人工智能训练代码
for i_test, data_test in enumerate(test_salobj_dataloader):
print("inferencing:",img_name_list[i_test].split(os.sep)[-1])
inputs_test = data_test['image']
inputs_test = inputs_test.type(torch.FloatTensor)
if torch.cuda.is_available():
inputs_test = Variable(inputs_test.cuda())
else:
inputs_test = Variable(inputs_test)
d1,d2,d3,d4,d5,d6,d7= net(inputs_test)
pred = 1.0 - d1[:,0,:,:]
pred = normPRED(pred)
save_output(img_name_list[i_test],pred,prediction_dir)
del d1,d2,d3,d4,d5,d6,d7
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