def match(crop_amount,ipd):
out = None
text1 = ent1.get().upper()
text2 = ent2.get().upper()
resize_ratio_m = float(ent3.get())
print resize_ratio_m
if resize_ratio_m == None:
resize_ratio_m = default_values.resize_ratio
num_matches = int(ent4.get())
if num_matches == None:
num_matches = 10
print resize_ratio_m
try:
img1URL = imagesHandler.get_full_url(text1)
img2URL = imagesHandler.get_full_url(text2)
img1 = cv2.imread(img1URL)
img2 = cv2.imread(img2URL)
if ipd =="SURF":
k1,d1,gray1 = interest_point_detectors.calculate_surf_values(img1,hessian_threshold=default_values.hessian_threshold,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
k2,d2,gray2 = interest_point_detectors.calculate_surf_values(img2,hessian_threshold=default_values.hessian_threshold,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
if ipd =="SIFT":
k1,d1,gray1 = interest_point_detectors.calculate_sift_values(img1,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
k2,d2,gray2 = interest_point_detectors.calculate_sift_values(img2,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
if ipd =="ORB":
k1,d1,gray1 = interest_point_detectors.calculate_orb_values(img1,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
k2,d2,gray2 = interest_point_detectors.calculate_orb_values(img2,resize_ratio=resize_ratio_m,resize_method=default_values.resize_method,crop_amount=crop_amount)
out = matching.matchandDraw(gray1,gray2,k1,d1,k2,d2,num_matches)
except Exception,e:
print e
def match(crop_amount, ipd):
out = None
text1 = ent1.get().upper()
text2 = ent2.get().upper()
resize_ratio_m = float(ent3.get())
print resize_ratio_m
if resize_ratio_m == None:
resize_ratio_m = default_values.resize_ratio
num_matches = int(ent4.get())
if num_matches == None:
num_matches = 10
print resize_ratio_m
try:
img1URL = imagesHandler.get_full_url(text1)
img2URL = imagesHandler.get_full_url(text2)
img1 = cv2.imread(img1URL)
img2 = cv2.imread(img2URL)
if ipd == "SURF":
k1, d1, gray1 = interest_point_detectors.calculate_surf_values(
img1,
hessian_threshold=default_values.hessian_threshold,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
k2, d2, gray2 = interest_point_detectors.calculate_surf_values(
img2,
hessian_threshold=default_values.hessian_threshold,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
if ipd == "SIFT":
k1, d1, gray1 = interest_point_detectors.calculate_sift_values(
img1,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
k2, d2, gray2 = interest_point_detectors.calculate_sift_values(
img2,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
if ipd == "ORB":
k1, d1, gray1 = interest_point_detectors.calculate_orb_values(
img1,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
k2, d2, gray2 = interest_point_detectors.calculate_orb_values(
img2,
resize_ratio=resize_ratio_m,
resize_method=default_values.resize_method,
crop_amount=crop_amount)
out = matching.matchandDraw(gray1, gray2, k1, d1, k2, d2, num_matches)
except Exception, e:
print e
def build_distribution(est, n_clusters, resize_ratio, resize_method, crop_amount):
print 'BuildingDistribution'
images = imagesHandler.get_all_img_rows()
allDist = []
numimg = 0
for image in images:
if numimg%100==0:
print numimg
imageId = image[0]
imageURL = image[1]
img = cv2.imread(dirm.rootDirectory + imageURL)
#print dirm.rootDirectory + imageURL
try:
kp,desc,gray = interest_point_detectors.calculate_sift_values(img, resize_ratio, resize_method, crop_amount)
except Exception,e:
print "unable to process image "+imageId
print str(e)
dist = np.zeros((n_clusters))
imagePred = est.predict(desc)
for p in imagePred:
dist[p] = dist[p] + 1
dist = dist / len(imagePred)
allDist.append([imageId] + dist.tolist())
numimg = numimg +1
def extract_all_descriptors(resize_ratio, resize_method, crop_amount):
print 'Extracting Discriptors: SIFT'
images = imagesHandler.get_all_img_rows()
concatDesc = []
concatIds = []
numimg = 0
numDesc = 0
for image in images:
if numimg%100==0:
print numimg
imageId = image[0]
imageURL = image[1]
img = cv2.imread(dirm.rootDirectory + imageURL)
try:
kp,desc,gray = interest_point_detectors.calculate_sift_values(img, resize_ratio, resize_method, crop_amount)
numDesc = numDesc + len(desc)
for d in desc:
concatDesc.append(d)
concatIds.append([imageId,len(desc)])
except Exception,e:
print "unable to process image "+imageId
print str(e)
numimg = numimg +1