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## Objective
This issue is to work on RCNN blog.
## Tasks
- TBD
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I got the clear-cut idea of the encoder side of the segmentation_models. I am using Resnet 152 as the UNet backbone. But I am unclear about the decoder architecture. What configuration of kernel size,…
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Preparing training data...
done
before filtering, there are 10022 images...
after filtering, there are 10022 images...
10022 roidb entries
Loading pretrained weights from data/pretrained_model/vg…
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Platform: WinPython under Windows 10
Python version: Python 3.5.4 (v3.5.4:3f56838, Aug 8 2017, 02:17:05) [MSC v.1900 64 bit (AMD64)] on win32
1) I installed MMdnn with pip install mmdnn as inst…
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Hi everyone!
I trained an inception model with my custom images (dataset of 8.000 images), then saved it.
And when I try to make predictions with it, whatever is the input images to predict, it's th…
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Hi,
The NVIDIA digits website: "Pre-trained UNET model added to the DIGITS model store for image segmentation of medical images" https://developer.nvidia.com/digits
I can not see this model in the…
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Hi, Wei @weiliu89 :
Thanks for your awesome code!
I am working on porting the work of SSD to equip base net other than the specialized VGG16 in your original paper. One of the most important mo…
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To simplify things let's consider VGG16 based FCN-32s (not U-net):
Code:
```
def get_fcn_vgg16_32s(inputs, n_classes, h, w):
x = BatchNormalization()(inputs)
# Block 1
x = Conv2D(64, (3…
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I train the ssd vgg16 300 on voc2007+voc2012 trainval, batchsize 64 and trained 240 epoches as the default settings, but I only get 73.8map,how to train to get 77map as the readme says.
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Hi,
when i used resnet101 for traning(just using the code downloaded) ,it had not gotten lower loss after long time,because there is only 1 GPU.
So,I changed the body to squeeze+resnet,and altered "de…