Open suikammd opened 5 years ago
I test the caffemodel using the following methods, but it turns out a low accuracy? Maybe the caffemodel not the right one?
import caffe import numpy as np net_file = './caffe-googlenet-bn/deploy.prototxt' model = './caffe-googlenet-bn/snapshots/googlenet_bn_stepsize_6400_iter_1200000.caffemodel' caffe.set_mode_gpu() caffe.set_device(0) net = caffe.Net(net_file, model, caffe.TEST) image_mean = np.load('./mean.npy') image_path = '/data/ImageNet2012/ILSVRC2012/ILSVRC2012_img_val/' image_txt = './label.txt' data_shape = net.blobs['data'].data.shape transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape}) transformer.set_transpose('data', (2, 0, 1)) transformer.set_mean('data', image_mean) transformer.set_raw_scale('data', 255) transformer.set_channel_swap('data', (2, 1, 0)) count = 0 print "start!" for line in f.readlines(): line = line.strip().split(" ") img = image_path + line[0] image = caffe.io.load_image(img) transformed_image = transformer.preprocess('data', image) net.blobs['data'].data[...] = transformed_image output = net.forward() output_prob = output['prob'][0] if int(line[1]) in output_prob.argsort()[-5:]: count += 1 print "accuracy", count * 1.0 / i, count print "top5: %lf", count * 1.0 / 50000
Thanks for your response!
I test the caffemodel using the following methods, but it turns out a low accuracy? Maybe the caffemodel not the right one?
Thanks for your response!