def get_msssim():
bppl = []
ssim = []
namel = []
path = '/mnt/Volume1/test/clic2020-devkit/bpg_reslut'
path_ta = '/mnt/Volume1/test/clic2020-devkit/targets_yuv'
path_bpg = '/mnt/Volume1/test/clic2020-devkit/part_bpg'
for root, dirs, files in os.walk(path, topdown=False):
for name in files:
#get size
p = os.path.join(path_bpg, name.replace('.png', '.bpg'))
size = os.path.getsize(p)
fig1 = Image.open(os.path.join(root, name))
fig1_array = np.asarray(fig1)
fig2 = Image.open(os.path.join(path_ta, name))
fig2_array = np.asarray(fig2)
bpp = size * 8 / fig1.size[0] / fig1.size[1]
#fig2 = Image.open('/mnt/Volume0/test/1.png')
fig1_array = fig1_array.reshape(
(1, fig1_array.shape[0], fig1_array.shape[1], 1))
fig2_array = fig2_array.reshape(
(1, fig2_array.shape[0], fig2_array.shape[1], 1))
# yuv = np.concatenate([fig1_array,fig1_array,fig1_array], axis = 3)
# yuv1 = np.concatenate([fig2_array,fig2_array,fig2_array], axis = 3)
score = MultiScaleSSIM(fig1_array,
fig2_array,
max_val=255,
filter_size=11,
filter_sigma=1.5,
k1=0.01,
k2=0.03,
weights=None)
print(score)
bppl.append(bpp)
ssim.append(score)
namel.append(name)
df1 = pd.DataFrame({'name': namel})
df2 = pd.DataFrame({'bpp': bppl})
df3 = pd.DataFrame({'ssim': ssim})
writer = pd.ExcelWriter(
'/mnt/Volume1/test/clic2020-devkit/bpg_bpp_ssim.xlsx')
df1.to_excel(writer, sheet_name='name', startcol=0)
df2.to_excel(writer, sheet_name='bpp', startcol=1)
df3.to_excel(writer, sheet_name='ssim', startcol=2)
writer.save()
def encode_I(args, frame_index, I_level, path, path_com, path_bin):
if args.mode == 'PSNR':
os.system('bpgenc -f 444 -m 9 ' + path + 'f' +
str(frame_index).zfill(3) + '.png '
'-o ' + path_bin + 'f' + str(frame_index).zfill(3) +
'.bin -q ' + str(I_level))
os.system('bpgdec ' + path_bin + 'f' + str(frame_index).zfill(3) +
'.bin '
'-o ' + path_com + 'f' + str(frame_index).zfill(3) + '.png')
elif args.mode == 'MS-SSIM':
os.system(args.python_path + ' ' + args.CA_model_path +
'/encode.py --model_type 1 '
'--input_path ' + path + 'f' + str(frame_index).zfill(3) +
'.png' + ' --compressed_file_path ' + path_bin + 'f' +
str(frame_index).zfill(3) + '.bin' + ' --quality_level ' +
str(I_level))
os.system(args.python_path + ' ' + args.CA_model_path +
'/decode.py --compressed_file_path ' + path_bin + 'f' +
str(frame_index).zfill(3) + '.bin' + ' --recon_path ' +
path_com + 'f' + str(frame_index).zfill(3) + '.png')
# bits = os.path.getsize(path_bin + str(frame_index).zfill(3) + '.bin')
# bits = bits * 8
F0_com = misc.imread(path_com + 'f' + str(frame_index).zfill(3) + '.png')
F0_raw = misc.imread(path + 'f' + str(frame_index).zfill(3) + '.png')
F0_com = np.expand_dims(F0_com, axis=0)
F0_raw = np.expand_dims(F0_raw, axis=0)
if args.metric == 'PSNR':
mse = np.mean(
np.power(np.subtract(F0_com / 255.0, F0_raw / 255.0), 2.0))
quality = 10 * np.log10(1.0 / mse)
elif args.metric == 'MS-SSIM':
quality = MultiScaleSSIM(F0_com, F0_raw, max_val=255)
print('Frame', frame_index, args.metric + ' =', quality)
return quality
def get_msssim():
return MultiScaleSSIM(make_batched(inp_img), make_batched(out_img))
