eval.py 文件源码

def eval(testSetPath, clipSize):

    checkTestAndTruths(testSetPath)
    checkDirs(testSetPath)

    imgTestDir = os.path.join(testSetPath, 'test/')

    caffe.set_mode_cpu()

    printTitle("Loading caffe model")
    net = caffe.Net(
          'src/deploy.prototxt'
        , 'src/fcn8s-heavy-pascal.caffemodel'
        , caffe.TEST)
    print("Model loaded.")

    testImgPaths = []
    for testImg in os.listdir(imgTestDir):
        testImgPaths.append(imgTestDir + testImg)
    testImgPaths.sort()

    printTitle("Generating predictions")
    totalPredictTime = 0.00
    for count in range(0, len(testImgPaths)):
        totalPredictTime += predict(testImgPaths[count], testSetPath, clipSize, net)

    printTitle("Average prediction time: %.3f" % (totalPredictTime / len(testImgPaths)))

    printTitle("Generating scores")
    segPath = os.path.join(testSetPath, 'seg/')
    truthPath = os.path.join(testSetPath, 'truth/')
    computeAccuracies(testSetPath, segPath, truthPath)

    print("eval.py has completed.")


# Make folders for seg, labelled and mask predictions