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Commit 8041d50e authored by tomrink's avatar tomrink
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modules/deeplearning/cloud_opd_srcnn_viirs.py
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...@@ -65,7 +65,7 @@ print('data_params_full: ', data_params_full) ...@@ -65,7 +65,7 @@ print('data_params_full: ', data_params_full)
print('label_param: ', label_param) print('label_param: ', label_param)
KERNEL_SIZE = 3 # target size: (128, 128) KERNEL_SIZE = 3 # target size: (128, 128)
LEN_X = LEN_Y = 128 # LEN_X = LEN_Y = 128
def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.relu, padding='SAME', def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.relu, padding='SAME',
...@@ -674,10 +674,9 @@ class SRCNN: ...@@ -674,10 +674,9 @@ class SRCNN:
def run_restore_static(directory, ckpt_dir, out_file=None): def run_restore_static(directory, ckpt_dir, out_file=None):
nn = SRCNN() nn = SRCNN()
labels, preds = nn.run_restore(directory, ckpt_dir) labels_denorm, preds_denorm = nn.run_restore(directory, ckpt_dir)
if out_file is not None: if out_file is not None:
np.save(out_file, np.save(out_file, [labels_denorm, preds_denorm])
[np.squeeze(labels), preds.argmax(axis=3), preds[:, :, :, 0], preds[:, :, :, 1], preds[:, :, :, 2]])
def run_evaluate_static(in_file, out_file, ckpt_dir): def run_evaluate_static(in_file, out_file, ckpt_dir):
......
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