modules/softcascade/misc/detections2negatives.py

   1 #!/usr/bin/env python
   2
   3 import sys, os, os.path, glob, math, cv2, string, random
   4 from datetime import datetime
   5 from optparse import OptionParser
   6 import re
   7 import numpy as np
   8 from xml.dom import minidom
   9
  10 def resize(image, d_w, d_h):
  11     if (d_h < image.shape[0]) or (d_w < image.shape[1]):
  12         ratio = min(d_h / float(image.shape[0]), d_w / float(image.shape[1]))
  13
  14         kernel_size = int( 5 / (2 * ratio))
  15         sigma = 0.5 / ratio
  16         image_to_resize = cv2.filter2D(image, cv2.CV_8UC3, cv2.getGaussianKernel(kernel_size, sigma))
  17         interpolation_type = cv2.INTER_AREA
  18     else:
  19         image_to_resize = image
  20         interpolation_type = cv2.INTER_CUBIC
  21
  22     return cv2.resize(image_to_resize,(d_w, d_h), None, 0, 0, interpolation_type)
  23
  24 def det2negative(xmldoc, opath):
  25     samples = xmldoc.getElementsByTagName('sample')
  26     for sample in samples:
  27         detections = sample.getElementsByTagName('detections')
  28         detections = minidom.parseString(detections[0].toxml())
  29         detections = detections.getElementsByTagName("_")
  30         if len(detections) is not 0:
  31             path = sample.getElementsByTagName("path")
  32             path = path[0].firstChild.nodeValue
  33             mat = cv2.imread(path)
  34             mat_h, mat_w, _ = mat.shape
  35
  36             for detection in detections:
  37                 detection = detection.childNodes
  38                 for each in detection:
  39                     rect = eval(re.sub( r"\b\s\b", ",", re.sub(r"\n", "[", each.nodeValue )) + "]")
  40                     print rect
  41
  42                     ratio = 64.0 / rect[3]
  43
  44                     print rect, ratio
  45                     mat = resize(mat, int(round(mat_w * ratio)), int(round(mat_h * ratio)))
  46
  47                     rect[0] = int(round(ratio * rect[0])) - 10
  48                     rect[1] = int(round(ratio * rect[1])) - 10
  49                     rect[2] = rect[0] + 32 + 20
  50                     rect[3] = rect[1] + 64 + 20
  51                     try:
  52                         cropped = mat[rect[1]:(rect[3]), rect[0]:(rect[2]), :]
  53                         img = os.path.join(opath, ''.join(random.choice(string.lowercase) for i in range(8)) + ".png")
  54                         cr_h, cr_w, _ = cropped.shape
  55                         if cr_h is 84 and cr_w is 52:
  56                             cv2.imwrite(img, cropped)
  57                     except:
  58                         pass
  59
  60 if __name__ == "__main__":
  61
  62     parser = OptionParser()
  63     parser.add_option("-i", "--input", dest="input", metavar="DIRECTORY", type="string",
  64                        help="Path to the xml collection folder.")
  65
  66     parser.add_option("-d", "--output-dir", dest="output", metavar="DIRECTORY", type="string",
  67                        help="Path to store data", default=".")
  68
  69     (options, args) = parser.parse_args()
  70
  71     if not options.input:
  72         parser.error("Input folder is required.")
  73
  74     opath = os.path.join(options.output, datetime.now().strftime("negatives" + "-%Y-%m-%d-%H-%M-%S"))
  75     os.mkdir(opath)
  76
  77     gl = glob.iglob( os.path.join(options.input, "set[0][0]_V0[0][5].seq.xml"))
  78     for f in gl:
  79         print f
  80         xmldoc = minidom.parse(f)
  81         det2negative(xmldoc, opath)