Need to start an object detection project. can anyone suggest the better framework which has better accuracy and speed. I have read about imagenet, resnet, mobilenet, yolo, tensorflow and dlib features. Can anyone give a comparison of them and suggest a better option.
A good overview is described in "Speed/accuracy trade-offs for modern convolutional object detectors" (https://arxiv.org/abs/1611.10012).
In order to save time, you may consider using Google Object Detection API https://github.com/tensorflow/models/tree/master/research/object_detection, they have an tutorial on how to train on your own dataset.
It is hard to say which object detection framework is the best. However, I saw people usually stick to Faster R-CNN (for accuracies) and SSD or YOLOv2 (for speed).