update readme

README.md

@@ -6,28 +6,39 @@
 - catalyst == 19.06.5
 
 # How to train 
-- In `configs/config.yml`  
-Change: `stages/data_params/root` to your root data that you download from Kaggle
+## Pretrained with controls
+```bash
+bash bin/train_control.sh
+```
+
+Pretrained models are saved at:
+`/raid/bac/kaggle/logs/recursion_cell/pretrained_controls/$channels/se_resnext50_32x4d/`  
+where `channels` can be: `[1,2,3,4,5], etc`
 
-- In `bin/train.sh`  
-Change: 
-  - `export CUDA_VISIBLE_DEVICES=2,3` which GPUs are used for training
-  - `LOGDIR`: saved checkpoints, logs, etc
-
-- Run: `bash bin/train.sh` 
-- Take a coffe or go to sleep
+## Train with pseudo data
+```bash
+bash bin/train_pseudo.sh
+```
 
+* `PRETRAINED_CONTROL`: is the root folder of pretrained models above  
 
-# How to predict 
-Please refer `make_submission.py`. 
+* `--model_params/weight=
+$PRETRAINED_CONTROL/$channels/se_resnext50_32x4d/checkpoints/best.pth:str \`  is the weight of 
+corresponding model pretrained on controls dataset.
 
-- Change following:
-```python
-    test_csv = '/raid/data/kaggle/recursion-cellular-image-classification/test.csv'
-    # test_csv = './csv/valid_0.csv'
-    log_dir = "/raid/bac/kaggle/logs/recursion_cell/test/rgb_no_crop_512_accum2_456/se_resnext50_32x4d/"
-    root = "/raid/data/kaggle/recursion-cellular-image-classification/"
 
+## Train with usually data
+Similar to `Train with pseudo data` part
+```bash
+bash bin/train.sh
 ```
 
+* `PRETRAINED_CONTROL`: is the root folder of pretrained models above  
+
+* `--model_params/weight=
+$PRETRAINED_CONTROL/$channels/se_resnext50_32x4d/checkpoints/best.pth:str \`  is the weight of 
+corresponding model pretrained on controls dataset.
+
+
+
 - Run: `python src/make_submission.csv`

bin/train.sh

@@ -4,6 +4,7 @@ export CUDA_VISIBLE_DEVICES=2,3
 RUN_CONFIG=config.yml
 
 
+PRETRAINED_CONTROL=/raid/bac/kaggle/logs/recursion_cell/pretrained_controls/
 for channels in [1,2,3,4,5]; do
     for fold in 0; do
         LOGDIR=/raid/bac/kaggle/logs/recursion_cell/test/190824/dont_drop_1/fold_$fold/se_resnext50_32x4d/
@@ -14,6 +15,7 @@ for channels in [1,2,3,4,5]; do
             --stages/data_params/channels=$channels:list \
             --stages/data_params/train_csv=./csv/train_$fold.csv:str \
             --stages/data_params/valid_csv=./csv/valid_$fold.csv:str \
+            --model_params/weight=$PRETRAINED_CONTROL/$channels/se_resnext50_32x4d/checkpoints/best.pth:str \
             --verbose
     done
 done

bin/train_control.sh

@@ -3,7 +3,7 @@
 export CUDA_VISIBLE_DEVICES=2,3
 RUN_CONFIG=config_control.yml
 
-for channels in [1,2,3,4,6] [1,2,3,5,6] [1,2,4,5,6] [1,3,4,5,6] [2,3,4,5,6]; do
+for channels in [1,2,3,4,5] [1,2,3,4,6] [1,2,3,5,6] [1,2,4,5,6] [1,3,4,5,6] [2,3,4,5,6]; do
     LOGDIR=/raid/bac/kaggle/logs/recursion_cell/pretrained_controls/$channels/se_resnext50_32x4d/
     catalyst-dl run \
         --config=./configs/${RUN_CONFIG} \

bin/train_pseudo.sh

@@ -4,9 +4,9 @@ export CUDA_VISIBLE_DEVICES=2,3
 RUN_CONFIG=config_pseudo.yml
 
 
-PRETRAINED_CONTROL=''
-for channels in [1,2,3,4,5] [1,2,3,4,6] [1,2,3,5,6] [1,2,4,5,6] [1,3,4,5,6] [2,3,4,5,6]; do
-    for fold in 0; do
+PRETRAINED_CONTROL=/raid/bac/kaggle/logs/recursion_cell/pretrained_controls/
+for channels in [1,2,3,4,6] [1,2,3,5,6]; do
+    for fold in 0 1 2 3 4; do
         LOGDIR=/raid/bac/kaggle/logs/recursion_cell/pseudo_from_control/$channels/fold_$fold/se_resnext50_32x4d/
         catalyst-dl run \
             --config=./configs/${RUN_CONFIG} \
@@ -15,7 +15,7 @@ for channels in [1,2,3,4,5] [1,2,3,4,6] [1,2,3,5,6] [1,2,4,5,6] [1,3,4,5,6] [2,3
             --stages/data_params/channels=$channels:list \
             --stages/data_params/train_csv=./csv/pseudo/train_$fold.csv:str \
             --stages/data_params/valid_csv=./csv/pseudo/valid_$fold.csv:str \
-            --model_params/weight=$PRETRAINED_CONTROL/$channels/se_resnext50_32x4d/checkpoints/best.pth \
+            --model_params/weight=$PRETRAINED_CONTROL/$channels/se_resnext50_32x4d/checkpoints/best.pth:str \
             --verbose
     done
 done