def resNet152Test(): net = loadResNet(modelpath="../TestData/ResNet-152-model.hdf", layers="152") sample = loadResNetSample(net, "../TestData/tarantula.jpg") labels = loadLabels(synpath="../TestData/synsets.txt", wordpath="../TestData/synset_words.txt") res = net(gpuarray.to_gpu(sample)).get().reshape(-1) showLabelResults(res, labels, header=net.name)
def main(): net = loadResNet(modelpath="../../TestData/ResNet-50-model.hdf", layers="50") data = gpuarray.to_gpu(loadResNetSample(net, "../../TestData/tarantula.jpg")) labels = loadLabels(synpath="../../TestData/synsets.txt", wordpath="../../TestData/synset_words.txt") engine = buildRTEngine(net, inshape=data.shape, savepath="../TestData", dtype=DataType.float32) scoreModels(net, engine, data, labels) benchModels(net, engine, data)
def main():
inshape = (1, 3, 224, 224)
net = loadResNet(modelpath="../../TestData/ResNet-50-model.hdf",
layers="50")
outshape = net.dataShapeFrom(inshape)
caffeengine = buildRTEngineFromCaffe(
("../TestData/ResNet-50-deploy.prototxt",
"../TestData/ResNet-50-model.caffemodel"),
inshape=inshape,
outshape=outshape,
outlayers=["prob"],
dtype=DataType.float32,
savepath="../TestData")
onnxengine = buildRTEngineFromOnnx("../TestData/resnet50.onnx",
inshape=inshape,
outshape=outshape,
dtype=DataType.float32,
savepath="../TestData")
data = gpuarray.to_gpu(
loadResNetSample(net, "../../TestData/tarantula.jpg"))
labels = loadLabels(synpath="../../TestData/synsets.txt",
wordpath="../../TestData/synset_words.txt")
netData = net(data).get()
caffeData = caffeengine(data).get()
data = np.moveaxis(
np.array(Image.open("../../TestData/tarantula.jpg"), dtype=np.float32),
2, 0)
data = gpuarray.to_gpu(preprocessCaffe2Onnx(data)[np.newaxis, ...])
onnxData = onnxengine(data).get()
printResults(netData, labels, "Net")
printResults(caffeData, labels, "Caffe")
printResults(onnxData, labels, "Onnx")