社区
VCL组件使用和开发
帖子详情
3D Shapes /Shapes /3D Layers
bianchenghaonan
2012-05-09 09:18:16
请问各位大哥。3D Shapes /Shapes /3D Layers是什么控件。我再xe2中看到了。可是在c++builder中不能使用。请问这个是用在哪里的??
...全文
82
1
打赏
收藏
3D Shapes /Shapes /3D Layers
请问各位大哥。3D Shapes /Shapes /3D Layers是什么控件。我再xe2中看到了。可是在c++builder中不能使用。请问这个是用在哪里的??
复制链接
扫一扫
分享
转发到动态
举报
写回复
配置赞助广告
用AI写文章
1 条
回复
切换为时间正序
请发表友善的回复…
发表回复
打赏红包
我不懂电脑
2012-05-10
打赏
举报
回复
还没用过xe2
北大去雨算法python版
去雨算法的PYTHON实现, Rain streaks can severely degrade the visibility, which causes many current computer vision algorithms fail to work. So it is necessary to remove the rain from images. We propose a novel deep network architecture based on deep convolutional and recurrent neural networks for single image deraining. As contextual information is very important for rain removal, we first adopt the dilated convolutional neural network to acquire large receptive field. To better fit the rain removal task, we also modify the network. In heavy rain, rain streaks have various directions and
shapes
, which can be regarded as the accumulation of multiple rain streak
layer
s. We assign different alpha-values to various rain streak
layer
s according to the intensity and transparency by incorporating the squeeze-and-excitation block. Since rain streak
layer
s overlap with each other, it is not easy to remove the rain in one stage. So we further decompose the rain removal into multiple stages. Recurrent neural network is incorporated to preserve the useful information in previous stages and benefit the rain removal in later stages. We conduct extensive experiments on both synthetic and real-world datasets. Our proposed method outperforms the state-of-the-art approaches under all evaluation metrics.
CAFFE: Developing new
layer
s
Developing new
layer
s Add a class declaration for your
layer
to include/caffe/
layer
s/your_
layer
.hpp. Include an inline implementation of type overriding the method virtual inline const char* t
Negative dimension size caused by subtracting 2 from 1 for ‘{{node fcinn/fgcnn_
layer
s/max_pooling2d_
ValueError: Negative dimension size caused by subtracting 2 from 1 for '{{node fcinn/fgcnn_
layer
s/max_pooling2d_3/MaxPool}} = MaxPool[T=DT_FLOAT, data_format="NHWC", ksize=[1, 2, 1, 1], padding="VALID", strides=[1, 2, 1, 1]](fcinn/fgcnn_
layer
s/conv2d_3/T
Learning a Probabilistic Latent Space of Object
Shapes
via
3D
Generative-Adversarial Modeling
This repository contains pre-trained models and sampling code for the
3D
Generative Adversarial Network (
3D
-GAN) presented at NIPS 2016.http://
3d
gan.csail.mit.eduPrerequisites论文介绍
3D
-GAN which generates
ValueError: "concat" mode can only merge
layer
s with matching output
shapes
except for the concat
在keras中merge([x1, x2], mode=’concat’, concat_axis=channel_axis)时报了如下一个错Traceback (most recent call last): File "F:/visual/SSsearch/ineptionV4.py", line 215, in
model = create_model(5)
VCL组件使用和开发
602
社区成员
13,459
社区内容
发帖
与我相关
我的任务
VCL组件使用和开发
C++ Builder VCL组件使用和开发
复制链接
扫一扫
分享
社区描述
C++ Builder VCL组件使用和开发
社区管理员
加入社区
获取链接或二维码
近7日
近30日
至今
加载中
查看更多榜单
社区公告
暂无公告
试试用AI创作助手写篇文章吧
+ 用AI写文章