test_bottle.py

import Image
import shutil
import dlib
import random
import os
import glob
from skimage import io
# print "\nTest1 accuracy: ", dlib.test_simple_object_detector('/home/jyotiska/Dropbox/Computer Vision/cupdataset_2_test.xml',"cupdetector_2.svm")
# print "\nTraining accuracy: ", dlib.test_simple_object_detector('/home/jyotiska/Dropbox/Computer Vision/cupdataset_3.xml',"cupdetector_3.svm")

detector = dlib.simple_object_detector("bottledetector.svm")

win_det = dlib.image_window()
win_det.set_image(detector)

win = dlib.image_window()
test_dir = '/home/jyotiska/Dropbox/Computer Vision/Bottle_test_convert'
assorted_dir = '/home/jyotiska/Dropbox/Computer Vision/Item bucket'

items =os.listdir(assorted_dir)


convert_i = 0
for f in glob.glob(test_dir+"/*.*"):
    print "processing file:", f
    img = io.imread(f)
    extension = f.split(".")[1]
    convert_file = "convert_bottle_"+str(convert_i)+"."+extension
    shutil.copy(f,convert_file)
    print "convert file:",convert_file
    background = Image.open(convert_file)
    dets = detector(img)

    print "number of cups detected:", len(dets)
    for d in dets:
    	x = d.left()
    	y = d.top()
    	width = d.right() - x
    	height = d.bottom() - y
        print "  detection position left,top,right,bottom:", d.left(), d.top(), d.right(), d.bottom()
        r = random.randint(0,len(items)-1)
        print r,items[r]
        random_item = Image.open(assorted_dir+"/"+items[r])
        # scale it a bit more, and adjust position

        # Apply blur?
        resized = random_item.resize( (int(1.2*width),int(1.2*height)) )
        background.paste(resized, (d.left()-12,d.top()-10), resized)

    background.show()
    background.save(convert_file)
    win.clear_overlay()
    win.set_image(img)
    win.add_overlay(dets)
    convert_i += 1
    raw_input("Hit enter to continue")