def get_standard_result(im_name, sigma):
for name in os.listdir(standard_result_dir):
if im_name[:-4] in name and 'sigma_' + str(int(sigma)) + '-' in name:
if '-1st' in name:
res_1st = decode_res(name)
if '-2nd' in name:
res_2nd = decode_res(name)
res_1st = float(res_1st['PSNR'])
res_2nd = float(res_2nd['PSNR'])
return res_1st, res_2nd
for im_name in im_name_list:
print(im_name)
standard_list = list()
bm_noisy_2nd_list = list()
im_str = im_name[:-4]
sigma_list = [2, 5, 10, 20, 30, 40, 60, 80, 100]
for sigma in sigma_list:
sigma_str = 'sigma_' + str(sigma) + '_'
psnr1st, psnr2nd = get_standard_result(im_name, sigma)
standard_list.append(psnr2nd)
name = find_filename_in_dir(
search_dir, include_str_list=[im_str, sigma_str, 'BM-noisy'])
psnr = decode_res(name)['PSNR']
bm_noisy_2nd_list.append(psnr)
x_list = sigma_list
y_list = standard_list
k_ = ['name', 'x', 'y', 'color', 'linestyle']
v_ = ['standard', x_list, y_list, 'green', '--']
line_dict_1 = dict(zip(k_, v_))
x_list = sigma_list
y_list = bm_noisy_2nd_list
v_ = ['2nd_use_noisy_BM', x_list, y_list, 'red', '--']
line_dict_2 = dict(zip(k_, v_))
plt = plot_dict_res(line_dict_1,
line_dict_2,
'nW': [0],
'NW': [8, 10, 12, 16, 20],
# 'lamb': np.arange(4, 12),
}
key = 'lamb'
val_list = np.arange(4, 12)
for condition in dict_product(hyper_dict):
key_psnr_list = list()
for val in val_list:
key_condition = {key: val}
for im_name in os.listdir(search_dir):
if is_contain_all(im_name, im_na, condition, key_condition):
kv = decode_res(im_name)
key_psnr_list.append(kv['psnr'])
print(condition)
print(key_psnr_list)
l1 = plt.plot(val_list, key_psnr_list, 'g--', label='psnr')
for x, psnr in zip(val_list, key_psnr_list):
plt.text(x,
psnr,
'cpp' + '%.3f' % psnr,
ha='center',
va='top',
fontsize=10,
color='g')
plt.rcParams['savefig.dpi'] = 300 # 图片像素