def RansacPointExtract(ID):
info = Info.GetVideoInfo(ID)
f_name = Info.GetTrackFileName(info)
f = open(f_name, 'r')
obj, graph_feature_data, graph_track_data = dataset.load_tracks_graph(f) #####
#print graph_track_data
f.close()
track_nodes, image_nodes = nx.algorithms.bipartite.sets(obj) ####
buf = Info.ReadReconstructionData(info)
image_lst = buf['shots'].keys() #####
reconstruct_data = buf['points'] ####
reconstruct_data_key_lst = reconstruct_data.keys() #####
match_data = np.load(Info.GetMatchResultFileName(info)).item()
#print match_data.keys()
f = open(Info.GetMatchResultPointFileName(info), 'r')
pano_data = json.load(f)
f.close()
#print pano_data.keys()
new_pano_data = {}
for index, key in enumerate(pano_data):
loc_key = pano_data[key].keys()[0]
pano_key = match_data[key].keys()[0]
tmp = np.reshape(pano_data[key][loc_key], (-1,3))
try:
new_pano_data[key][pano_key] = tmp
except:
new_pano_data[key] = {}
new_pano_data[key][pano_key] = tmp
recontruct_point = []
pano_point = []
for index, key in enumerate(match_data):
#key_tmp = key + '.jpg'
key_tmp = key
if key_tmp in image_lst:
pano_key = match_data[key].keys()[0]
for index, image_index in enumerate(match_data[key][pano_key][0]):
if image_index in graph_feature_data[key_tmp]:
track_id = graph_track_data[key_tmp][str(image_index)]
if track_id in reconstruct_data_key_lst:
point1 = reconstruct_data[track_id]['coordinates']
point2 = new_pano_data[key_tmp][pano_key][index, :]
if point2[np.abs(point2) > 10000].size == 0:
recontruct_point.append(point1)
pano_point.append(point2)
recontruct_point = np.array(recontruct_point, dtype=np.float32)
#length = recontruct_point.shape[0]
#recontruct_point = np.array([recontruct_point[:,0], recontruct_point[:,1], recontruct_point[:,2], np.ones([length])], dtype=np.float32)
pano_point = np.array(pano_point, dtype = np.float32)
#pano_point = np.array([pano_point[:,0], pano_point[:,1], pano_point[:,2], np.ones([length])], dtype=np.float32)
np.save(Info.GetMatchResultExtractPointFileName(info), [recontruct_point, pano_point])
print recontruct_point.shape
print pano_point.shape
print '%s extract point finish'%ID
def RunRansac(ID):
print ID
info = Info.GetVideoInfo(ID)
data = np.load(Info.GetMatchResultExtractPointFileName(info))
#data2 = data[1]
#data[0] = data[0][np.abs(data[1]) <= 3000]
#data[1] = data[1][np.abs(data[1]) <= 3000]
#data2 = data[1i]
try:
M, align_data = RANSAC.RANSAC_affine(data[0], data[1], 10000, 5)
except:
return
if M is None:
return
print M
#print np.reshape(M, [12])
try:
M = np.reshape(M, [12]).astype(float)
except:
return
gcp = Info.ReadGCPData(info)
data = Info.ReadReconstructionData(info)
trajectory = {}
for shot in data['shots']:
[x, y, z] = optical_center(data['shots'][shot])
trajectory[shot] = [x, y, z]
data['gcp'] = gcp
#print gcp
data['transformation'] = list(M)
#print type(M[0])
data['trajectory'] = trajectory
#print trajectory
f_name = Info.Get3DRansacFileName(info)
f = open(f_name, 'w')
f.write(json.dumps(data, indent=4))
f.close()
print '%s ransac finish' % ID
