小编nsk*_*nsl的帖子

我只有两张图片，一张是当前帧，一张是其他方式计算出来的光流图。

当前帧为：

光流图为：

我的问题是如何使用两幅图像计算前一帧？

我看到了一个解决方案，只是使用双线性插值将当前帧扭曲到具有光流图像的最后一帧。但我不知道该怎么做。

那么，有人能给我一些建议或想法吗？非常感谢。

我已经安装了CUDA 8.0并将cuDNN文件复制到目录中,如安装CUDA(Linux上的GPU)所示.

我运行mnist_cnn.py并获得以下信息:

Using TensorFlow backend.
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] Couldn't open CUDA library libcudnn.so. LD_LIBRARY_PATH: 
I tensorflow/stream_executor/cuda/cuda_dnn.cc:3448] Unable to load cuDNN DSO
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally
X_train shape: (60000, 28, 28, 1)
60000 train samples

最后

Traceback (most recent call last):
  File "mnist_cnn.py", line 65, in <module>
    model.add(Dropout(0.25))
  File "/home/nsknsl/.local/lib/python3.5/site-packages/keras/models.py", line …

我在caffe上按照步骤操作，并更改了配置文件：

PYTHON_LIBRARIES := boost_python3 python3.5m PYTHON_INCLUDE :=
/usr/include/python3.5m \
                /usr/lib/python2.7/dist-packages/numpy/core/include"

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include 
/usr/include/hdf5/serial/ LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib
/usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/

然后做了：

make all
make test
make runtest

这些运行正常。但是当我跑步时：

make pycaffe

我收到一个错误：

CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp

/usr/bin/ld: cannot find -lboost_python3

collect2: error: ld returned 1 exit status Makefile:507: recipe for
target 'python/caffe/_caffe.so' failed make: ***
[python/caffe/_caffe.so] Error 1

我怎么解决这个问题？