object detection: using more feature extractors with faster RCNN (feature request)

[gdelab]

System information

• What is the top-level directory of the model you are using: tensorflow/models/object_detection
• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): no (only config files)
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): v1.2.0-5-g435cdfc
• CUDA/cuDNN version: 8
• GPU model and memory: Titan X Pascal

Describe the problem

I'm trying to perform object detection on a custom, relatively easy dataset (with ~30k samples). I've successfully used Faster_RCNN with Resnet101_v1 (final mAP 0.9) and inception_resnet_v2 feature extractors (training in progress). Now I would like my model to run faster but still keep good performance, so I'd like to compare the ones I have, with SSD running with various versions of mobile_net. However, to know which changes in performance come from SSD and which come from the feature extractor, I'd like to also try Faster-RCNN with mobile_nets. It's also possible that this yields the tradeoff I need between performance and inference time (faster RCNN being good and slow, and mobile_nets fast).

How can I make mobile_nets compatible with Faster-RCNN?

[michaelisard]

This question is better asked on StackOverflow since it is not a bug or feature request. There is also a larger community that reads questions there. Thanks!

[akashjobanputra]

@gdelab if you have posted the query on StackOverflow, can you share the link to your post ? Thanks!