add parse_res_file in README

README.md

@@ -80,13 +80,25 @@ To train the CNN, use the following command, where:
 python main_holo.py --checkpoint_dir /lium/raid01_c/tahon/holography/checkpoints/ --sample_dir /lium/raid01_c/tahon/holography/eval_samples/ --params "phase=train" --save_dir "./data1/"
 ```
 
+All results and training information are summarized in res files which are stored in `sample_dir`directory together with predicted images (.tiff). To get the results over all epochs on the HOLODEEP database (evaluation step), the following command will help:
+```
+python parse_res_file.py /lium/raid01_c/tahon/holography/eval_samples/run-test2020-04-12_12\:14\:29.082341/res
+NumEpochs: 150
+BestEpoch  140
+avg 0,040 55,540
+0,0 0,024 58,080
+1,0 0,030 56,380
+1,5 0,038 55,500
+2,0 0,050 54,340
+2,5 0,062 53,400
+```
 
 ## Test
-To test the model which is located here `/lium/raid01_c/tahon/holography/checkpoints/run-test2020-04-12_12\:14\:29.082341/, use one of these commands. The first one is the detailed Python command, while the second one, run the job on the cluster via slurm (test on DATAEVAL and HOLODEEP).
+To test the model which is located here `/lium/raid01_c/tahon/holography/checkpoints/run-test2020-04-12_12\:14\:29.082341/, use one of these commands. The first one is the detailed Python command, while the second one, run the job on the cluster with sbatch (test on DATAEVAL and HOLODEEP).
 ```
 python main_holo.py --params "phase=test" --test_noisy_img /lium/raid01_c/tahon/holography/HOLODEEPmat/PATTERN1/MFH_0/NoisyPhase.mat --test_noisy_key 'NoisyPhase' --test_clean_img /lium/raid01_c/tahon/holography/HOLODEEPmat/PATTERN1/PhaseDATA.mat --test_clean_key 'Phase' --test_flip False --test_ckpt_index /lium/raid01_c/tahon/holography/checkpoints/run-test2020-04-12_12\:14\:29.082341/
 
-./run_holo_test.sh /lium/raid01_c/tahon/holography/checkpoints/run-test2020-04-12_12\:14\:29.082341/
+sbatch /run_holo_test.sh /lium/raid01_c/tahon/holography/checkpoints/run-test2020-04-12_12\:14\:29.082341/
 ```
 
 ## Results