コード例 #1
0
args = vars(ap.parse_args())

db = {}

for line in csv.reader(open(args["db"])):
    db[line[0]] = line[1:]

useSIFT = args["sift"] > 0
useHamming = args["sift"] == 0
ratio = 0.7
minMatches = 15

if useSIFT:
    minMatches = 50

descriptor = DinoDescriptor(useSIFT = useSIFT)
dinoMatcher = DinoMatcher(descriptor, glob.glob(args["samples"] + "/*.png"), ratio = ratio, minMatches = minMatches, useHamming = useHamming)
dinoResultsHandler = DinoResultsHandler(db)

# capture from web cam
cap = cv2.VideoCapture(0)
while True:
    ret, queryImage = cap.read()
    if ret == True:
        queryImage = utils2.resize(queryImage, width = 1000)
        # Segment the pink area out
        segImage = ColorSegmenter.getMagentaBlob(queryImage)
        # Describe the query image
        (queryKps, queryDescs, queryKpdRaw) = descriptor.describeQuery(segImage)
        # It is really important to handle the camera idling time.
        if len(queryKps) == 0:
コード例 #2
0
ファイル: search.py プロジェクト: abhat91/HumanDinoClassifier
if useSIFT:
    minMatches = 50

inputImage=cv2.imread(args["query"])

# cv2.imshow('Raw', inputImage)
# cv2.waitKey(0)



segmenter = DinoSegmenter2()
segImage = segmenter.segmentImage(inputImage)
# cv2.imshow('Segmented', segImage)
# cv2.waitKey(0)

descriptor = DinoDescriptor(useSIFT = useSIFT)
dinoMatcher = DinoMatcher(descriptor, glob.glob(args["samples"] + "/*.png"), ratio = ratio, minMatches = minMatches, useHamming = useHamming)

# queryImage = cv2.imread(args["query"])

# capture from webcam
# cap = cv2.VideoCapture(0)
# while(True):
#     ret, queryImage = cap.read()

# gray = cv2.cvtColor(queryImage, cv2.COLOR_BGR2GRAY)
(queryKps, queryDescs) = descriptor.describe(segImage)
# To  show the key points
KpImage = cv2.drawKeypoints(segImage, descriptor.kpsRaw, None)
cv2.imshow("Query KP Image", KpImage)
cv2.waitKey(0)