Flumotion is a streaming media server created with the backing of Fluendo. It features intuitive graphical administration tools, making the task of setting up and manipulating audio and video streams easy for even novice system administrators. Flumotion is released under the GPL.
This presentation was given as a scheduled talk at PyCon UK 2007. The material presented covered the following subjects: * Generating code from user interface descriptions with pyuic4 * Connecting signals and slots using auto-connection * Creating custom widgets with PyQt4 for use in Qt Designer
From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures.
PyAMG is a library of Algebraic Multigrid (AMG) solvers with a convenient Python interface. What is AMG?¶ AMG is a multilevel technique for solving large-scale linear systems with optimal or near-optimal efficiency. Unlike geometric multigrid, AMG requires little or no geometric information about the underlying problem and develops a sequence of coarser grids directly from the input matrix. This feature is especially important for problems discretized on unstructured meshes and irregular grids.
Mat estimateRigidTransform(const Mat& srcpt, const Mat& dstpt, bool fullAffine)¶ Computes optimal affine transformation between two 2D point sets Parameters: * srcpt – The first input 2D point set * dst – The second input 2D point set of the same size and the same type as A * fullAffine – If true, the function finds the optimal affine transformation with no any additional resrictions (i.e. there are 6 degrees of freedom); otherwise, the class of transformations to choose from is limited to combinations of translation, rotation and uniform scaling (i.e. there are 5 degrees of freedom) The function finds the optimal affine transform [A|b] (a 2 \times 3 floating-point matrix) that approximates best the transformation from \texttt{srcpt}_i to \texttt{dstpt}_i : [A^*|b^*] = arg \min _{[A|b]} \sum _i \| \texttt{dstpt} _i - A { \texttt{srcpt} _i}^T - b \| ^2 where [A|b] can be either arbitrary (when fullAffine=true ) or have form