-world 3D models, avoiding the need for site visiting and fieldwork. This study aims to assess three print-grammetry scenarios for capturing screen images from the Google Earth (GE) Pro using various camera orientation settings to follow these advancements. Images were captured automatically, allowing the user to set the image size and interval time for screen image capturing. The outcomes model for individual scenarios was classified into three categories (buildings, corridors, grass area) and inspected with a reference 3D model generated by photogrammetry. The results show that images captured from the nadir have a minimal mean and standard deviation across classes of the outcome models. However, images captured at a 45° orientation angle in the north-south path and a 0° orientation angle in the east-west path achieve average values compared to other scenarios. The outcomes indicated that capturing oblique images obtained the highest STD values compared to vertical images, demonstrating a lower accuracy level than scenarios captured by truly vertical images. On the other hand, reference point errors and point density provide essential insights in evaluating individual scenarios. Scenario A presents the lowest rate of errors; however, scenario B dominates in point density and is therefore suitable for large areas due to more data collection in a shorter period. Scenario C, on the other hand, displays a high error rate and low score, which reduces accuracy and efficiency.