garybradski

if (!fork()) {
  cv::imshow("debug", frame_image);
  cv::waitKey(0);
  exit(0);
}

garybradski

my_tuple = ('p','r','o','g','r','a','m','i','z')

print("og forward:")
print("og: ",my_tuple[2:4])
print("og: ",my_tuple[-7:4])
print("og: ",my_tuple[-7:-5])
print("og: ",my_tuple[2:-5])

print("og backwards (go):")
print("go: ",my_tuple[3:1:-1])

garybradski

#Method 1, pythonic
        img_res = np.zeros(image.shape, np.uint8)   #create the image
        img_res[:, :] = (0, 0, 200)                 #color it red
        idx = (mask != 0)
        img_res[idx] = image[idx]
        
#Method 2 OpenCV
        img_red = np.zeros(image.shape, np.uint8)                 #create the image
        img_red[:, :] = (0, 0, 200)                               #color it red
        fg = cv2.bitwise_and(image, image, mask=mask)             #isolate the segmented region

garybradski

    cap = cv2.VideoCapture('/opt/home/garybradski/data/matte_this/shot02/Tornado.mp4')
    length = int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))
    print "len Tornado = ", length
    cv2.namedWindow('Tornado', cv2.WINDOW_NORMAL)
    cv2.resizeWindow('Tornado',960,540)
    # seek
    assert cap.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, 8000)
    n = 0
    wait_key = 30
    while True:

garybradski

import argparse
import logging
    parser.add_argument('--loglevel', help='Logging level: NONE, DEBUG 10, INFO 20, WARNING 30, ERROR 40, CRITICAL 50. Default: OFF 100', type=str, default='WARNING' )
    args = parser.parse_args()

    logging.basicConfig()
    logger = logging.getLogger()
    if(args.loglevel == 'OFF'): logger.setLevel(100)
    elif(args.loglevel == 'DEBUG'): logger.setLevel(logging.DEBUG)
    elif(args.loglevel == 'INFO'): logger.setLevel(logging.INFO)

garybradski

import cv2
 
# Read the images
foreground = cv2.imread("puppets.png")
background = cv2.imread("ocean.png")
alpha = cv2.imread("puppets_alpha.png")
 
# Convert uint8 to float
foreground = foreground.astype(float)
background = background.astype(float)

garybradski

void alphaBlend(Mat& foreground, Mat& background, Mat& alpha, Mat& outImage)
{
     // Find number of pixels. 
     int numberOfPixels = foreground.rows * foreground.cols * foreground.channels();
 
     // Get floating point pointers to the data matrices
     float* fptr = reinterpret_cast<float*>(foreground.data);
     float* bptr = reinterpret_cast<float*>(background.data);
     float* aptr = reinterpret_cast<float*>(alpha.data);
     float* outImagePtr = reinterpret_cast<float*>(outImage.data);

garybradski

import cv2
import argparse
import numpy as np
import os
import logging

#GLOBAL
logging.basicConfig()       #Fire up the logger
logger = logging.getLogger()

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)

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)) )