garybradski

import sys
import argparse
import cv2


MIN_PYTHON = (3, 3)
if sys.version_info < MIN_PYTHON:
    sys.exit("Python %s.%s or later is required.\n" % MIN_PYTHON)

garybradski

# From https://gist.github.com/zacharybell/8d9b1b25749fe6494511f843361bb167
import numpy as np

def mean_iou(labels, predictions, n_classes):
    mean_iou = 0.0
    seen_classes = 0

    for c in range(n_classes):
        labels_c = (labels == c)
        pred_c = (predictions == c)

garybradski

fdupes -rdN <dir>
# r is recursive
# d is keep the first file of the duplicated files
# N is run silent so you don't have to say yes or no

garybradski

import cv2
import argparse
import os

parser = argparse.ArgumentParser()
parser.add_argument('--video', help='path to video to convert to images.')
parser.add_argument('--out', help='path to output directory.')
args = parser.parse_args()

if not os.path.exists(args.out):

garybradski

import cv2
import numpy as np

def connected_components(thresh_img):
    thresh_img = mog_mask.copy()
    contours, hierarchy = cv2.findContours(thresh_img, cv2.RETR_TREE,
                                           cv2.CHAIN_APPROX_SIMPLE)
    fg_mask = np.zeros(frame.shape[:2], np.uint8)
    i = 0
    cs = []

garybradski

def skeletonize(img):
  '''
  Adapted from: 
    https://opencvpython.blogspot.com/2012/05/skeletonization-using-opencv-python.html
  '''
    assert len(img.shape) == 2  #make sure its single channel
    size = np.size(img)
    tenth_size = size/10
    skel = np.zeros(img.shape,np.uint8)

garybradski

#!/bin/bash
# Useful stuff for scripts, Gary Bradski

#Python
## For python, you should run your files through yapf
sudo pip install yapf
yapf -i <path/file_to_be_yapfed>

##To convert python 2 to 3 in place: 
2to3 -w <path/file_to_be_converted>

garybradski

def rect_files(start,stop):
    startstop = range(start,stop)
    for i in startstop:
        openstr = "%09d.txt"%(i) #zero justify out to 9 places
        file = open(openstr,"w")
        file.write("[ 0, 0, 0, 0 ]")
        file.close()

garybradski

def text_to_floatlist(pathfile):
        f = open(pathfile, 'r')
        line = f.readline().strip('[]')
        f.close()
        return [float(x) for x in line.split()]

#Use
        rect = text_to_floatlist(seg_bb[frame_count])
        if(len(rect) < 4):
            logger.critical("Length of rectangle not long enough %d",int(len(rect)) )

garybradski

import cv2
from matplotlib import pyplot as plt

. . .

    #DO PYTHON MATPLOTLIB IMAGE DISPLAY
    plt.imshow(image_seg)
    plt.draw()
    plt.show()  # , plt.draw(), plt.show()
    plt.pause(0.01)