Change input size of a pre-trained network
23 次查看(过去 30 天)
显示 更早的评论
Hi,
I am working on an object detection algorithm with YOLO V2 and I have been following Mathworks guidelines. In particular, I wanted to use the solution given in the following link: https://uk.mathworks.com/help/vision/ug/create-yolo-v2-object-detection-network.html. After that, I'd like to re-train the network so that it gets used to the type of images I am working with. However, when it comes to modify the input size, I end up by having a graph structure, and my imported network continues to have the same input size. If I try to modify it manually, it says the InputSize property is a read-only property, and if I try to directly change my new imageInputLayer object in the network, it also says it's read only.
Is there a way to:
- Import a pre-trained network (I am using resnet50)
- Change its input size and number of output features
- Re-train it?
Thank you in advance!
Virginia
0 个评论
回答(1 个)
HyeongHun LEE
2019-6-11
编辑:HyeongHun LEE
2019-6-11
Hi there
If you want to change the specific layer parameters in pretrained neural networks(e.g. ResNet, DenseNet etc), following the procedure will work.
1. Load target pretrained network in workspace
2. Open "Neural network designer (GUI version, newly updated in 2019a)"
3. Import pretrained network model into the neural network designer space (block diagram will display automatically)
4. Change layer properties (eg. input size, filter size etc)
5. Export network model
Best regards
4 个评论
Ansuman Mahapatra
2020-5-26
编辑:Ansuman Mahapatra
2020-5-26
No it is read only. I cannot able to change even in designer app. I mean cannot edit.
But you have to delete the input layer and create a new input layer.
Mrutyunjaya Hiremath
2023-6-25
编辑:Mrutyunjaya Hiremath
2023-6-25
Delete existing Image Input Layer and Fully Connected Layer then add new Layer in that places . and modify the parameters.. also anyalyze the network for sucessfull creataion
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!