Special purpose object detection systems need to be fast, accurate and dedicated to classifying a handful but relevant number of objects. Our aim was to integrate a system which utilizes the Inception's vast heuristically mapped image pre-diction tree along-with a real time system accurate and robust enough to work at various processing powers and give the user enough confidence of identifying and detecting object with a single frame. As this property can be utilized at huge number of places relying on real time detection, it might not be limited to only driving assistance or autonomous driving systems, but are beyond the scope of this project. To come up with a novel dataset, which would have an image tree with enough weights and variety so as to predict the objects being identified with high accuracy and precision, was taken up to set up the softmax layer of Inception, which was earlier weighted by the existing ImageNet dataset. The results were a convincing recognition accuracy and prediction confidence with real time test frames of a video.