def __init__(self, useSIFT = False, useHamming = True, ratio = 0.7, minMatches = 40): # store whether or not SIFT should be used as the feature # detector and extractor self.useSIFT = useSIFT self.useHamming = useHamming self.ratio = ratio self.minMatches = minMatches # if SIFT is to be used, then update the parameters if useSIFT: self.minMatches = 50 self.cd = CoverDescriptor(useSIFT = useSIFT) self.cv = CoverMatcher(self.cd, ratio = ratio, minMatches = minMatches, useHamming = useHamming)
# Converts np.array to TEXT when inserting sqlite3.register_adapter(numpy.ndarray, adapt_array) # Converts TEXT to np.array when selecting sqlite3.register_converter("array", convert_array) ap = argparse.ArgumentParser() args = vars(ap.parse_args()) useSIFT = False useHamming = True # initialize the cover descriptor and cover matcher cd = CoverDescriptor(useSIFT=useSIFT) conn = sqlite3.connect('db', detect_types=sqlite3.PARSE_DECLTYPES) cur = conn.cursor() c = conn.cursor() for imgPath in glob.glob("newimages/*.png"): # load the query image, convert it to grayscale, and # extract keypoints and descriptors cover = cv2.imread(imgPath) gray = cv2.cvtColor(cover, cv2.COLOR_BGR2GRAY) (kps, descs) = CoverDescriptor.describe(cd, gray) c.execute( 'INSERT INTO images(filename,keypoints,descriptors) VALUES(?,?,?)',
# otherwise, load the video else: camera = cv2.VideoCapture(args["video"]) # initialize the database dictionary of covers db = {} # loop over the database, CSV file is opened and each line looped over. # The db dictionary is updated with the unique filename of the book as the key and # the title of the book and author as the value. for l in csv.reader(open(args["db"])): # update the database using the image ID as the key db[l[0]] = l[1:] # initialize the cover descriptor and cover matcher cd = CoverDescriptor() cv = CoverMatcher(cd, glob.glob(args["empaques"] + "/*.png")) ######################################################################################################### # keep looping while True: # grab the current frame (grabbed, frame) = camera.read() # if we are viewing a video and we did not grab a # frame, then we have reached the end of the video if args.get("video") and not grabbed: break gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)