I hereby claim:
- I am markroxor on github.
- I am markroxor (https://keybase.io/markroxor) on keybase.
- I have a public key whose fingerprint is 88E6 23D1 6F92 29B0 0EBC 60E1 9A40 0A69 45E9 1AA6
To claim this, I am signing this object:
import urllib2 | |
import json | |
import pickle | |
import time | |
while True: | |
response = urllib2.urlopen('http://122.252.246.246:8081/MMTSLiveeng.html') | |
html = response.read() |
I hereby claim:
To claim this, I am signing this object:
running install | |
running bdist_egg | |
running egg_info | |
writing requirements to gensim.egg-info/requires.txt | |
writing gensim.egg-info/PKG-INFO | |
writing top-level names to gensim.egg-info/top_level.txt | |
writing dependency_links to gensim.egg-info/dependency_links.txt | |
reading manifest file 'gensim.egg-info/SOURCES.txt' | |
reading manifest template 'MANIFEST.in' | |
warning: no files found matching 'COPYING.LESSER' |
Coding/gensim [TF*] » python tftest.py | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally | |
E tensorflow/stream_executor/cuda/cuda_driver.cc:509] failed call to cuInit: CUDA_ERROR_NO_DEVICE | |
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:158] retrieving CUDA diagnostic information for host: thehive | |
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname: thehive | |
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported version is: 367.57.0 |
Coding/gensim [TF*] » python tftest.py | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally | |
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally | |
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero | |
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: | |
name: GeForce GTX 1060 3GB | |
major: 6 minor: 1 memoryClockRate (GHz) 1.797 |
--------------------------------------------------- | |
constituent[0]: file:/usr/share/maven/lib/eclipse-aether-connector-basic.jar | |
constituent[1]: file:/usr/share/maven/lib/maven-repository-metadata-3.x.jar | |
constituent[2]: file:/usr/share/maven/lib/maven-artifact-3.x.jar | |
constituent[3]: file:/usr/share/maven/lib/plexus-sec-dispatcher.jar | |
constituent[4]: file:/usr/share/maven/lib/slf4j-api.jar | |
constituent[5]: file:/usr/share/maven/lib/plexus-component-annotations.jar | |
constituent[6]: file:/usr/share/maven/lib/maven-core-3.x.jar | |
constituent[7]: file:/usr/share/maven/lib/commons-lang3.jar | |
constituent[8]: file:/usr/share/maven/lib/maven-builder-support-3.x.jar |
import urllib # URL functions | |
import urllib2 # URL functions | |
# Set YOUR TextLocal username | |
username = '[email protected]' | |
# Set YOUR unique API hash | |
# It is available from the docs page | |
# https://control.txtlocal.co.uk/docs/ |
//(҂>_<) | |
//<,︻╦╤─ ҉ ---- -M-A-R-K-!!!-R-O-X-O-R- ------ | |
// /﹋\" BRATATATATATAT!! | |
#include<bits/stdc++.h> | |
#include<iostream> | |
#include<algorithm> | |
//#include<stdio.h> | |
#include<time.h> |
from detectionFunction import fingerCount | |
import thread,threading,time,cv2 | |
from multiprocessing.pool import ThreadPool | |
pool = ThreadPool(processes=1) | |
cap = cv2.VideoCapture(0) | |
# cap = 1 | |
async_result = pool.apply_async(fingerCount, (cap,1, )) # tuple of args for foo |
import cv2,pygame | |
from detectionFunction import fingerCount | |
capture = cv2.VideoCapture(0) | |
k = fingerCount(capture,2) | |
print k | |
pygame.time.wait(3000) |