def show_pan_img(image):
pan_ext=np.expand_dims(image,axis=0)
plt.figure()
th_pan = image_quantile(pan_ext, np.array([0.01, 0.99]))
pan_ext = image_stretch(np.squeeze(pan_ext),np.squeeze(th_pan))
plt.imshow(pan_ext,cmap='gray',clim=[0,1])
plt.title('PANCHROMATIC'), plt.axis('off')
plt.show()
def show_ms_img(image, rgb_idx):
th_msrgb = image_quantile(np.squeeze(image[rgb_idx,:,:]), np.array([0.01, 0.99]));
d = image_stretch(np.squeeze(image[rgb_idx,:,:]),th_msrgb)
d[d<0] = 0
d[d>1] = 1
plt.imshow(d.transpose(1,2,0))
plt.title('MULTISPECTRAL LOW RESOLUTION'), plt.axis('off')
plt.show()
#%% save data choice one for time
export2(I_Fus_CNN, test_dir_out)
#%% Visualization
from image_quantile import image_quantile, image_stretch
import matplotlib.pyplot as plt
plt.close('all')
RGB_indexes_MS = np.array([2, 1, 0])
#I_PAN=np.expand_dims(I_PAN,axis=0) # we do not use in this case
I_PAN_show = I_PAN.transpose(2, 0, 1)
plt.figure()
plt.subplot(231)
th_PANrgb = image_quantile(np.squeeze(I_PAN_show[RGB_indexes_MS, :, :]),
np.array([0.01, 0.99]))
PAN = image_stretch(np.squeeze(I_PAN_show[RGB_indexes_MS, :, :]), th_PANrgb)
PAN[PAN < 0] = 0
PAN[PAN > 1] = 1
plt.imshow(PAN.transpose(1, 2, 0))
plt.title('MS Image'), plt.axis('off')
#RGB_indexes = RGB_indexes - 1
RGB_indexes_HS = np.array([20, 14, 7
]) # matlab 8,15,21, therefore transpose e less one
plt.subplot(232)
th_MSrgb = image_quantile(np.squeeze(I_MS_LR[RGB_indexes_HS, :, :]),
np.array([0.01, 0.99]))
d = image_stretch(np.squeeze(I_MS_LR[RGB_indexes_HS, :, :]), th_MSrgb)
d[d < 0] = 0
I_MS_HR = PNN_test(I_MS_LR, I_PAN, inputImg, PNN_model, net, path, mode,
epochs)
#%% save data
export2(I_MS_HR, test_dir_out)
#%% Visualization
from image_quantile import image_quantile, image_stretch
import matplotlib.pyplot as plt
plt.close('all')
I_PAN = np.expand_dims(I_PAN, axis=0)
plt.figure()
plt.subplot(131)
th_PAN = image_quantile(I_PAN, np.array([0.01, 0.99]))
PAN = image_stretch(np.squeeze(I_PAN), np.squeeze(th_PAN))
plt.imshow(image_stretch(np.squeeze(I_PAN), np.squeeze(th_PAN)),
cmap='gray',
clim=[0, 1])
plt.title('PANCHROMATIC'), plt.axis('off')
RGB_indexes = np.array(inputImg['RGB_indexes'])
RGB_indexes = RGB_indexes - 1
plt.subplot(132)
th_MSrgb = image_quantile(np.squeeze(I_MS_LR[RGB_indexes, :, :]),
np.array([0.01, 0.99]))
d = image_stretch(np.squeeze(I_MS_LR[RGB_indexes, :, :]), th_MSrgb)
d[d < 0] = 0
d[d > 1] = 1
print("Time CNN:",elapsed,'sec')
#%% save data choice one for time
export2(I_Fus_CNN,test_dir_out)
#%% Visualization
from image_quantile import image_quantile, image_stretch
import matplotlib.pyplot as plt
plt.close('all')
I_PAN=np.expand_dims(I_PAN,axis=0)
plt.figure()
plt.subplot(231)
th_PAN = image_quantile(I_PAN, np.array([0.01, 0.99]))
PAN = image_stretch(np.squeeze(I_PAN),np.squeeze(th_PAN))
plt.imshow( image_stretch(np.squeeze(I_PAN),np.squeeze(th_PAN)),cmap='gray',clim=[0,1])
plt.title('PAN Image'), plt.axis('off')
RGB_indexes = np.array([3,2,1])
#RGB_indexes = RGB_indexes - 1
plt.subplot(232)
th_MSrgb = image_quantile(np.squeeze(I_MS[RGB_indexes,:,:]), np.array([0.01, 0.99])); #modifico delle cose 06/04
d=image_stretch(np.squeeze(I_MS_LR[RGB_indexes,:,:]),th_MSrgb)
d[d<0]=0
d[d>1]=1
plt.imshow(d.transpose(1,2,0))
plt.title('MS Image (pan scale)'), plt.axis('off')