# HG changeset patch
# User Laman
# Date 2019-05-06 13:02:49
# Node ID c934d44cdf5c6c41e0776299768ea60ca6ecc122
# Parent  8b30e6dba468af6ca97c17a1e2db530e8bb66518

tensorboard logging, created a configuration file

diff --git a/exp/kerokero/config.py b/exp/kerokero/config.py
new file mode 100644
--- /dev/null
+++ b/exp/kerokero/config.py
@@ -0,0 +1,10 @@
+import os
+import json
+import logging as log
+
+
+log.basicConfig(level=log.INFO,format="%(asctime)s %(levelname)s: %(message)s")
+thisDir=os.path.dirname(__file__)
+
+with open(os.path.join(thisDir,"ftp.json")) as f:
+	ftp=json.load(f)
diff --git a/exp/kerokero/ftp.py b/exp/kerokero/ftp.py
--- a/exp/kerokero/ftp.py
+++ b/exp/kerokero/ftp.py
@@ -1,17 +1,14 @@
 import os
-import json
 import ftplib
 import logging as log
 
-thisDir=os.path.dirname(__file__)
-with open(os.path.join(thisDir,"ftp.json")) as f:
-	cfg=json.load(f)
+import config as cfg
 
 
 def push(path):
 	ftp=ftplib.FTP_TLS()
-	ftp.connect(cfg["host"],cfg["port"])
-	ftp.login(cfg["user"],cfg["password"])
+	ftp.connect(cfg.ftp["host"],cfg.ftp["port"])
+	ftp.login(cfg.ftp["user"],cfg.ftp["password"])
 
 	filename=os.path.basename(path)
 
@@ -23,4 +20,4 @@ def push(path):
 
 
 if __name__=="__main__":
-	push(os.path.join(thisDir,"ftp.py"))
+	push(os.path.join(cfg.thisDir,"ftp.py"))
diff --git a/exp/kerokero/test.py b/exp/kerokero/test.py
--- a/exp/kerokero/test.py
+++ b/exp/kerokero/test.py
@@ -1,4 +1,5 @@
 import argparse
+import logging as log
 
 import numpy as np
 from keras.models import load_model
@@ -6,6 +7,7 @@ from keras.models import load_model
 from prepare_data import loadDataset,Sample
 from analyzer.epoint import EPoint
 from analyzer.corners import Corners
+import config as cfg
 
 
 parser=argparse.ArgumentParser()
@@ -15,13 +17,15 @@ args=parser.parse_args()
 
 model=load_model(args.model)
 
-print("loading data...")
+log.info("loading data...")
 with np.load(args.data) as data:
 	trainImages=data["trainImages"]
 	trainLabels=data["trainLabels"]
 	testImages=data["testImages"]
 	testLabels=data["testLabels"]
-print("done")
+log.info("done")
+
+log.info(model.evaluate(testImages.reshape((-1,224,224,1)),testLabels))
 
 for img in testImages:
 	label=model.predict(np.reshape(img,(1,224,224,1)))
diff --git a/exp/kerokero/train.py b/exp/kerokero/train.py
--- a/exp/kerokero/train.py
+++ b/exp/kerokero/train.py
@@ -1,14 +1,16 @@
+import os
+from time import time
 import argparse
 import logging as log
 
 import numpy as np
 from keras.layers import Conv2D,Dropout,Dense,Flatten,MaxPooling2D,BatchNormalization
 from keras.models import Sequential,load_model
+from keras.callbacks import TensorBoard
 
+import config as cfg
 import ftp
 
-log.basicConfig(level=log.INFO,format="%(asctime)s %(levelname)s: %(message)s")
-
 parser=argparse.ArgumentParser()
 parser.add_argument("data")
 parser.add_argument("--load_model")
@@ -82,10 +84,11 @@ with np.load(args.data) as data:
 	testLabels=data["testLabels"]
 log.info("done")
 
+tensorboard = TensorBoard(log_dir=os.path.join(cfg.thisDir,"../logs","{}".format(time())))
 for i in range(args.initial_epoch//10,args.epochs//10):
-	model.fit(trainImages.reshape((-1,224,224,1)),trainLabels,epochs=(i+1)*10,initial_epoch=i*10,batch_size=128,validation_split=0.2)
+	model.fit(trainImages.reshape((-1,224,224,1)),trainLabels,epochs=(i+1)*10,initial_epoch=i*10,batch_size=128,validation_split=0.2,callbacks=[tensorboard])
 	path=args.save_model.format((i+1)*10)
 	log.info("saving model...")
 	model.save(path)
-	if i%2==1: ftp.push(path)
-log.info(model.evaluate(testImages,testLabels))
+	ftp.push(path)
+log.info(model.evaluate(testImages.reshape((-1,224,224,1)),testLabels))