Where can I find the pretrained models of fasterRCNN / R-FCN with Mobilenet Feature extractor trained on COCO datset?

Question

I want train a custom dataset on FasterRCNN with Mobilenetv1 or v2. I want to use the pre-trained models in tensorflow zoo. But I cant find faster Rcnn model with mobilenet as base extractor. Where can I get it?

I have already tensorflow zoo in github. I have previous used SSD+Mobilenet config for the same. Now I want to compare the results with FasterRCNN and RCNN with Mobilenet.

danyfang danyfang · Accepted Answer · 2019-05-17T15:49:50

The official repo has not released Faster RCNN with mobilenet models yet. But if you want you can still use some other models with mobilenet trained on COCO, the process is a bit complicated.

There are two important steps to proceed.

First one is to have corresponding feature extractor class. For Faster RCNN, the models directory already contains faster_rcnn_mobilenet feature extractor implementation so this step is OK. But for R-FCN, you will have to implement the feature extractor class yourself.
Second one is to change tensor names available in the checkpoint. For example, if you use ssd_mobilenet_v1_xxx as checkpoint, then all tensors within mobilenet scope are named as FeatureExtractor/MobilenetV1/XXX while if in the faster_rcnn_mobilenet_v1 model, the tensor names within mobilenet scope are FirstStageFeatureExtractor/MobilenetV1/XXX (and SecondStageFeatureExtractor/MobilenetV1/XXX). So essentially you need to remove FirstStage (as well as SecondStage) in the names of all feature extractor tensors, then these tensors will have exactly the same name as in the checkpoint, and will be correctly restored. If you do this, the function you need to modify is
```
  def restore_map(self,
          fine_tune_checkpoint_type='detection',
          load_all_detection_checkpoint_vars=False):
```

in file faster_rcnn_meta_arch.py.

Where can I find the pretrained models of fasterRCNN / R-FCN with Mobilenet Feature extractor trained on COCO datset?

1 Answers