Working on Windows with same accuracy
Ram-Godavarthi opened this issue · comments
Hi,
Is it possible to run the code on windows.?
Is it similar to the original faster rcnn in terms of accuracy ?
Did you do inference with this repo??
Yes, I writed and tested on windows.
But currently, the mAP on voc dataset is lower than original faster rcnn... 😭
Okay Fine.
Is the procedure holds same for both windows and ubuntu??
I am getting this error when running demo script in windows..
File "demo_faster_rcnn.py", line 59, in
bbox_mean=cfg.bbox_mean, bbox_std=cfg.bbox_std)
File "C:\Users\godavart\Desktop\gluon-faster-rcnn-master\rcnn\rcnn.py", line 37, in init
negative_iou_threshold=rpn_negative_threshold)
File "C:\Users\godavart\Desktop\gluon-faster-rcnn-master\rcnn\anchor.py", line 13, in init
self._base_anchors = self.params.get_constant('base_anchors', base_anchors)
AttributeError: 'ParameterDict' object has no attribute 'get_constant'
Could you provide your mxnet version? Seems it is caused of your mxnet is out of date.
Even i thought the same.
In windows it is 1.0.0..
How to upgrade this in windows using command line? any command for that
pip install --upgrade --pre mxnet-cuXX
XX is your cuda version, eg. mxnet-cu80 if you use cuda 8.0
Refer to https://pypi.org/project/mxnet/ for all aviliable packages.
I could able to run it on aws.
I will try on windows later..
I want it to work fine in aws now.. Later i will play with it in windows.
Which Pretrained model should i use to check the demo.?
Can You provide me the link?
I have used the one from here I used vgg16 param file .
But i am getting an error something like this .
raceback (most recent call last):
File "./demo_faster_rcnn.py", line 61, in
net.load_params(cfg.model_params.strip(), ctx=ctx)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/block.py", line 340, in load_params
filename, ctx, allow_missing, ignore_extra, self.prefix)
File "/home/ubuntu/anaconda3/lib/python3.6/site-packages/mxnet/gluon/parameter.py", line 769, in load
"with '%s'"%(restore_prefix, name, restore_prefix)
AssertionError: restore_prefix is 'fasterrcnn0_' but Parameters name 'vgg0_conv0_weight' does not start with 'fasterrcnn0_'
Help me out in this..
Pertained model parameters are not release d yet, since the mAP on VOC is lower than original at this config.
The model file you referred is the base model used to init vgg feature extract layers that will be downloaded automatically in the frist you trian.
I got it.. Thank You..
I am not using any pretrained model, instead i am randomizing the weights...