implement positive sample extraction

apps/sft/misk/scale_caltech.py

@@ -4,21 +4,15 @@ import sys, os, os.path, glob, math, cv2
 from datetime import datetime
 from optparse import OptionParser
 import re
+import numpy as np
 
-start_templates = ["lbl", "pos", "occl"]
 
-class Sample:
+def extract(f):
-    def __init__(self, l):
-        self
-
-if __name__ == "__main__":
-    f = open("/home/kellan/datasets/caltech/set00/V004.txt")
     person = re.compile("^lbl=\'person\'\s+str=(\d+)\s+end=(\d+)\s+hide=0$")
     newobj = re.compile("^lbl=\'(\w+)\'\s+str=(\d+)\s+end=(\d+)\s+hide=0$")
     pos = re.compile("^pos\s=(\[[((\d+\.+\d*)|\s+|\;)]*\])$")
     nonarray = re.compile("\;\s+(?!\])|\s+(?!\])")
     lastSemicolon = re.compile("\;\s+(?=\])")
-    qqq = re.compile("(?=\[)\b(?=\d*)")
 
     goNext = 0
     start = 0
@@ -66,5 +60,112 @@ if __name__ == "__main__":
                             img = cv2.imread(file)
                             cv2.rectangle(img, (int(x), int(y)), (int(x + w), int(y + h)), (0,255,0), 2)
                             cv2.imshow("sample", img)
-                            cv2.waitKey(0)
+                            cv2.waitKey(50)
+
+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*=(\[[0-1|\s]*\])$")
+
+    goNext = 0
+    start = 0
+    end = 0
+
+    person_id = -1;
+
+    boxes = []
+    occls = []
+
+    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))
+                end   = int(m.group(3))
+                person_id = person_id + 1
+                print m.group(1), person_id, start, end
+            else:
+                goNext = 0
+        else:
+            m = pos.match(l)
+            if m is not None:
+                if not goNext:
+                    continue
+                strarr = re.sub(r"\s", ", ", re.sub(r"\;\s+(?=\])", "]", re.sub(r"\;\s+(?!\])", "],[", re.sub(r"(\[)(\d)", "\\1[\\2", m.group(1)))))
+                boxes = eval(strarr)
+            else:
+                m = occl.match(l)
+                if m is not None:
+                    occls = eval(re.sub(r"\s+(?!\])", ",", 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 and w > 5 and h > 47:
+                                img = cv2.imread(file)
+
+                                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)
+
+                                c = cv2.waitKey(10)
+                                if c == 27:
+                                    exit(0)
+
+
+if __name__ == "__main__":
+    parser = OptionParser()
+    parser.add_option("-i", "--input", dest="input", metavar="DIRECTORY", type="string",
+                       help="path to the Caltech dataset folder.")
+
+    parser.add_option("-o", "--output", dest="output", metavar="DIRECTORY", type="string",
+                       help="path to store data", default=".")
+
+    (options, args) = parser.parse_args()
+
+    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"))
+    os.mkdir(opath)
+
+    # mat = cv2.imread("/home/kellan/datasets/INRIArescaled/training_set/pos/octave_-1/sample_0.png");
+    # cv2.rectangle(mat, (10, 10), (42, 74), (8, 107, 255), 1)
+
+    # cv2.imshow("person", mat)
+    # cv2.waitKey(0)
+    # if c == 27:
+    #     exit(0)
+
+    gl = glob.iglob( os.path.join(options.input, "set[0-1][0-9]/V0[0-9][0-9].txt"))
+    for each in gl:
+        path, ext = os.path.splitext(each)
+        path = path + ".seq"
+        print path
+        showPeople(open(each), path, opath)
 
+    # f = open("/home/kellan/datasets/caltech/set00/V004.txt")
+    # extract(f)