caffe.set_device(1)
net = caffe.Net(net_file, caffe_model, caffe.TEST)
coco_names = np.loadtxt('../lib/coco_names.txt', str, delimiter='\n')
data_dir = '../demo/images/'
out_dir = '../demo/output/'
if not os.path.exists(out_dir):
os.makedirs(out_dir)
imgpath = os.listdir(data_dir)
for imgfile in imgpath:
result = open(out_dir + '/' + imgfile.split('.')[0] + '.txt', 'w+')
starttime = time.time()
cls_det = multi_scale_test_net_512(net,
data_dir + '/' + imgfile,
soft_nms=False)
endtime = time.time()
print 'speed: {:.3f}s / iter'.format(endtime - starttime)
result.write(imgfile.split('.')[0] + '\n')
for j in range(1, 81):
if len(cls_det[j][0]) != 0:
for i in range(len(cls_det[j][0])):
result.write(
str(coco_names[j - 1]) + ' ' +
str(int(cls_det[j][0][i][0])) + ' ' +
str(int(cls_det[j][0][i][1])) + ' ' +
str(int(cls_det[j][0][i][2])) + ' ' +
str(int(cls_det[j][0][i][3])) + ' ' +
str(cls_det[j][0][i][4]) + '\n')
result.close()
caffemodel = path + model
print('Start evaluating: ' + caffemodel)
net = caffe.Net(prototxt, caffemodel, caffe.TEST)
net.name = os.path.splitext(os.path.basename(model))[0]
cfg.net_name = net.name
try:
iter = int(net.name.split('_')[-1])
except:
iter = 000000
if single_scale is True:
single_scale_test_net(net, imdb, targe_size=input_size)
else:
if input_size == 320:
multi_scale_test_net_320(net, imdb)
else:
multi_scale_test_net_512(net, imdb)
mAP[iter] = cfg.mAP
keys = mAP.keys()
keys.sort()
templine = []
print(
"#########################################################################################################"
)
print(
"#########################################################################################################"
)
if 'voc' in test_set:
for key in keys:
value = mAP.get(key)
print("%d\t%.4f" % (key, value))
iter = 000000
if single_scale is True:
single_scale_test_net(net,
imdb,
targe_size=input_size,
vis=visualizeDets,
redoInference=redoInference)
else:
if input_size == 320:
multi_scale_test_net_320(net,
imdb,
vis=visualizeDets,
redoInference=redoInference)
else:
multi_scale_test_net_512(net,
imdb,
vis=visualizeDets,
redoInference=redoInference)
mAP[iter] = cfg.mAP
mPrec[iter] = cfg.prec
mRec[iter] = cfg.rec
# Also available for further evaluation (From MATLAB, not used yet):
miss[iter] = cfg.miss
#roc[iter] = cfg.roc
#gt[iter] = cfg.gt
#dt[iter] = cfg.dt
# Just to check data structure:
#print("Miss : " + str( miss.get(miss.keys()[0]) ))
#print("ROCs : " + str( roc.get(roc.keys()[0]) ))
#print("GTs : " + str( gt.get(gt.keys()[0]) ))
#print("DTs : " + str( dt.get(dt.keys()[0]) ))