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invokesus / nao_call.py
Last active November 17, 2018 05:13
import os
import naoqi
import sys
from naoqi import ALProxy
IP = ""
PORT = ""
try:
@invokesus
invokesus / exec_bin.py
Last active November 17, 2018 05:13
import os.path
import time
from json import loads
from darkflow.net.build import TFNet
import cv2
options = {"model": "cfg/yolo.cfg", "load": "bin/yolo.weights", "threshold": 0.5, "gpu": 1.0}
tfnet = TFNet(options)
initial_file_name = 0
@invokesus
invokesus / metadata.csv
Last active November 13, 2018 16:51
id gender age_group designation education
1 male <30 junior high school
2 female >50 leader mba
3 female 31-40 leader mba
4 female 31-40 leader mba
5 female 41-50 senior undergrad
6 female >50 executive postgrad
7 male 31-40 senior mba
8 female 31-40 senior undergrad
9 male <30 senior undergrad
@invokesus
invokesus / accelerometer.json
Created October 20, 2018 09:55
{
"data": [{
"t": 1539415804029,
"x": -0.586273193359375,
"y": -0.260101318359375,
"z": 9.895584106445312
}, {
"t": 1539415804229,
"x": -0.710693359375,
"y": -0.41802978515625,
@invokesus
invokesus / processedTrees.json
Created October 20, 2018 08:32
[{"name":"area","nodes":[{"_children":[1],"_data":{"url":"data/unemployment-across-industries.json","format":{"type":"json"}},"id":0,"nodetype":"SourceNode"},{"_children":[2],"_parent":0,"_parse":{"date":"date","count":"number"},"id":1,"nodetype":"ParseNode"},{"_children":[3],"_parent":1,"formula":{"yearmonth_date":{"as":"yearmonth_date","timeUnit":"yearmonth","field":"date"}},"id":2,"nodetype":"TimeUnitNode"},{"_children":[4],"_parent":2,"dimensions":{"yearmonth_date":true},"measures":{"count":{"sum":"sum_count"}},"id":3,"nodetype":"AggregateNode"},{"debugName":"main","_children":[],"_parent":3,"type":"main","refCounts":{"main":3,"raw":0},"_name":"main","_source":"main","id":4,"nodetype":"OutputNode"}],"links":[{"id":"0_1","source":0,"target":1},{"id":"1_2","source":1,"target":2},{"id":"2_3","source":2,"target":3},{"id":"3_4","source":3,"target":4}]},{"name":"area_cumulative_freq","nodes":[{"_children":[1],"_data":{"url":"data/movies.json","format":{"type":"json"}},"id":0,"nodetype":"SourceNode"},{"_children
@invokesus
invokesus / dropconnect.csv
Created September 15, 2018 16:53
Step Time Epoch Loss Accuracy Validation_Loss Validation_Accuracy
200 18.180 010 2.3127412 0.198798 2.185596 0.29998199999999997
400 17.945 020 1.7837568 0.39555599999999996 1.7554249999999998 0.397494
600 18.158 030 1.548939 0.462162 1.3889344 0.622506
800 18.191 040 1.3079864 0.601494 1.2300176 0.6450480000000001
1000 18.109 050 1.0739526 0.6424980000000001 1.095885 0.660042
1200 18.344 060 0.9850274000000001 0.70482 0.9817933999999999 0.69003
1400 18.393 070 0.737107 0.759288 0.936782 0.6375
1600 18.466 080 0.6657532 0.7723439999999999 0.865389 0.7274639999999999
1800 18.574 090 0.5206152000000001 0.83691 0.8054522 0.750006
@invokesus
invokesus / model4.csv
Created September 10, 2018 22:40
Step Time Epoch Loss Accuracy Validation_Loss Validation_Accuracy
200 24.382 010 2.30355 0.2032 2.10794 0.2941
400 24.266 020 1.81161 0.3971 1.86578 0.3162
600 24.366 030 1.41484 0.5317 1.27272 0.5662
800 24.365 040 1.20015 0.5952 1.14674 0.6544
1000 24.563 050 1.03396 0.6639 1.08285 0.6471
1200 24.644 060 0.83834 0.7371 1.03589 0.6397
1400 24.551 070 0.70238 0.7784 0.87082 0.7353
1600 24.811 080 0.68126 0.7802 0.97635 0.6838
1800 24.742 090 0.50884 0.8427 0.78722 0.7647
@invokesus
invokesus / model3.csv
Created September 10, 2018 22:38
Step Time Epoch Loss Accuracy Validation_Loss Validation_Accuracy
200 18.180 010 2.35994 0.1949 2.23020 0.2941
400 17.945 020 1.82016 0.3878 1.79125 0.3897
600 18.158 030 1.58055 0.4531 1.41728 0.6103
800 18.191 040 1.33468 0.5897 1.25512 0.6324
1000 18.109 050 1.09587 0.6299 1.11825 0.6471
1200 18.344 060 1.00513 0.6910 1.00183 0.6765
1400 18.393 070 0.75215 0.7444 0.95590 0.6250
1600 18.466 080 0.67934 0.7572 0.88305 0.7132
1800 18.574 090 0.53124 0.8205 0.82189 0.7353
@invokesus
invokesus / model2.csv
Created September 10, 2018 22:37
Step Time Epoch Loss Accuracy Validation_Loss Validation_Accuracy
200 18.144 010 2.18292 0.2485 2.04492 0.2868
400 18.193 020 1.67891 0.4755 1.69865 0.3750
600 18.246 030 1.62197 0.5297 1.40128 0.5221
800 18.443 040 1.14746 0.6103 1.30761 0.5882
1000 18.256 050 0.96806 0.6662 1.13990 0.6397
1200 18.281 060 0.77709 0.7608 1.09431 0.5809
1400 18.808 070 0.69050 0.7918 0.99878 0.6397
@invokesus
invokesus / model1.csv
Created September 10, 2018 22:27
Step Time Epoch Loss Accuracy Validation_Loss Validation_Accuracy
200 55.955 010 1.91523 0.3506 1.74671 0.4779
400 55.965 020 1.49748 0.5097 1.31340 0.5882
600 55.085 030 1.07349 0.6599 1.06813 0.5882
800 56.277 040 0.98565 0.6910 0.89610 0.6912
1000 56.289 050 1.05948 0.7457 0.77642 0.7574
1200 56.707 060 0.57501 0.8147 0.75292 0.7279
1400 57.118 070 0.41966 0.8882 0.68322 0.7794
1600 57.114 080 0.44839 0.9001 0.72408 0.7721