skipperkongen

Keybase proof

I hereby claim:

• I am skipperkongen on github.
• I am skipperkongen (https://keybase.io/skipperkongen) on keybase.
• I have a public key ASBjntm9D5V5uVtiIAogJKMeTmVedwh69aRp5p1fLzPqxQo

To claim this, I am signing this object:

skipperkongen

select 
    year(dt) as departure_year, 
    weekofyear(dt) as departure_week
from (
    select date_add(current_date(), x)  as dt
    from `table_that_contains_integers_0_to_n_as_x`
    where x % 7 = 0
)
order by dt

skipperkongen

from matplotlib import pyplot as plt
import numpy as np

a = np.random.randn(10,10)
plt.imshow(a, cmap='gray')

skipperkongen

%matplotlib inline
import networkx as nx
from networkx.algorithms import bipartite
from networkx.algorithms import community
from matplotlib import pyplot as plt

G = bipartite.gnmk_random_graph(3,5,10)
top = nx.bipartite.sets(G)[0]
pos = nx.bipartite_layout(G, top)
nx.draw_networkx(G,pos)

skipperkongen

# pip install icrawler
from icrawler.builtin import GoogleImageCrawler
import argparse

if __name__=='__main__':

    parser = argparse.ArgumentParser(description='Scrape some images.')
    parser.add_argument('keywords', metavar = 'KEYWORDS', nargs = '+',
        help='keywords to download images for')
    parser.add_argument('-n', '--max-num', type = int, default = 10,

skipperkongen

# Infer on live video
from math import ceil
import subprocess
import cv2

TEST_FRAMES = 500

# Initialize camera
cap = cv2.VideoCapture(0)
# Check if camera opened successfully

skipperkongen

from keras.models import Sequential, load_model
from keras.layers import Dense, Activation, Dropout
from sklearn.model_selection import train_test_split
from sklearn.metrics import f1_score

MODEL_PATH='model.h5'
EPOCHS = 10
HIDDEN_SIZE = 16

model = Sequential()

skipperkongen

# Create X, y series
import cv2
import numpy as np
from keras.preprocessing import image
from keras.applications.vgg16 import VGG16
from keras.applications.vgg16 import preprocess_input

class VGGFramePreprocessor():
    
    def __init__(self, vgg_model):

skipperkongen

import cv2
from time import sleep

CLASSES = ['SAFE', 'DANGER']
NEG_IDX = 0
POS_IDX = 1
FRAMES_PER_VIDEO = 100
VIDEOS_PER_CLASS = 2

def capture(num_frames, path='out.avi'):

skipperkongen

// Load two data paths
val df1 = spark.read.load("/path/to/data1") // e.g. parquet files
val df2 = spark.read.load("/path/to/data2") // e.g. parquet files


// Union into single dataframe 
df1.createOrReplaceTempView("data1")
df2.createOrReplaceTempView("data2")

val df = spark.sql("""