Changeset - c934d44cdf5c
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Laman - 6 years ago 2019-05-06 13:02:49

tensorboard logging, created a configuration file
4 files changed with 28 insertions and 14 deletions:
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exp/kerokero/config.py
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new file 100644
 
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)
exp/kerokero/ftp.py
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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"))
exp/kerokero/test.py
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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)))
exp/kerokero/train.py
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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))
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