| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <title>Create an autocomplete search using vanilla JavaScript</title> | |
| </head> | |
| <body> | |
| <div> | |
| <input type="text" id="autocomplete" placeholder="Select a color..."></input> |
| # -*- coding: utf-8 -*- | |
| # app.py | |
| from flask import Flask, render_template | |
| from flask_sqlalchemy import SQLAlchemy | |
| from flask_wtf import FlaskForm | |
| from wtforms import Form, FieldList, FormField, IntegerField, SelectField, \ | |
| StringField, TextAreaField, SubmitField | |
| from wtforms import validators |
| bl_info = { | |
| "name": "FreeCAD Importer", | |
| "category": "Import-Export", | |
| "author": "Yorik van Havre", | |
| "version": (5, 0, 0), | |
| "blender": (2, 80, 0), | |
| "location": "File > Import > FreeCAD", | |
| "description": "Imports a .FCStd file from FreeCAD", | |
| "warning": "This addon needs FreeCAD installed on your system. Only Part- and Mesh-based objects supported at the moment.", | |
| } |
| # My project directory is /home/rahit/www/mysite. I am storing cache file in my project folder under cache folder. | |
| # You can use any of your prefered location in system. may be: /tmp/nginx | |
| # I am naming keys_zone name my_cache. You can give it yours. We will need it later on in proxy_cache. | |
| # Just make sure you put same zone name there | |
| proxy_cache_path /home/rahit/www/mysite/cache levels=1:2 keys_zone=my_cache:10m max_size=1G; | |
| # This is our media server, which will be used to resize and crop. |
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.
| # Live streaming 2D monochrome image receiver | |
| # We can start this from python to view images | |
| # So we get the live image or a current image from Python, and | |
| # send it to ImageJ through this interface. Boom! | |
| from ij import IJ | |
| from ij.process import ByteProcessor, ShortProcessor, LUT | |
| import jarray |
| import numpy as np | |
| def imhist(im): | |
| # calculates normalized histogram of an image | |
| m, n = im.shape | |
| h = [0.0] * 256 | |
| for i in range(m): | |
| for j in range(n): | |
| h[im[i, j]]+=1 | |
| return np.array(h)/(m*n) |
| import random | |
| def get_random_color(pastel_factor = 0.5): | |
| return [(x+pastel_factor)/(1.0+pastel_factor) for x in [random.uniform(0,1.0) for i in [1,2,3]]] | |
| def color_distance(c1,c2): | |
| return sum([abs(x[0]-x[1]) for x in zip(c1,c2)]) | |
| def generate_new_color(existing_colors,pastel_factor = 0.5): | |
| max_distance = None |
