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README.MD

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@@ -57,14 +57,14 @@ requires python3 and PyTorch 0.3
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- Optional, but strongly recommended: build cython code `nms_gpu_post`:
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```Python
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```Bash
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cd model/utils/nms/
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python3 build.py build_ext --inplace
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```
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- start vidom for visualize
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```
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```Bash
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nohup python3 -m visdom.server &
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```
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@@ -85,23 +85,23 @@ See [demo.ipynb](https://github.com/chenyuntc/simple-faster-rcnn-pytorch/blob/ma
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1. Download the training, validation, test data and VOCdevkit
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```
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```Bash
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wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
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wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
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wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCdevkit_08-Jun-2007.tar
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```
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2. Extract all of these tars into one directory named `VOCdevkit`
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```
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```Bash
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tar xvf VOCtrainval_06-Nov-2007.tar
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tar xvf VOCtest_06-Nov-2007.tar
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tar xvf VOCdevkit_08-Jun-2007.tar
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```
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3. It should have this basic structure
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```
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```Bash
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$VOCdevkit/ # development kit
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$VOCdevkit/VOCcode/ # VOC utility code
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$VOCdevkit/VOC2007 # image sets, annotations, etc.
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If you want to use caffe-pretrain model as initial weight, you can run below to get vgg16 weights converted from caffe, which is the same as the origin paper use.
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````
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````Bash
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python misc/convert_caffe_pretrain.py
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````
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@@ -156,7 +156,7 @@ Some Key arguments:
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you may open browser, type:`http://<ip>:8097` and see the visualization of training procedure as below:
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![visdom](http://7zh43r.com1.z0.glb.clouddn.com/del/visdom-fasterrcnn.png)
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![visdom](http://7zh43r.com2.z0.glb.clouddn.com/del/visdom-fasterrcnn.png)
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## Troubleshooting
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TODO: make it clear

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