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, hessian_threshold, 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_surf_values(img, hessian_threshold, 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 build_distribution(est, n_clusters, hessian_threshold, 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_surf_values( img, hessian_threshold, 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(hessian_threshold, resize_ratio, resize_method, crop_amount): print 'Extracting Discriptors: SURF' 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_surf_values( img, hessian_threshold, 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
def extract_all_descriptors(hessian_threshold,resize_ratio, resize_method, crop_amount): print 'Extracting Discriptors: SURF' 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_surf_values(img, hessian_threshold, 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