# loadcsv=1,
logFormat='acc:{acc:.3f}, loss:{loss:.3f}',
sortkey='loss',
# loged=False,
saveResoult=False,
)
c.names.sort(key=lambda x: readgt(x).shape[0])
for name in c.names[:]:
img, gt = readimg(name), readgt(name)
prob = predict((name))
re = prob.argmax(2)
e.evalu(re, gt, name)
gtc = labelToColor(gt, colors)
rec = labelToColor(re, colors)
show(img[::10, ::10], gtc[::10, ::10], (gt != re)[::10, ::10],
rec[::10, ::10])
# diff = binaryDiff(re,gt)
# show(img,diff,re)
# show(img,diff)
# show(diff)
# yellowImg=gt[...,None]*img+(npa-[255,255,0]).astype(np.uint8)*~gt[...,None]
# show(yellowImg,diff)
# imsave(pathjoin(args.out,name+'.png'),uint8(re))
print args.restore, e.loss.mean()
#map(lambda n:show(readimg(n),e[n],readgt(n)),e.low(80).index[:])
class ArgList(list):
'''
## saveResoult=False,
# )
c.names.sort(key=lambda x:readgt(x).shape[0])
# c.names[0] = '01'
# f = open(pathjoin(args.out,'Pr-all1.txt'),'w')
# f.read()
# f.write('Pre\tRec\tAcc\tM\n')
for name in c.names[:]:
img,gt = readimg(name),readgt(name)>0
prob = predict(toimg(name))
re = prob.argmax(2)
# res= re*1.0
# e.evalu(re,gt,name)
show(img,gt,re)
# imsave(pathjoin(args.out,name+'.png'),uint8(re))
# for x in range(0,prob.shape[1]):
# for y in range(0,prob.shape[0]):
# res[y][x] = prob[y][x][1]
# imsave(pathjoin(args.out,name+'res.png'),res)
# f = open(pathjoin(args.out,'Pr-'+name+'.txt'),'w')
## f.read()
# f.write('Pre\tRec\tAcc\tM\n')
# res1 = res
# TP,TN,FP,FN,TOL = 0 ;
for a in range(1,101,1):
jobDir = (os.path.split(dirname(filePath))[-1])
expDir = (os.path.split((filePath))[-1])
cf.project = cf.project or jobDir
cf.experment = cf.experment or expDir
cf.savename = '%s-%s-%s'%(cf.netdir,cf.experment,cf.project)
cf.toValGtPath = cf.toValGtPath or cf.toGtPath
#cf.valArgs = cf.valArgs or cf.trainArgs
c.update(cf)
c.cf = cf
c.weightsPrefix = fileJoinPath(__file__,pathjoin(c.tmpdir,'weights/%s-%s'%(c.netdir,c.experment)))
#show- map(readimg,c.names[:10])
if __name__ == '__main__':
setMod('train')
img = readimg(c.names[0])
gt = readgt(c.names[0])
show(img,gt)
loga(gt)
pass