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| import numpy as np | |
| dist1 = np.array([6.391326314769685e-05, 0.05027947947382927,\ | |
| 0.10930796712636948, 0.24019761383533478, 0.30929023027420044,\ | |
| 0.169674351811409, 0.07713371515274048, 0.036470066756010056,\ | |
| 0.007540848571807146, 4.184951467323117e-05]) | |
| dist2 = np.array([0.1]*10) | |
| # weighted mean |
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| #!/usr/bin/env python | |
| from setuptools import setup, find_packages | |
| # https://svn.python.org/projects/sandbox/trunk/setuptools/setuptools.txt | |
| # ls /Users/vkajjam/miniconda3/envs/feature_engineering/lib/python3.7/site-packages/ | |
| setup( | |
| name="color profiler", | |
| version="0.0.1", | |
| description="color profiler app.", |
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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import numpy as np | |
| d = 64 # dimension | |
| nb = 100000 # database size | |
| nq = 10000 # nb of queries |
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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| #!/usr/bin/env python2 | |
| from __future__ import print_function | |
| import os | |
| import time |
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| from concurrent.futures import ThreadPoolExecutor | |
| import csv | |
| import numpy as np | |
| from functools import partial | |
| import random | |
| import threading | |
| import time | |
| filename = 'lock_writes.csv' | |
| def thread_function(lock, id): |
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| #!/bin/bash | |
| # kernel-version: | |
| echo "Kernel version: $(uname -r)" | |
| # kernel-release: | |
| echo "Kernel release: $(uname -v)" | |
| # operating-system: | |
| echo "Operationg System: $(uname -o)" |
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| # https://github.com/tensorflow/models/issues/5348#issuecomment-423634084 | |
| The model_train.py combined train.py and eval.py | |
| in ole version and find that: | |
| 1 Add tf.logging.set_verbosity(tf.logging.INFO) after the import section of the model_main.py script. It will display a summary after every 100th step. Maybe model_train.py forget it officially. | |
| 2 As for the warning like WARNING:tensorflow:Ignoring ground truth with image id 283094706 since it was previously added, if you set anyone of the arg in --num_eval_steps=200 or the num_examples in .config file | |
| eval_config: { num_examples: 200 max_evals: 10 } | |
| larger than the numbers of your test images in you datasets. Then it will show the warning. So just set them as the test images num will be ok. |
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| mkdir -p ~/catkin_ws/src | |
| cd ~/catkin/src | |
| catkin_init_workspace | |
| cd ~/catkin | |
| catkin_make | |
| ls | |
| cd ~/catkin_ws/src | |
| $ git clone https://github.com/udacity/simple_arm_01.git simple_arm | |
| cd ~/catkin |
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| minikube version | |
| minikube start | |
| kubectl version | |
| kubectl cluster-info | |
| kubectl get nodes | |
| # Deploying app example 1 | |
| kubectl run kubernetes-bootcamp --image=gcr.io/google-samples/kubernetes-bootcamp:v1 --port=8080 | |
| kubectl get deployments |
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| source 'http://rubygems.org' | |
| gem 'rails', '3.0.10' | |
| gem 'mysql2', '< 0.3' | |
| gem 'paperclip' | |
| gem 'rake' | |
| # Use unicorn as the web server |
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