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torch to caffe convert error

See original GitHub issue

59,60c59
<     pad: 1
<     ceil_mode: false
---
>     pad: 0
2435a2435,2444
>   name: "avgpool1"
>   type: "Pooling"
>   bottom: "relu_blob49"
>   top: "avgpool_blob1"
>   pooling_param {
>     pool: AVE
>     global_pooling: true
>   }
> }
> layer {
2438c2447
<   bottom: "relu_blob49"
---
>   bottom: "avgpool_blob1"
2449c2458
<   top: "batch_norm_blob54"
---
>   top: "output"

https://github.com/JDAI-CV/fast-reid/tree/master/tools/deploy I saw the site above and converted model.

./run_inference.sh What should I do?

Issue Analytics

State:
Created 3 years ago
Comments:19 (1 by maintainers)

Top GitHub Comments

3reactions

Hwijunecommented, Jul 22, 2020

Hello, Do we need to install caffe?

After installing caffe, you need to add your code to “caffe_inference.py” specify your caffe path

#caffe_inference.py
caffe_root = '/home/phj8498/caffe/'
sys.path.insert(0, caffe_root + 'python')
import caffe

0reactions

gmt710commented, Jul 24, 2020

@L1aoXingyu This difference may be related to NL_2.

In caffe_export.py
cfg.MODEL.BACKBONE.WITH_NL = False 

But in visualize_result.py :
cfg.MODEL.BACKBONE.WITH_NL = True

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