def compare_msssim(inp_img_batched, out_img_batched):
return MultiScaleSSIM(inp_img_batched, out_img_batched)
str_file_target = os.path.join("/mnt/Volume1/test/clic2020-devkit/yuv_result",name)
str_mid =os.path.join('/mnt/Volume1/test/clic2020-devkit/tng_save',name[:-5]+'rgb.tng')
im_re = Image.open(str_file_result)
im_ta = Image.open(str_file_target)
im_re_arr = np.asarray(im_re)
im_ta_arr = np.asarray(im_ta)
im_re_arr = im_re_arr.reshape((1,im_re_arr.shape[0],im_re_arr.shape[1],1))
im_ta_arr = im_ta_arr.reshape((1,im_ta_arr.shape[0],im_ta_arr.shape[1],1))
yuv = np.concatenate([im_re_arr,im_re_arr,im_re_arr], axis = 3)
yuv1 = np.concatenate([im_ta_arr,im_ta_arr,im_ta_arr], axis = 3)
score = MultiScaleSSIM(yuv,yuv1)
if np.isnan(score):
print(str_file_result)
score = 0
#print(score)
#str_w = 'input:' + p2+'; '+ 'target: ' + name + '; ' + 'ssim: ' + str(score)+ '\n'
score_nochange = float(data[i].split(':',4)[3])
ssims[i%3]=score_nochange
size = os.path.getsize(str_mid)
#print("size",size)
if not (i+1)%3:
tmp = tmp + size
ssim_tng = ssim_tng + score * 4
ssim_yuv = ssim_yuv + score_nochange*4
# print("tng",ssim_tng)
str(I_level))
os.system(args.python_path + ' ' + args.CA_model_path +
'/decode.py --compressed_file_path ' + path_com +
str(f + 1).zfill(3) + '.bin' + ' --recon_path ' + path_com +
'f' + str(f + 1).zfill(3) + '.png')
F0_com = misc.imread(path_com + 'f' + str(f + 1).zfill(3) + '.png')
F0_raw = misc.imread(path + 'f' + str(f + 1).zfill(3) + '.png')
#Quality(to WRQE)
if args.mode == 'PSNR':
mse = np.mean(np.power(np.subtract(F0_com / 255.0, F0_raw / 255.0), 2.0))
quality_frame[f] = 10 * np.log10(1.0 / mse)
elif args.mode == 'MS-SSIM':
quality_frame[f] = MultiScaleSSIM(np.expand_dims(F0_com, 0),
np.expand_dims(F0_raw, 0),
max_val=255)
with open(path_com + 'quality_' + str(f + 1).zfill(3) + '.bin', "wb") as ff:
ff.write(np.array(quality_frame[f], dtype=np.float32).tobytes())
bits = os.path.getsize(path_com + str(f + 1).zfill(3) + '.bin') \
+ os.path.getsize(path_com + 'quality_' + str(f + 1).zfill(3) + '.bin')
bits = bits * 8
#Bits(to WRQE)
bits_frame[f] = bits / Height / Width
print('Frame', f + 1)
print(args.mode + ' =', quality_frame[f], 'bpp =', bits_frame[f])
bits = os.path.getsize(path_bin + str(f + 1).zfill(3) + '.bin')
bits = bits * 8
F0_com = misc.imread(path_com + 'f' + str(f + 1).zfill(3) + '.png')
F0_raw = misc.imread(path + 'f' + str(f + 1).zfill(3) + '.png')
F0_com = np.expand_dims(F0_com, axis=0)
F0_raw = np.expand_dims(F0_raw, axis=0)
if args.metric == 'PSNR':
mse = np.mean(
np.power(np.subtract(F0_com / 255.0, F0_raw / 255.0), 2.0))
quality_frame[f] = 10 * np.log10(1.0 / mse)
elif args.metric == 'MS-SSIM':
quality_frame[f] = MultiScaleSSIM(F0_com, F0_raw, max_val=255)
bits_frame[f] = bits
print('Frame', f + 1, args.metric + ' =', quality_frame[f], 'bpp =',
bits_frame[f] / Height / Width)
p_frame_number = np.min([args.GOP - 1, args.frame - f - 1])
for p_frame in range(p_frame_number):
f = f + 1
F1_raw = misc.imread(path + 'f' + str(f + 1).zfill(3) + '.png')
F1_raw = np.expand_dims(F1_raw, axis=0)
F0_com, string_MV, string_Res, quality_com \