Merge pull request #616 from knorth55/fix-args-pretrained-model

args --pretrained_model -> --pretrained-model
chainer · May 25, 2018 · 80f6a9c · 80f6a9c
2 parents 1b480bc + 75b5549
commit 80f6a9c
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Showing 14 changed files with 15 additions and 15 deletions.
diff --git a/examples/classification/README.md b/examples/classification/README.md
@@ -26,7 +26,7 @@ The score is reported using a weight converted from a weight trained by Caffe.
 These scores are obtained using OpenCV backend. If Pillow is used, scores would differ.
 
 ```
-$ python eval_imagenet.py <path_to_val_dataset> [--model vgg16|resnet50|resnet101|resnet152] [--pretrained_model <model_path>] [--batchsize <batchsize>] [--gpu <gpu>] [--crop center|10]
+$ python eval_imagenet.py <path_to_val_dataset> [--model vgg16|resnet50|resnet101|resnet152] [--pretrained-model <model_path>] [--batchsize <batchsize>] [--gpu <gpu>] [--crop center|10]
 ```
 
 

diff --git a/examples/classification/eval_imagenet.py b/examples/classification/eval_imagenet.py
@@ -24,7 +24,7 @@ def main():
     parser.add_argument('val', help='Path to root of the validation dataset')
     parser.add_argument(
         '--model', choices=('vgg16', 'resnet50', 'resnet101', 'resnet152'))
-    parser.add_argument('--pretrained_model', default='imagenet')
+    parser.add_argument('--pretrained-model', default='imagenet')
     parser.add_argument('--gpu', type=int, default=-1)
     parser.add_argument('--batchsize', type=int, default=32)
     parser.add_argument('--crop', choices=('center', '10'), default='center')

diff --git a/examples/detection/README.md b/examples/detection/README.md
@@ -24,7 +24,7 @@ For the details, please check the documents and examples of each model.
 
 You can reproduce these scores by the following command.
 ```
-$ python eval_voc07.py [--model faster_rcnn|ssd300|ssd512|yolo_v2|yolo_v3] [--pretrained_model <model_path>] [--batchsize <batchsize>] [--gpu <gpu>]
+$ python eval_voc07.py [--model faster_rcnn|ssd300|ssd512|yolo_v2|yolo_v3] [--pretrained-model <model_path>] [--batchsize <batchsize>] [--gpu <gpu>]
 ```
 
 ## Visualization of models

diff --git a/examples/detection/eval_voc07.py b/examples/detection/eval_voc07.py
@@ -21,7 +21,7 @@ def main():
         '--model',
         choices=('faster_rcnn', 'ssd300', 'ssd512', 'yolo_v2', 'yolo_v3'),
         default='ssd300')
-    parser.add_argument('--pretrained_model')
+    parser.add_argument('--pretrained-model')
     parser.add_argument('--gpu', type=int, default=-1)
     parser.add_argument('--batchsize', type=int, default=32)
     args = parser.parse_args()

diff --git a/examples/faster_rcnn/README.md b/examples/faster_rcnn/README.md
@@ -27,7 +27,7 @@ Our experiment was conducted on Ubuntu 14.04.5 with Pascal Titan X.
 If a path to pretrained model path is not given, weights distributed on the internet will be used.
 
 ```
-$ python demo.py [--gpu <gpu>] [--pretrained_model <model_path>] <image>.jpg
+$ python demo.py [--gpu <gpu>] [--pretrained-model <model_path>] <image>.jpg
 ```
 
 This example will automatically download a pretrained weights from the internet when executed.

diff --git a/examples/faster_rcnn/demo.py b/examples/faster_rcnn/demo.py
@@ -12,7 +12,7 @@
 def main():
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', type=int, default=-1)
-    parser.add_argument('--pretrained_model', default='voc07')
+    parser.add_argument('--pretrained-model', default='voc07')
     parser.add_argument('image')
     args = parser.parse_args()
 

diff --git a/examples/instance_segmentation/eval_sbd.py b/examples/instance_segmentation/eval_sbd.py
@@ -16,7 +16,7 @@ def main():
     parser.add_argument(
         '--model', choices=('fcis_resnet101'),
         default='fcis_resnet101')
-    parser.add_argument('--pretrained_model')
+    parser.add_argument('--pretrained-model')
     parser.add_argument('--iou-thresh', type=float, default=0.5)
     parser.add_argument('--gpu', type=int, default=-1)
     args = parser.parse_args()

diff --git a/examples/segnet/README.md b/examples/segnet/README.md
@@ -43,7 +43,7 @@ Here is a quick demo using our pretrained weights. The pretrained model is autom
 
 ```
 $ wget https://raw.githubusercontent.com/alexgkendall/SegNet-Tutorial/master/CamVid/test/0001TP_008550.png
-$ python demo.py [--gpu <gpu>] [--pretrained_model <model_path>] 0001TP_008550.png
+$ python demo.py [--gpu <gpu>] [--pretrained-model <model_path>] 0001TP_008550.png
 ```
 
