score = uNet5Stackb.evaluate(interpolated_tf, groundtruth_img, verbose=0)
probs = uNet5Stackb.predict(interpolated_tf, verbose=0)
# Computing and plotting mse and nmse
mse = [mean_squared_error(groundtruth_img[idx][:, :, 0], probs[idx][:, :, 0]) for idx in
range(len(groundtruth))]
mse_den = [mean_squared_error(groundtruth_img[idx][:, :, 0], np.zeros(groundtruth_img[idx][:, :, 0].shape))
for idx in range(len(groundtruth))]
nmse = [mse[idx] / mse_den[idx] for idx in range(len(groundtruth))]
mse_int = [mean_squared_error(groundtruth_img[idx][:, :, 0], interpolated_tf[idx][:, :, 0]) for idx in
range(len(groundtruth))]
nmse_int = [mse_int[idx] / mse_den[idx] for idx in range(len(groundtruth))]
pR.plot_mse(mse, mse_int)
plt.title("Mse of uNetStackb")
# Plot a random image
pR.plot_hr(probs[0][:, :, 0], groundtruth_img[0][:, :, 0], interpolated_tf[0][:, :, 0],
downsampled_img[0][:, :, 0])
plt.title("Random reconstruction by uNetStackb")
pR.plot_mse(nmse, nmse_int)
plt.title('Normalized mean squared error uNetStackb')
# Plotting worst reconstructed image
max_mse = max(mse)
idx_bad = mse.index(max_mse)
pR.plot_hr(probs[idx_bad][:, :, 0], groundtruth_img[idx_bad][:, :, 0], interpolated_tf[idx_bad][:, :, 0],
downsampled_img[idx_bad][:, :, 0])
mean_squared_error(groundtruth_test_img[idx][:, :, 0],
np.zeros(groundtruth_test_img[idx][:, :, 0].shape))
for idx in range(len(groundtruth_test_img))
]
nmseb = [mseb[idx] / mse_denb[idx] for idx in range(len(groundtruth_test_img))]
mse_intb = [
mean_squared_error(groundtruth_test_img[idx][:, :, 0],
interpolated_test_tf[idx][:, :, 0])
for idx in range(len(groundtruth_test_img))
]
nmse_intb = [
mse_intb[idx] / mse_denb[idx] for idx in range(len(groundtruth_test_img))
]
pR.plot_mse(mseb, mse_intb)
plt.title("Mse uNetStackb")
pR.plot_hr(probsb[0][:, :, 0], groundtruth_test_img[0][:, :, 0],
interpolated_test_tf[0][:, :, 0], downsampled_test_img[0][:, :, 0])
plt.title("Rec by uNetStackb")
pR.plot_mse(nmseb, nmse_intb)
plt.title('Normalized mean squared error uNetStackb')
# Plotting worst reconstructed image
max_mseb = max(mseb)
idx_badb = mseb.index(max_mseb)
pR.plot_hr(probsb[idx_badb][:, :, 0], groundtruth_test_img[idx_badb][:, :, 0],
interpolated_test_tf[idx_badb][:, :, 0],
downsampled_test_img[idx_badb][:, :, 0])
idx_hmsebisb = [