Build starting from a Jupyter 2.x image.
docker build -t jupyterlab .
import tensorflow as tf | |
import numpy as np | |
FC_SIZE = 1024 | |
DTYPE = tf.float32 | |
def _weight_variable(name, shape): | |
return tf.get_variable(name, shape, DTYPE, tf.truncated_normal_initializer(stddev=0.1)) |
Python version of the MATLAB code in this Stack Overflow post: https://stackoverflow.com/a/18648210/97160
The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.
Implemented in Python + NumPy + SciPy + matplotlib.
Last Update: May 13, 2019
Offline Version
#!/usr/bin/python | |
''' | |
Author: Igor Maculan - n3wtron@gmail.com | |
A Simple mjpg stream http server | |
''' | |
import cv2 | |
import Image | |
import threading | |
from BaseHTTPServer import BaseHTTPRequestHandler,HTTPServer | |
from SocketServer import ThreadingMixIn |