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:
| // 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(""" |
| 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'): |
| # 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): |
| 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() |
| # 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 |
| # 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, |
| %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) |
| from matplotlib import pyplot as plt | |
| import numpy as np | |
| a = np.random.randn(10,10) | |
| plt.imshow(a, cmap='gray') |
| 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 |
I hereby claim:
To claim this, I am signing this object: