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summarize_results_Cat1solid.py
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summarize_results_Cat1solid.py
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import xlwt
from argparse import ArgumentParser
parser = ArgumentParser(description='LSRN-PCGC summarize results')
parser.add_argument('-model', '--model', default='LSRN', type=str,
help='LSRN')
parser.add_argument('-act', '--activation', default='Sine', type=str,
help='Sine')
parser.add_argument('-nl', '--num_layers', type=int, default=1,
help='Number of layers (default: 1)')
parser.add_argument('-D', '--D', type=int, default=1,
help='neighbors (2D+1)^3-1')
parser.add_argument('-precision', '--precision', type=int, default=16,
help=' (default: 16)')
parser.add_argument('-fsr', '--frame_sampling_rate', type=int, default=1,
help='#frame sampling rate (default: 1)')
parser.add_argument('-lr', '--lr', type=float, default=1e-3,
help='learning rate (default: 1e-3)')
parser.add_argument('-bs', '--batch_size', type=int, default=2048,
help='batch size (default: 2048)')
parser.add_argument('-e', '--epochs', type=int, default=150,
help='number of epochs to train (default: 150)')
args = parser.parse_args()
logpath = 'logs_eval/' # eval
datasetname_lst = list([
'basketball_player_vox11_00000200.ply',
'dancer_vox11_00000001.ply',
'Facade_00064_vox11.ply',
'longdress_vox10_1300_n.ply',
'loot_vox10_1200_n.ply',
'queen_0200_n.ply',
'redandblack_vox10_1550_n.ply',
'soldier_vox10_0690_n.ply',
'Thaidancer_viewdep_vox12.ply',
])
pqs_lst = list([
64,
32,
16,
8,
4,
2,
])
wbk = xlwt.Workbook()
sheet = wbk.add_sheet('C2 lossyG,lossyA,intra', cell_overwrite_ok=True)
output = open('Cat1solid.txt', 'w')
file_lst = list()
for name in datasetname_lst:
for pqs in pqs_lst:
fs_base = '{}_{}_bc{}_nl{}_D{}_p{}_lr{}_fsr{}_bs{}_e{}_{}_pqs{}'
file = logpath+fs_base.format(args.model, args.activation, int(64/pqs),
args.num_layers, args.D, args.precision,
args.lr, args.frame_sampling_rate, args.batch_size,
args.epochs, name, pqs)
file_lst.append(file)
row = 0
col = 0
missed = 0
for k, file_name in enumerate(file_lst):
print(file_name)
record = list()
netparam = 0
base = 0
points = 0
D1 = 0
D2 = 0
nF = 0
try:
reader = open(file_name, 'r')
for line in reader:
words = line.split()
if ('network' in words) :
netparam = int(words[-2])
if ('scaling' in words):
points += int(words[-2][:-1])
nF += 1
if (('mseF,PSNR' in words) and ('(p2point):' in words)):
D1 += float(words[2])
if (('mseF,PSNR' in words) and ('(p2plane):' in words)):
D2 += float(words[2])
if (('Total' in words) and ('bitstream' in words)) :
base += int(words[3]) * 8
reader.close()
D1 = D1 / nF
D2 = D2 / nF
except IOError:
print('No files found!')
base = int(base / 2) # encoder+decoder
geom = base + netparam
total = geom
print(points, geom, base, netparam, D1, D2)
if base != 0:
if points != 0:
record.append(str(points))
sheet.write(row, col, points)
if total != 0:
record.append(str(total))
sheet.write(row, col+1, total)
if geom != 0:
record.append(str(base))
record.append(str(netparam))
sheet.write(row, col+2, geom)
if D1 != 0:
record.append(str(D1))
sheet.write(row, col+5, D1)
if D2 != 0:
record.append(str(D2))
sheet.write(row, col+6, D2)
record_str = ''
row = row + 1
else:
missed += 1
record_str = ''
if (k+1)%6==0: # 6 rate points / pc
row = row + missed
missed = 0
for word in record:
record_str = record_str + str(word) + ' '
record_str = record_str + '\n'
output.write(record_str)
output.close()
excel_file = 'Cat1solid.xls' #
wbk.save(excel_file)