# 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