Assign requires shapes of both tensors to match. lhs shape= [2048,3] rhs shape= [2048,21] about faster-rcnn_tensorflow HOT 9 CLOSED

I guess, you changed the CLASS_NUM(in the cfgs.py ) to 2, and you have restored the detection model with the Weights offered by us which trained in the pascal VOC.

Some solutions are as following:
Solution 1: You can load ImageNet's pretrained weights to train your data. Our program does not load the weights of Fast-RCNN/cls_fc when loading ImageNet Pretrained weights, so no error is reported.

Solution 2: Use the pre-trained model we provide to load, but you have to write some codes to control it does not load Fast-RCNN/cls_fc, because the shape is VOC trained weights is [2048, 21] while in your model is [2048, 3].
@leetesua

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@yangJirui you are right, i changed the class num to 2. But how can i load imagenet's pretrained weights? Or how can i control not to load fast_rcnn/cls_fc? thanks a lot!

from faster-rcnn_tensorflow.

If you want to train your own dataset, please change the value of VERSION in cfgs.py. If not, model will load the weights which we provide according to the VERSION. @leetesua

from faster-rcnn_tensorflow.

1、If you want to train your own data, please note:

(1) Modify parameters (such as CLASS_NUM, DATASET_NAME, VERSION, etc.) in $PATH_ROOT/libs/configs/cfgs.py
(2) Add category information in $PATH_ROOT/libs/label_name_dict/lable_dict.py     
(3) Add data_name to line 76 of $PATH_ROOT/data/io/read_tfrecord.py 

@leetesua

from faster-rcnn_tensorflow.

I have changed the VERSION in cfgs from 'FasterRCNN_20180517' to '', so it won't load anything from output/trained_weight, however, when I run train.py again, it stops, with 'restore model' as the last printed line:

also, I am a little bit confused about,,, should i change the trained_weight in output folder or pretrained_weight in data folder ?

from faster-rcnn_tensorflow.

from faster-rcnn_tensorflow.

from faster-rcnn_tensorflow.

There are must something wrong with your tfrecord. @leetesua

from faster-rcnn_tensorflow.

Check your data and xml carefully.

from faster-rcnn_tensorflow.