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!11806 fix spelling

From: @wukesong
Reviewed-by: @wuxuejian,@oacjiewen
Signed-off-by: @wuxuejian
tags/v1.2.0-rc1
mindspore-ci-bot Gitee 4 years ago
parent
commit
c6ce72713a
4 changed files with 5 additions and 5 deletions
  1. +1
    -1
      model_zoo/official/cv/simple_pose/README.md
  2. +1
    -1
      model_zoo/official/cv/simple_pose/src/dataset.py
  3. +1
    -1
      model_zoo/official/cv/tinydarknet/README_CN.md
  4. +2
    -2
      model_zoo/official/cv/tinydarknet/train.py

+ 1
- 1
model_zoo/official/cv/simple_pose/README.md View File

@@ -139,7 +139,7 @@ The structure of the files in this repository is shown below.
│ ├─ network_define.py // define loss
│ └─ predict.py // predict keypoints from heatmaps
├─ eval.py // evaluation script
├─ param_convert.py // model parameters convertion script
├─ param_convert.py // model parameters conversion script
├─ train.py // training script
└─ README.md // descriptions about this repository
```


+ 1
- 1
model_zoo/official/cv/simple_pose/src/dataset.py View File

@@ -47,7 +47,7 @@ class KeypointDatasetGenerator:
self.rotation_factor = cfg.DATASET.ROT_FACTOR
self.flip = cfg.DATASET.FLIP

# dataset informations
# dataset information
self.db = []
self.is_train = is_train



+ 1
- 1
model_zoo/official/cv/tinydarknet/README_CN.md View File

@@ -55,7 +55,7 @@ Tiny-DarkNet是Joseph Chet Redmon等人提出的一个16层的针对于经典的

<!-- # [Features](#contents)

## [Distrubuted](#contents)
## [Distributed](#contents)

<!-- 不同的机器有同一个模型的多个副本,每个机器分配到不同的数据,然后将所有机器的计算结果按照某种方式合并 -->



+ 2
- 2
model_zoo/official/cv/tinydarknet/train.py View File

@@ -73,7 +73,7 @@ if __name__ == '__main__':
if args_opt.dataset_name == "imagenet":
cfg = imagenet_cfg
else:
raise ValueError("Unsupport dataset.")
raise ValueError("Unsupported dataset.")
# set context
device_target = cfg.device_target
@@ -97,7 +97,7 @@ if __name__ == '__main__':
if args_opt.dataset_name == "imagenet":
dataset = create_dataset_imagenet(cfg.data_path, 1)
else:
raise ValueError("Unsupport dataset.")
raise ValueError("Unsupported dataset.")
batch_num = dataset.get_dataset_size()


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