yptheangel

1. iterate through rows of a dataframe

for index, row in df.iterrows():
    print(row['yourcolumnkey1'], row['yourcolumnkey2'])

yptheangel

my GCP cheatsheet

1. check google bucket total size
   gsutil -m du -hs gs://<yourbucketname>
2. check individual file size
   gsutil -m du -h gs://<yourbucketname>

yptheangel

0. Create your script,"script.sh" e.g.

#!/bin/bash

cd /home/wilson/opencv-starter-pack/python/basic
python open_video.py

1. Create your own service, .e.g

yptheangel

#!/bin/bash
#
# rotate_desktop.sh
#
# Rotates modern Linux desktop screen and input devices to match. Handy for
# convertible notebooks. Call this script from panel launchers, keyboard
# shortcuts, or touch gesture bindings (xSwipe, touchegg, etc.).
#
# Using transformation matrix bits taken from:
#   https://wiki.ubuntu.com/X/InputCoordinateTransformation

yptheangel

#!/bin/bash
#
# rotate_desktop.sh
#
# Rotates modern Linux desktop screen and input devices to match. Handy for
# convertible notebooks. Call this script from panel launchers, keyboard
# shortcuts, or touch gesture bindings (xSwipe, touchegg, etc.).
#
# Using transformation matrix bits taken from:
#   https://wiki.ubuntu.com/X/InputCoordinateTransformation

yptheangel

import serial
import serial.tools.list_ports as port_list


ports = list(port_list.comports())
print(ports[0].device)
port = ports[0].device
baudrate = 9600
serialPort = serial.Serial(port=port, baudrate=baudrate,
                                bytesize=8, timeout=1, stopbits=serial.STOPBITS_ONE)

yptheangel

sudo apt-get install build-essential pkg-config libtbb2 libtbb-dev libavcodec-dev libavformat-dev libswscale-dev libtiff-dev libjpeg-dev libpng-dev libxvidcore-dev libavresample-dev libcanberra-gtk-module libcanberra-gtk3-module libv4l-dev libdc1394-22-dev 

yptheangel

class PNet(nn.Module):
    """MTCNN PNet.

    Keyword Arguments:
        pretrained {bool} -- Whether or not to load saved pretrained weights (default: {True})
    """

    def __init__(self, pretrained=True):
        super().__init__()

yptheangel

import numpy as np

a = np.array(["1","2","3"])
print(a)
print(type(a))
a=a[1:]
print(a)
print(len(a))
a=np.append(a,1)
print(a)

yptheangel

import org.datavec.api.io.filters.BalancedPathFilter;
import org.datavec.api.io.labels.ParentPathLabelGenerator;
import org.datavec.api.split.FileSplit;
import org.datavec.api.split.InputSplit;
import org.datavec.image.loader.BaseImageLoader;
import org.datavec.image.recordreader.ImageRecordReader;
import org.datavec.image.transform.*;
import org.deeplearning4j.api.storage.StatsStorage;
import org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator;
import org.deeplearning4j.nn.conf.layers.DenseLayer;