snapshot...

modules/deeplearning/cloud_opd_srcnn_viirs.py

@@ -65,7 +65,7 @@ print('data_params_full: ', data_params_full)
 print('label_param: ', label_param)
 
 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',
@@ -674,10 +674,9 @@ class SRCNN:
 
 def run_restore_static(directory, ckpt_dir, out_file=None):
     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:
-        np.save(out_file,
-                [np.squeeze(labels), preds.argmax(axis=3), preds[:, :, :, 0], preds[:, :, :, 1], preds[:, :, :, 2]])
+        np.save(out_file, [labels_denorm, preds_denorm])
 
 
 def run_evaluate_static(in_file, out_file, ckpt_dir):