Traffic camera video feeds are helpful in implementing intelligent vehicle detection and classification (IVDC). It has various applications in the transportation engineering domain, such as queue length estimation, vehicle tracking, traffic parameters estimation. However, in the Indian traffic, wide variety of vehicles (motorbikes, auto-rickshaws, cycle-rickshaws, minitrucks, trucks, etc.) travel on the road. They do not follow lane disciplined and occluded each other, making vehicle detection very challenging. This work presented an anchor-free object detection model (YOLOX) on the Indian traffic dataset (ITD) and compared it with the existing object detection models. It achieves 88% mean average precision (mAP) and 37 frames per second (FPS) on ITD.