 
@@ -52,7 +52,7 @@ $ python demo.py [--gpu <gpu>] [--pretrained_model <model_path>] 0001TP_008550.p
 The trained weights to replicate the same results as below is here: [model_iteration-16000](https://www.dropbox.com/s/exas66necaqbxyw/model_iteration-16000).
 
 ```
-$ python eval_camvid.py [--gpu <gpu>] [--pretrained_model <model_path>] [--batchsize <batchsize>]
+$ python eval_camvid.py [--gpu <gpu>] [--pretrained-model <model_path>] [--batchsize <batchsize>]
 ```
 
 

diff --git a/examples/segnet/demo.py b/examples/segnet/demo.py
@@ -16,7 +16,7 @@ def main():
 
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', type=int, default=-1)
-    parser.add_argument('--pretrained_model', default='camvid')
+    parser.add_argument('--pretrained-model', default='camvid')
     parser.add_argument('image')
     args = parser.parse_args()
 

diff --git a/examples/segnet/eval_camvid.py b/examples/segnet/eval_camvid.py
@@ -43,7 +43,7 @@ def calc_bn_statistics(model, batchsize):
 def main():
     parser = argparse.ArgumentParser()
     parser.add_argument('--gpu', type=int, default=-1)
-    parser.add_argument('--pretrained_model', type=str, default='camvid')
+    parser.add_argument('--pretrained-model', type=str, default='camvid')
     parser.add_argument('--batchsize', type=int, default=24)
     args = parser.parse_args()
 

diff --git a/examples/ssd/README.md b/examples/ssd/README.md
@@ -15,7 +15,7 @@ Scores are mean Average Precision (mAP) with PASCAL VOC2007 metric.
 ## Demo
 Detect objects in an given image. This demo downloads Pascal VOC pretrained model automatically if a pretrained model path is not given.
 ```
-$ python demo.py [--model ssd300|ssd512] [--gpu <gpu>] [--pretrained_model <model_path>] <image>.jpg
+$ python demo.py [--model ssd300|ssd512] [--gpu <gpu>] [--pretrained-model <model_path>] <image>.jpg
 ```
 
 ## Convert Caffe model

diff --git a/examples/ssd/demo.py b/examples/ssd/demo.py
@@ -15,7 +15,7 @@ def main():
     parser.add_argument(
         '--model', choices=('ssd300', 'ssd512'), default='ssd300')
     parser.add_argument('--gpu', type=int, default=-1)
-    parser.add_argument('--pretrained_model', default='voc0712')
+    parser.add_argument('--pretrained-model', default='voc0712')
     parser.add_argument('image')
     args = parser.parse_args()
 

diff --git a/examples/yolo/README.md b/examples/yolo/README.md
@@ -16,7 +16,7 @@ Similar issue is reported [here](https://github.com/AlexeyAB/darknet#how-to-calc
 ## Demo
 Detect objects in an given image. This demo downloads Pascal VOC pretrained model automatically if a pretrained model path is not given.
 ```
-$ python demo.py [--model yolo_v2|yolo_v3] [--gpu <gpu>] [--pretrained_model <model_path>] <image>.jpg
+$ python demo.py [--model yolo_v2|yolo_v3] [--gpu <gpu>] [--pretrained-model <model_path>] <image>.jpg
 ```
 
 ## Convert Darknet model

diff --git a/examples/yolo/demo.py b/examples/yolo/demo.py
@@ -16,7 +16,7 @@ def main():
         '--model', choices=('yolo_v2', 'yolo_v3'),
         default='yolo_v2')
     parser.add_argument('--gpu', type=int, default=-1)
-    parser.add_argument('--pretrained_model', default='voc0712')
+    parser.add_argument('--pretrained-model', default='voc0712')
     parser.add_argument('image')
     args = parser.parse_args()