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Commit 4e70b030 authored by tomrink's avatar tomrink
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...@@ -208,7 +208,7 @@ class SRCNN: ...@@ -208,7 +208,7 @@ class SRCNN:
self.test_label_files = None self.test_label_files = None
# self.n_chans = len(data_params_half) + len(data_params_full) + 1 # self.n_chans = len(data_params_half) + len(data_params_full) + 1
self.n_chans = 6 self.n_chans = 3
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans)) self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
...@@ -267,16 +267,16 @@ class SRCNN: ...@@ -267,16 +267,16 @@ class SRCNN:
tmp = normalize(tmp, param, mean_std_dct) tmp = normalize(tmp, param, mean_std_dct)
data_norm.append(tmp) data_norm.append(tmp)
for param in sub_fields: # for param in sub_fields:
idx = params.index(param) # idx = params.index(param)
tmp = input_data[:, idx, :, :] # tmp = input_data[:, idx, :, :]
tmp = upsample_nearest(tmp) # tmp = upsample_nearest(tmp)
tmp = tmp[:, self.slc_y, self.slc_x] # tmp = tmp[:, self.slc_y, self.slc_x]
if param != 'refl_substddev_ch01': # if param != 'refl_substddev_ch01':
tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct) # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
else: # else:
tmp = np.where(np.isnan(tmp), 0, tmp) # tmp = np.where(np.isnan(tmp), 0, tmp)
data_norm.append(tmp) # data_norm.append(tmp)
# for param in data_params_full: # for param in data_params_full:
# idx = params_i.index(param) # idx = params_i.index(param)
...@@ -287,6 +287,7 @@ class SRCNN: ...@@ -287,6 +287,7 @@ class SRCNN:
# data_norm.append(tmp[:, self.slc_y, self.slc_x]) # data_norm.append(tmp[:, self.slc_y, self.slc_x])
# --------------------------------------------------- # ---------------------------------------------------
tmp = input_label[:, label_idx_i, ::2, ::2] tmp = input_label[:, label_idx_i, ::2, ::2]
tmp = tmp.copy()
tmp = np.where(np.isnan(tmp), 0, tmp) tmp = np.where(np.isnan(tmp), 0, tmp)
tmp = tmp[:, self.slc_y_2, self.slc_x_2] tmp = tmp[:, self.slc_y_2, self.slc_x_2]
tmp = self.upsample(tmp) tmp = self.upsample(tmp)
...@@ -299,8 +300,9 @@ class SRCNN: ...@@ -299,8 +300,9 @@ class SRCNN:
# ----------------------------------------------------- # -----------------------------------------------------
# ----------------------------------------------------- # -----------------------------------------------------
label = input_label[:, label_idx_i, ::2, ::2] label = input_label[:, label_idx_i, ::2, ::2]
label = normalize(label, label_param, mean_std_dct) label = label.copy()
# label = scale(label, label_param, mean_std_dct) # label = normalize(label, label_param, mean_std_dct)
label = scale(label, label_param, mean_std_dct)
label = label[:, self.y_128, self.x_128] label = label[:, self.y_128, self.x_128]
label = np.where(np.isnan(label), 0, label) label = np.where(np.isnan(label), 0, label)
...@@ -415,7 +417,7 @@ class SRCNN: ...@@ -415,7 +417,7 @@ class SRCNN:
conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2', kernel_size=KERNEL_SIZE, scale=scale) conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2', kernel_size=KERNEL_SIZE, scale=scale)
#conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3', kernel_size=KERNEL_SIZE, scale=scale) conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3', kernel_size=KERNEL_SIZE, scale=scale)
#conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale) #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
...@@ -628,10 +630,10 @@ class SRCNN: ...@@ -628,10 +630,10 @@ class SRCNN:
preds = np.concatenate(self.test_preds) preds = np.concatenate(self.test_preds)
print(labels.shape, preds.shape) print(labels.shape, preds.shape)
labels_denorm = denormalize(labels, label_param, mean_std_dct) # labels_denorm = denormalize(labels, label_param, mean_std_dct)
preds_denorm = denormalize(preds, label_param, mean_std_dct) # preds_denorm = denormalize(preds, label_param, mean_std_dct)
# labels_denorm = descale(labels, label_param, mean_std_dct) labels_denorm = descale(labels, label_param, mean_std_dct)
# preds_denorm = descale(preds, label_param, mean_std_dct) preds_denorm = descale(preds, label_param, mean_std_dct)
return labels_denorm, preds_denorm return labels_denorm, preds_denorm
...@@ -761,8 +763,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir): ...@@ -761,8 +763,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
print('INPUT: ', data.shape) print('INPUT: ', data.shape)
cld_opd_sres = nn.run_evaluate(data, ckpt_dir) cld_opd_sres = nn.run_evaluate(data, ckpt_dir)
# cld_opd_sres = descale(cld_opd_sres, label_param, mean_std_dct) cld_opd_sres = descale(cld_opd_sres, label_param, mean_std_dct)
cld_opd_sres = denormalize(cld_opd_sres, label_param, mean_std_dct) # cld_opd_sres = denormalize(cld_opd_sres, label_param, mean_std_dct)
_, ylen, xlen, _ = cld_opd_sres.shape _, ylen, xlen, _ = cld_opd_sres.shape
print('OUT: ', ylen, xlen) print('OUT: ', ylen, xlen)
......
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