Open abaooaba opened 5 years ago
yes,I used it ,i also have the same question
yes,I used it ,i also have the same question
Well,i have the issue too.In the getLabeledDataVector() function ,change tho return type to a list.That means change "return output;" to "return list(output);" It works for me ,maybe u can try it.
import sys
import sys
path = "C:\Program Files\libsvm-3.24\python"
sys.path.append(path)
import os
import itertools
import random
from PIL import Image
from svmutil import * # libSVM
# Image data constants
DIMENSION = 32
ROOT_DIR = "images/"
DAL = "dalmatian"
DOLLAR = "dollar_bill"
PIZZA = "pizza"
BALL = "soccer_ball"
FLOWER = "sunflower"
CLASSES = [DAL, DOLLAR, PIZZA, BALL, FLOWER]
# libsvm constants
LINEAR = 0
RBF = 2
# Other
USE_LINEAR = False
IS_TUNING = False
def main():
try:
train, tune, test = getData(IS_TUNING)
models = getModels(train)
results = None
if IS_TUNING:
print ("!!! TUNING MODE !!!")
results = classify(models, tune)
else:
results = classify(models, test)
print()
totalCount = 0
totalCorrect = 0
for clazz in CLASSES:
count, correct = results[clazz]
totalCount += count
totalCorrect += correct
print ("%s %d %d %f" % (clazz, correct, count, (float(correct) / count)))
print ("%s %d %d %f" % ("Overall", totalCorrect, totalCount, (float(totalCorrect) / totalCount)))
except Exception as e:
print (e)
return 5
def classify(models, dataSet):
results = {}
for trueClazz in CLASSES:
count = 0
correct = 0
for item in dataSet[trueClazz]:
predClazz, prob = predict(models, item)
print ("%s,%s,%f" % (trueClazz, predClazz, prob))
count += 1
if trueClazz == predClazz: correct += 1
results[trueClazz] = (count, correct)
return results
def predict(models, item):
maxProb = 0.0
bestClass = ""
for clazz, model in models.items():
prob = predictSingle(model, item)
if prob > maxProb:
maxProb = prob
bestClass = clazz
return (bestClass, maxProb)
def predictSingle(model, item):
output = svm_predict([0], [item], model, "-q -b 1")
prob = output[2][0][0]
return prob
def getModels(trainingData):
models = {}
param = getParam(USE_LINEAR)
for c in CLASSES:
labels, data = getTrainingData(trainingData, c)
prob = svm_problem(labels, data)
m = svm_train(prob, param)
models[c] = m
return models
def getTrainingData(trainingData, clazz):
labeledData = getLabeledDataVector(trainingData, clazz, 1)
negClasses = [c for c in CLASSES if not c == clazz]
for c in negClasses:
ld = getLabeledDataVector(trainingData, c, -1)
labeledData += ld
random.shuffle(labeledData)
unzipped = [list(t) for t in zip(*labeledData)]
# labels, data = unzipped[0], unzipped[1]
labels, data = unzipped or ([], [])
return (labels, data)
def getParam(linear = True):
param = svm_parameter("-q")
param.probability = 1
if(linear):
param.kernel_type = LINEAR
param.C = .01
else:
param.kernel_type = RBF
param.C = .01
param.gamma = .00000001
return param
def getLabeledDataVector(dataset, clazz, label):
data = dataset[clazz]
labels = [label] * len(data)
output = zip(labels, data)
return list(output)
def getData(generateTuningData):
trainingData = {}
tuneData = {}
testData = {}
for clazz in CLASSES:
(train, tune, test) = buildTrainTestVectors(buildImageList(ROOT_DIR + clazz + "/"), generateTuningData)
trainingData[clazz] = train
tuneData[clazz] = tune
testData[clazz] = test
return (trainingData, tuneData, testData)
def buildImageList(dirName):
imgs = [Image.open(dirName + fileName).resize((DIMENSION, DIMENSION)) for fileName in os.listdir(dirName)]
imgs = [list(itertools.chain.from_iterable(img.getdata())) for img in imgs]
return imgs
def buildTrainTestVectors(imgs, generateTuningData):
# 70% for training, 30% for test.
testSplit = int(.7 * len(imgs))
baseTraining = imgs[:testSplit]
test = imgs[testSplit:]
training = None
tuning = None
if generateTuningData:
# 50% of training for true training, 50% for tuning.
tuneSplit = int(.5 * len(baseTraining))
training = baseTraining[:tuneSplit]
tuning = baseTraining[tuneSplit:]
else:
training = baseTraining
return (training, tuning, test)
if __name__ == "__main__":
# sys.exit(main())
main()
this works for me
excuse me,I run your code,However, I have the problem of "unsupported operand type(s) for +=: 'zip' and 'zip'",Do you know what caused this?Thanks!