panmari

channels = 32
img_size = 128

W_conv1 = weight_variable([5, 5, 1, channels])
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1))
# Produces a tensor of size [-1, img_size, img_size, channels]

## Prepare for visualization
# Take only convolutions of first image, discard convolutions for other images.
V = tf.slice(h_conv1, (0, 0, 0, 0), (1, -1, -1, -1), name='slice_first_input')

panmari

import tensorflow as tf
import copy

epochs = 5
filename_seed = 4
capacity = 32
batch_size = 255

import string
import random

panmari

require 'benchmark'

# Disable logging if in development/test mode
ActiveRecord::Base.logger = nil

model_name = Icd
N = 100

Benchmark.bm(11) do |x|
  x.report('ruby rand') { N.times { model_name.offset(rand(model_name.count)).first } }

panmari

# Benchmarks for images with 6 channels.
# Full command line:
# bazel run -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda tensorflow/core/kernels:resize_benchmark_test_gpu -- --benchmarks=..
BEFORE
Benchmark                                        Time(ns) Iterations
--------------------------------------------------------------------
BM_Resize_ResizeNearestNeighbor_cpu_10_499_499   50546710        100	 295.6M items/s
BM_Resize_ResizeNearestNeighbor_gpu_10_499_499    9572830        100	 1560.7M items/s
BM_Resize_ResizeBilinear_cpu_10_499_499          64680780        100	 231.0M items/s
BM_Resize_ResizeBilinear_gpu_10_499_499          11350100        100	 1316.3M items/s

panmari

General tips

• Install the source/javadoc for eclipse built in documentation (right click on project -> Maven -> download source).
• Manually add the documentation for vecmath (simple project -> maven dependancies -> vecmath-1.3.1.jar rightclick -> properties -> add http://download.java.net/media/java3d/javadoc/1.5.0/ under javadoc location path.

Linux

Nvidia graphics card

panmari

# try this in a rails environment, that has the Indexing module loaded. (medcode, orangeproton)
search_queries = ["Ein sehr komplizierter query, der sehr lange zum ausfuhren braucht", "kurz"] # !sic
threads = []

search_queries.each do |string|
    threads << Thread.new(string) do |query|
        puts "started #{query}"
        Indexing.elastic_find_all(string, 'icd', '2012', 'ch', 'de')
        puts "finished #{query}"
    end

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/usr/bin/cmake -H/home/panmari/oiio -B/home/panmari/oiio/build --check-build-system CMakeFiles/Makefile.cmake 0
/usr/bin/cmake -E cmake_progress_start /home/panmari/oiio/build/CMakeFiles /home/panmari/oiio/build/CMakeFiles/progress.marks
make -f CMakeFiles/Makefile2 all
make[1]: Entering directory '/home/panmari/oiio/build'
make -f src/libutil/CMakeFiles/OpenImageIO_Util.dir/build.make src/libutil/CMakeFiles/OpenImageIO_Util.dir/depend
make[2]: Entering directory '/home/panmari/oiio/build'
cd /home/panmari/oiio/build && /usr/bin/cmake -E cmake_depends "Unix Makefiles" /home/panmari/oiio /home/panmari/oiio/src/libutil /home/panmari/oiio/build /home/panmari/oiio/build/src/libutil /home/panmari/oiio/build/src/libutil/CMakeFiles/OpenImageIO_Util.dir/DependInfo.cmake --color=
make[2]: Leaving directory '/home/panmari/oiio/build'
make -f src/libutil/CMakeFiles/OpenImageIO_Util.dir/build.make src/libutil/CMakeFiles/OpenImageIO_Util.dir/build
make[2]: Entering directory '/home/panmari/oiio/build'

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# This is the CMakeCache file.
# For build in directory: /home/panmari/oiio/build
# It was generated by CMake: /usr/bin/cmake
# You can edit this file to change values found and used by cmake.
# If you do not want to change any of the values, simply exit the editor.
# If you do want to change a value, simply edit, save, and exit the editor.
# The syntax for the file is as follows:
# KEY:TYPE=VALUE
# KEY is the name of a variable in the cache.
# TYPE is a hint to GUIs for the type of VALUE, DO NOT EDIT TYPE!.

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# Using opencv for borderless cloning.
import cv2
import numpy as np

# Read images : src image will be cloned into dst
im_filename = "wolf.jpg"
im = cv2.imread(im_filename)
obj= cv2.flip(cv2.imread("hamster.jpg"), 1)
mask = cv2.flip(cv2.imread("hamster_mask.png"), 1)
mask = cv2.cvtColor(mask, cv2.COLOR_RGB2GRAY)

panmari

OpenCV version: 3.0.0-dev
OpenCV VCS version: 3.0.0-556-g33f5ac5
Build type: release
Parallel framework: pthreads
CPU features: mmx sse sse2 sse3
OpenCL Platforms: 
    NVIDIA CUDA
        dGPU: GeForce GTX TITAN (OpenCL 1.2 CUDA)
Current OpenCL device: 
    Type = dGPU