import re
import numpy as np
+def resize(image, d_w, d_h):
+ if (d_h < image.shape[0]) or (d_w < image.shape[1]):
+ ratio = min(d_h / float(image.shape[0]), d_w / float(image.shape[1]))
+
+ kernel_size = int( 5 / (2 * ratio))
+ sigma = 0.5 / ratio
+ image_to_resize = cv2.filter2D(image, cv2.CV_8UC3, cv2.getGaussianKernel(kernel_size, sigma))
+ interpolation_type = cv2.INTER_AREA
+ else:
+ image_to_resize = image
+ interpolation_type = cv2.INTER_CUBIC
+
+ return cv2.resize(image_to_resize,(d_w, d_h), None, 0, 0, interpolation_type)
+
def showPeople(f, path, opath):
newobj = re.compile("^lbl=\'(\w+)\'\s+str=(\d+)\s+end=(\d+)\s+hide=0$")
pos = re.compile("^pos\s=(\[[((\d+\.+\d*)|\s+|\;)]*\])$")
occl = re.compile("^occl\s*=(\[[0-1|\s]*\])$")
+ octave = 0.5
+
+ whole_mod_w = int(64 * octave) + 2 * int(20 * octave)
+ whole_mod_h = int(128 * octave) + 2 * int(20 * octave)
+
goNext = 0
start = 0
end = 0
for l in f:
m = newobj.match(l)
if m is not None:
- print m.group(1)
if m.group(1) == "person":
goNext = 1
start = int(m.group(2))
occls = eval(re.sub(r"\s+(?!\])", ",", m.group(1)))
if len(boxes) > 0 and len(boxes) == len(occls):
- print len(boxes)
for idx, box in enumerate(boxes):
color = (8, 107, 255)
if occls[idx] == 1:
continue
- # color = (255, 107, 8)
+
x = box[0]
y = box[1]
w = box[2]
h = box[3]
+
id = int(start) - 1 + idx
file = os.path.join(path, "I0%04d.jpg" % id)
- print file
+ if (start + id) >= end or w < 10 or h < 64:
+ continue
+
+ mat = cv2.imread(file)
+ mat_h, mat_w, _ = mat.shape
+
+ scale = h / float(96)
+ rel_scale = scale / octave
+
+ d_w = whole_mod_w * rel_scale
+ d_h = whole_mod_h * rel_scale
+
+ tb = (d_h - h) / 2.0
+ lr = (d_w - w) / 2.0
+
+ x = int(round(x - lr))
+ y = int(round(y - tb))
+
+ w = int(round(w + lr * 2.0))
+ h = int(round(h + tb * 2.0))
+
+ inner = [max(5, x), max(5, y), min(mat_w - 5, x + w), min(mat_h - 5, y + h) ]
+ cropped = mat[inner[1]:inner[3], inner[0]:inner[2], :]
+
+ top = int(max(0, 0 - y))
+ bottom = int(max(0, y + h - mat_h))
+ left = int(max(0, 0 - x))
+ right = int(max(0, x + w - mat_w))
+
+ if top < -d_h / 4.0 or bottom > d_h / 4.0 or left < -d_w / 4.0 or right > d_w / 4.0:
+ continue
- if (start + id) < end and w > 5 and h > 47:
- img = cv2.imread(file)
+ cropped = cv2.copyMakeBorder(cropped, top, bottom, left, right, cv2.BORDER_REPLICATE)
+ resized = resize(cropped, whole_mod_w, whole_mod_h)
+ flipped = cv2.flip(resized, 1)
- fname = re.sub(r"^.*\/(set[0-1]\d)\/(V0\d\d)\.(seq)/(I\d+).jpg$", "\\1_\\2_\\4", file)#os.path.basename(file)
- fname = os.path.join(opath, fname + "_%04d." % person_id + "png")
- try:
- print "->", fname
- submat = img[int(y):int(y + h), int(x):int(x + w),:]
- cv2.imwrite(fname, submat)
- except:
- print "something wrong... go next."
- pass
- cv2.rectangle(img, (int(x), int(y)), (int(x + w), int(y + h)), color, 1)
- cv2.imshow("person", img)
+ cv2.imshow("resized", resized)
- c = cv2.waitKey(10)
- if c == 27:
- exit(0)
+ c = cv2.waitKey(20)
+ if c == 27:
+ exit(0)
+ fname = re.sub(r"^.*\/(set[0-1]\d)\/(V0\d\d)\.(seq)/(I\d+).jpg$", "\\1_\\2_\\4", file)
+ fname = os.path.join(opath, fname + "_%04d." % person_id + "png")
+ fname_fl = os.path.join(opath, fname + "_mirror_%04d." % person_id + "png")
+ try:
+ cv2.imwrite(fname, resized)
+ cv2.imwrite(fname_fl, flipped)
+ except:
+ print "something wrong... go next."
+ pass
if __name__ == "__main__":
parser = OptionParser()
if not options.input:
parser.error("Caltech dataset folder is required.")
- opath = os.path.join(options.output, datetime.now().strftime("raw_ge48-" + "-%Y-%m-%d-%H-%M-%S"))
+ opath = os.path.join(options.output, datetime.now().strftime("raw_ge64_cr_mirr_ts" + "-%Y-%m-%d-%H-%M-%S"))
os.mkdir(opath)
- gl = glob.iglob( os.path.join(options.input, "set[0-1][0-9]/V0[0-9][0-9].txt"))
+ gl = glob.iglob( os.path.join(options.input, "set[0-1][0-5]/V0[0-9][0-9].txt"))
for each in gl:
path, ext = os.path.splitext(each)
path = path + ".seq"
projects / platform / upstream / opencv.git / commitdiff