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| ## 数据准备 | ||
| 模型使用timofte作为训练任务的数据,使用set5或set14作为验证任务的数据。 | ||
| 数据存放结构如下: |
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需要给出数据下载脚本,保证新手可以方便下载到数据,
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需要给出数据下载脚本,保证新手可以方便下载到数据,
已添加,数据集暂无公开的下载链接,所以上传到百度云。
fluid/SRCNN/README.md
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| 下图是使用`infer.py`脚本预测产生的结果示例,其中,第一行是输入的原始图片,第二行是输入图片经过subsample的结果,第三行是超分辨率重构的结果。 | ||
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建议将图片放到当前repo下。
已添加到当前repo下
fluid/SRCNN/infer.py
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| add_arg('checkpoint_path', str, 'model', "Checkpoint save path.") | ||
| add_arg('image_path', str, 'data/val_dataset/set5/baby_GT.bmp', "Img data path.") | ||
| add_arg('show_img', bool, True, "show img or not") |
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默认不要窗口展示图片了,一般用的环境默认没有UI.
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默认不要窗口展示图片了,一般用的环境默认没有UI.
默认设置为False,并修改了这个参数不生效的bug
fluid/SRCNN/train.py
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| def net(X, Y, model_struct): | ||
| # construct net | ||
| conv1 = fluid.layers.nn.conv2d(X, model_struct.n1, model_struct.f1, act='relu', name='conv1' , |
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fluid.layers.nn.conv2d -> fluid.layers.conv2d
可以不用nn
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fluid.layers.nn.conv2d -> fluid.layers.conv2d
可以不用nn
已修改API
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稍后我们会将该工作merge到contribute目录。 |
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pancreatic-cystic-lesion
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This is the model of the super-resolution domain, and I'm glad to see the implementation code, but please update the data download link
| ## 数据准备 | ||
| 模型使用timofte作为训练任务的数据,使用set5或set14作为验证任务的数据。数据集获取难度较大,可以通过下面的下载地址下载: | ||
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| 链接:https://pan.baidu.com/s/1rynLdqzsbyPamJnKOIwNiA |
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The link has expired, please update
add SRCNN code and README.md