143 lines
5.6 KiB
Python
Executable File
143 lines
5.6 KiB
Python
Executable File
#!/usr/bin/env python
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import sys, os, os.path, glob, math, cv2, sft
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from datetime import datetime
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from optparse import OptionParser
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import re
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import numpy as np
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def extractPositive(f, path, opath, octave, min_possible):
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newobj = re.compile("^lbl=\'(\w+)\'\s+str=(\d+)\s+end=(\d+)\s+hide=0$")
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pos = re.compile("^pos\s=(\[[((\d+\.+\d*)|\s+|\;)]*\])$")
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occl = re.compile("^occl\s*=(\[[0-1|\s]*\])$")
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whole_mod_w = int(64 * octave) + 2 * int(20 * octave)
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whole_mod_h = int(128 * octave) + 2 * int(20 * octave)
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goNext = 0
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start = 0
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end = 0
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person_id = -1;
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boxes = []
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occls = []
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for l in f:
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m = newobj.match(l)
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if m is not None:
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if m.group(1) == "person":
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goNext = 1
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start = int(m.group(2))
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end = int(m.group(3))
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person_id = person_id + 1
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print m.group(1), person_id, start, end
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else:
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goNext = 0
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else:
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m = pos.match(l)
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if m is not None:
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if not goNext:
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continue
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strarr = re.sub(r"\s", ", ", re.sub(r"\;\s+(?=\])", "]", re.sub(r"\;\s+(?!\])", "],[", re.sub(r"(\[)(\d)", "\\1[\\2", m.group(1)))))
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boxes = eval(strarr)
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else:
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m = occl.match(l)
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if m is not None:
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occls = eval(re.sub(r"\s+(?!\])", ",", m.group(1)))
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if len(boxes) > 0 and len(boxes) == len(occls):
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for idx, box in enumerate(boxes):
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if occls[idx] == 1:
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continue
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x = box[0]
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y = box[1]
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w = box[2]
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h = box[3]
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id = int(start) - 1 + idx
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file = os.path.join(path, "I0%04d.jpg" % id)
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if (start + id) >= end or w < 10 or h < min_possible:
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continue
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mat = cv2.imread(file)
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mat_h, mat_w, _ = mat.shape
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# let default height of person be 96.
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scale = h / float(96)
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rel_scale = scale / octave
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d_w = whole_mod_w * rel_scale
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d_h = whole_mod_h * rel_scale
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tb = (d_h - h) / 2.0
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lr = (d_w - w) / 2.0
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x = int(round(x - lr))
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y = int(round(y - tb))
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w = int(round(w + lr * 2.0))
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h = int(round(h + tb * 2.0))
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inner = [max(5, x), max(5, y), min(mat_w - 5, x + w), min(mat_h - 5, y + h) ]
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cropped = mat[inner[1]:inner[3], inner[0]:inner[2], :]
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top = int(max(0, 0 - y))
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bottom = int(max(0, y + h - mat_h))
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left = int(max(0, 0 - x))
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right = int(max(0, x + w - mat_w))
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if top < -d_h / 4.0 or bottom > d_h / 4.0 or left < -d_w / 4.0 or right > d_w / 4.0:
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continue
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cropped = cv2.copyMakeBorder(cropped, top, bottom, left, right, cv2.BORDER_REPLICATE)
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resized = sft.resize_sample(cropped, whole_mod_w, whole_mod_h)
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flipped = cv2.flip(resized, 1)
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cv2.imshow("resized", resized)
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c = cv2.waitKey(20)
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if c == 27:
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exit(0)
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fname = re.sub(r"^.*\/(set[0-1]\d)\/(V0\d\d)\.(seq)/(I\d+).jpg$", "\\1_\\2_\\4", file)
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fname = os.path.join(opath, fname + "_%04d." % person_id + "png")
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fname_fl = os.path.join(opath, fname + "_mirror_%04d." % person_id + "png")
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try:
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cv2.imwrite(fname, resized)
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cv2.imwrite(fname_fl, flipped)
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except:
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print "something wrong... go next."
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pass
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if __name__ == "__main__":
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parser = OptionParser()
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parser.add_option("-i", "--input", dest="input", metavar="DIRECTORY", type="string",
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help="Path to the Caltech dataset folder.")
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parser.add_option("-d", "--output-dir", dest="output", metavar="DIRECTORY", type="string",
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help="Path to store data", default=".")
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parser.add_option("-o", "--octave", dest="octave", type="float",
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help="Octave for a dataset to be scaled", default="0.5")
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parser.add_option("-m", "--min-possible", dest="min_possible", type="int",
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help="Minimum possible height for positive.", default="64")
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(options, args) = parser.parse_args()
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if not options.input:
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parser.error("Caltech dataset folder is required.")
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opath = os.path.join(options.output, datetime.now().strftime("raw_ge64_cr_mirr_ts" + "-%Y-%m-%d-%H-%M-%S"))
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os.mkdir(opath)
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gl = glob.iglob( os.path.join(options.input, "set[0][0]/V0[0-9][0-9].txt"))
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for each in gl:
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path, ext = os.path.splitext(each)
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path = path + ".seq"
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print path
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extractPositive(open(each), path, opath, options.octave, options.min_possible)
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