prash neotheicebird

## Flake8.txt
How to manually setup flake8 as PyCharm external tool

File / Settings / Tools / External Tools / Add
Name: Flake8
Program: $PyInterpreterDirectory$/python
Parameters: -m flake8 --max-complexity 10 --ignore E501 $FilePath$
Working directory: $ProjectFileDir$

Output Filters / Add
Name: Filter 1

## staircase_lr_decay_tf.py
# Ref: https://github.com/ericjang/genadv_tutorial/blob/master/genadv1.ipynb
learning_rate = tf.train.exponential_decay(
        0.001,                # Base learning rate.
        batch,                # Current index into the dataset.
        TRAIN_ITERS // 4,     # Decay step - this decays 4 times throughout training process.
        0.95,                 # Decay rate.
        staircase=True)

## reduce_json_dicts.py
def get_from_json_dict(json_dict, keys, default_dict=None):

    for index, key in enumerate(keys):
        if isinstance(json_dict, dict) and isinstance(key, str):   # check if you have a `dict` and `str` in hand
            # get item of the key from json_dict, if key is Bad, get item from default_dict, or get None
            json_dict = json_dict.get(key, default_dict[key] if default_dict else None)
            if default_dict:
                default_dict = default_dict[key]    # reducing default dict
            continue
        if isinstance(json_dict, list) and isinstance(key, int):   # check if you have a `list` and `int` in hand

## reduce_nested_dicts.py
# get only the first element
checkout_curse = reduce(lambda curses_dict, key: dict.get(key), [curses_dict, "curses", "names", 0])

## access_webcam_matplotlib_notebook_sigint.ipynb

      
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                neotheicebird
                / access_webcam_matplotlib_notebook_sigint.ipynb
            
            
              Last active
              August 17, 2021 21:03
            
              
                Acces webcam for image processing. SIGINT signal is captured to exit while loop.
              
          
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## gist:41307ee86cf6bee46185f382c0b1f7b6
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2016-11-01T17:33:15.254949",
     "start_time": "2016-11-01T17:33:12.700730"
    },

## access_webcam_matplotlib_inline.ipynb

      
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                neotheicebird
                / access_webcam_matplotlib_inline.ipynb
            
            
              Last active
              October 25, 2020 10:02
            
              
                Access webcam in iPython notebook (Slower version)
              
          
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## access_webcam_matplotlib_notebook.ipynb

      
              1 file
            
          
              1 fork
            
          
              0 comments
            
          
              0 stars
            
          
                neotheicebird
                / access_webcam_matplotlib_notebook.ipynb
            
            
              Last active
              April 10, 2019 23:13
            
              
                 Access Webcam in iPython notebook
              
          
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## cpickle_in_py3.py
import pickle    # pickle is py2 equivalent of cPickle
# if a Py2 cPickle object shows UnicodeError in Py3
with open(picklefile, 'rb') as f
    d = pickle.load(f, encoding='latin1')

## download_file.py
import requests

url = "http://www.matthewzeiler.com/pubs/arxive2013/eccv2014.pdf"
r = requests.get(url)

pdffile = r.url.split('/')[-1]
with open(pdffile, 'wb') as pdf:
  pdf.write(r.content)
	How to manually setup flake8 as PyCharm external tool

	File / Settings / Tools / External Tools / Add
	Name: Flake8
	Program: $PyInterpreterDirectory$/python
	Parameters: -m flake8 --max-complexity 10 --ignore E501 $FilePath$
	Working directory: $ProjectFileDir$

	Output Filters / Add
	Name: Filter 1
	# Ref: https://github.com/ericjang/genadv_tutorial/blob/master/genadv1.ipynb
	learning_rate = tf.train.exponential_decay(
	0.001, # Base learning rate.
	batch, # Current index into the dataset.
	TRAIN_ITERS // 4, # Decay step - this decays 4 times throughout training process.
	0.95, # Decay rate.
	staircase=True)
	def get_from_json_dict(json_dict, keys, default_dict=None):

	for index, key in enumerate(keys):
	if isinstance(json_dict, dict) and isinstance(key, str): # check if you have a `dict` and `str` in hand
	# get item of the key from json_dict, if key is Bad, get item from default_dict, or get None
	json_dict = json_dict.get(key, default_dict[key] if default_dict else None)
	if default_dict:
	default_dict = default_dict[key] # reducing default dict
	continue
	if isinstance(json_dict, list) and isinstance(key, int): # check if you have a `list` and `int` in hand
	# get only the first element
	checkout_curse = reduce(lambda curses_dict, key: dict.get(key), [curses_dict, "curses", "names", 0])
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {
	"ExecuteTime": {
	"end_time": "2016-11-01T17:33:15.254949",
	"start_time": "2016-11-01T17:33:12.700730"
	},
	import pickle # pickle is py2 equivalent of cPickle
	# if a Py2 cPickle object shows UnicodeError in Py3
	with open(picklefile, 'rb') as f
	d = pickle.load(f, encoding='latin1')
	import requests

	url = "http://www.matthewzeiler.com/pubs/arxive2013/eccv2014.pdf"
	r = requests.get(url)

	pdffile = r.url.split('/')[-1]
	with open(pdffile, 'wb') as pdf:
	pdf.write(r.content)