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@bigsnarfdude
bigsnarfdude / two_sigma_kalman_rolling.py
Last active Feb 14, 2019
using kalman filter for rolling window instead of average for faster convergence esp 2 sigma
View two_sigma_kalman_rolling.py
# https://scipy-cookbook.readthedocs.io/items/KalmanFiltering.html
# https://github.com/pykalman/pykalman
import pandas as pd
from pykalman import KalmanFilter
import numpy as np
def rolling_window(a, step):
shape = a.shape[:-1] + (a.shape[-1] - step + 1, step)
strides = a.strides + (a.strides[-1],)
@bigsnarfdude
bigsnarfdude / moar.py
Last active Feb 14, 2019
keras two image input model
View moar.py
# coding: utf-8
# In[38]:
from keras.layers import Input, Concatenate # symbolic version
from keras.layers import Input, Conv2D, Flatten, Dense
from keras.models import Model
@bigsnarfdude
bigsnarfdude / face_counter.py
Last active Feb 5, 2019
motion_detection.py
View face_counter.py
#face_counter.py
import numpy as np
import cv2
import requests
cv2.namedWindow('frame')
cv2.namedWindow('dist')
@bigsnarfdude
bigsnarfdude / face_verification.py
Last active Feb 4, 2019
microsoft face api face_verification.py
View face_verification.py
import cv2
from os import system
import cognitive_face as CF
from utils import *
import config as CFG
CF.Key.set(CFG.KEY)
BASE_URL = 'https://canadacentral.api.cognitive.microsoft.com/face/v1.0'
View nvidia_tx2_tensorflow.ipynb
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View gist:906af9bf6e0ba94f47708d827e7831e8
def grab(cam, queue, width, height, fps):
global running
capture = cv2.VideoCapture(cam)
capture.set(cv2.CAP_PROP_FRAME_WIDTH, width)
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
capture.set(cv2.CAP_PROP_FPS, fps)
while(running):
frame = {}
capture.grab()
@bigsnarfdude
bigsnarfdude / gpuMonitor.py
Created Jan 14, 2019
gpu tx2 monitor using python matplotlib
View gpuMonitor.py
#!/usr/bin/python
# MIT License
# Copyright (c) 2018 Jetsonhacks
import sys
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from collections import deque
@bigsnarfdude
bigsnarfdude / tensorflow_face_detection_demo.py
Last active Jan 3, 2019
face detection tensorflow demo with photo
View tensorflow_face_detection_demo.py
import cv2
from faced import FaceDetector
from faced.utils import annotate_image
face_detector = FaceDetector()
thresh = 0.8
img_path = 'meCroppedNormal.PNG'
img = cv2.imread(img_path)
rgb_img = cv2.cvtColor(img.copy(), cv2.COLOR_BGR2RGB)
@bigsnarfdude
bigsnarfdude / autograd.ipynb
Last active Dec 17, 2018
From Appendix B in the paper Neural ODE Solver Implementation using autograd https://arxiv.org/abs/1806.07366
View autograd.ipynb
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View gist:d408bef7b950124e1bae8d12153339a1
https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn589800(v=pandp.10)
https://docs.microsoft.com/en-us/azure/architecture/patterns/event-sourcing
https://cloud.google.com/images/forrester/forrester-graph.png
https://support.snowflake.net/s/article/configuring-azure-active-directory-as-an-identity-provider
us-east-2
snowflake just a compute skin on storage blobs
distributed query planning and aggregation
****************** customer record consistency is more of an issue
https://azure.microsoft.com/en-ca/services/data-factory/
ETL Pipeline - https://azure.microsoft.com/en-us/blog/deploying-apache-airflow-in-azure-to-build-and-run-data-pipelines/
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