<p>A good overview is described in "<em>Speed/accuracy trade-offs for modern convolutional object detectors</em>" (<a href="https://arxiv.org/abs/1611.10012" rel="nofollow noreferrer">https://arxiv.org/abs/1611.10012</a>). </p>

<p>In order to save time, you may consider using Google Object Detection API <a href="https://github.com/tensorflow/models/tree/master/research/object_detection" rel="nofollow noreferrer">https://github.com/tensorflow/models/tree/master/research/object_detection</a>,  they have an tutorial on how to train on your own dataset.</p>

<p>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).</p>
Among object detection frameworks which is better in case of time, accuracy, object detection and prediction
<p>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.</p>