Open ideaRunner opened 6 years ago
I agree. I think in tf.placeholder(), you must feed a fixed shape so that in later spp layer you can calculate the previous conv layer shape.
In spp_layer.py
, if the size of not fixed previous conv layer will be None
, so error occur when you try to devide it.
self.batch_size = self.input.get_shape().as_list()[0]
@danielkaifeng How to solve this problem?
@WanliOuyang Unfortunately there is no way to solve this in tensorflow to my knowledge.
@danielkaifeng When I use a fixed batch size value(such as batch_size=4), the code can run, but when training, the precision of the training keeps fluctuating on a very small number(such as the mean accuracy is 0.16). Why is this?
@danielkaifeng Do you sovle it and do you know how to use the multi_scale image inputs ?
@ideaRunner Hi, do you solve the multi-scale image input size problem ?
Hi, chengjunwen:
I think in tensorflow, the convolutional layer's input image size must be fixed. How you make it be capable to input different image size ?
Your reply will be really appriciated, thank you!