| import tensorflow as tf | |
| from tensorflow.keras import layers | |
| from tensorflow.keras.models import Model | |
| from tensorflow.keras.callbacks import Callback, History, LearningRateScheduler | |
| import tensorflow.keras.backend as K | |
| from tensorflow.contrib.tpu.python.tpu import keras_support | |
| from train1000 import cifar10 | |
| import numpy as np | |
| from sklearn.metrics.pairwise import cosine_similarity |
| layers { | |
| name: "frames_input_layer" | |
| type: MEMORY_DATA | |
| top: "frames" | |
| top: "dummy1" | |
| memory_data_param { | |
| batch_size: 32 | |
| channels: 4 | |
| height: 84 | |
| width: 84 |
| namespace { | |
| const int MAX_DETS = 5; | |
| const float SCALE_FACTOR = 1.1f; | |
| const float STRIDE_FACTOR = 0.1f; | |
| const float QUALITY_THRESH = 10.0f; | |
| const float ANGLE_STEP = 45.0f; | |
| } |
| #!/bin/bash | |
| # Install Spark on CentOS 7 | |
| yum install java -y | |
| java -version | |
| yum install wget -y | |
| wget http://downloads.typesafe.com/scala/2.11.7/scala-2.11.7.tgz | |
| tar xvf scala-2.11.7.tgz | |
| sudo mv scala-2.11.7 /usr/lib | |
| sudo ln -s /usr/lib/scala-2.11.7 /usr/lib/scala |
| name: "VGG_VOC0712_SSD_300x300_train" | |
| layer { | |
| name: "data" | |
| type: "AnnotatedData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { |
| #!/bin/bash | |
| TARGET_NAME="libjpeg-turbo" | |
| TARGET_VERSION="1.5.1" # change this to libjpeg-turbo version you need | |
| IOS_SDK_VERSION=10.3 # change this to match current Xcode SDK version | |
| IOS_SDK_MIN_VERSION=8.0 | |
| IOS_PLATFORM_BASE="/Applications/Xcode.app/Contents/Developer/Platforms" | |
| cd `dirname $0` |
The tutorial Use OpenCL in Android camera preview based CV application show us how we can use the Transparent API to dramatically increase the performance of some expensive operations.
The first step in order to be able to execute the tutorial example is to re-compile opencv with the correct flags:
# Export your NDK, it will be looked for OpenCV to compile your project. In my case
export ANDROID_NDK=~/graffter/libs/android-ndk-r10d/
# Download the necessary code
| #!/bin/sh | |
| # Set CPU to full performance on NVIDIA Jetson TK1 Development Kit | |
| if [ $(id -u) != 0 ]; then | |
| echo "This script requires root permissions" | |
| echo "$ sudo "$0"" | |
| exit | |
| fi | |
| # To obtain full performance on the CPU (eg: for performance measurements or benchmarking or when you don't care about power draw), you can disable CPU scaling and force the 4 main CPU cores to always run at max performance until reboot: |
| #!/bin/bash | |
| set -e | |
| # Put | |
| # 1. CUDA installation script (cuda_*.run, see https://developer.nvidia.com/cuda-downloads) | |
| # 2. cuDNN archive (cudnn-*.tgz, see https://developer.nvidia.com/rdp/cudnn-download) | |
| # 3. Intel MKL archive (l_mkl_*.tgz, see https://software.intel.com/en-us/intel-mkl) | |
| # under $HOME | |
| # Also set INTEL_MKL_SN to Intel MKL's serial number (XXXX-XXXXXXXX) |