Open yghlc opened 7 years ago
Hello, There is no test net accuracy in the log file even I specified the test data layer in the train.prototxt file:
layers { name: "data" type: IMAGE_SEG_DATA top: "data" top: "label" image_data_param { root_folder: "" source: "./list/test_aug.txt" label_type: PIXEL batch_size: 100 } transform_param { mean_value: 75.209 mean_value: 85.950 mean_value: 95.685 crop_size: 663 mirror: false } include: { phase: TEST } }
Only loss and train net accuracy in the log file, such as:
I0424 09:32:20.303715 32660 solver.cpp:209] Iteration 50, loss = 0.270298 I0424 09:32:20.303766 32660 solver.cpp:224] Train net output #0: accuracy = 0.883158 I0424 09:32:20.303774 32660 solver.cpp:224] Train net output #1: accuracy = 0.780627 I0424 09:32:20.303809 32660 solver.cpp:224] Train net output #2: accuracy = 0.70205
How do I get the test accuracy during training? What the meaning of Train net output #0, Train net output "#1", Train net output "#2"? "#0", "#1", "#2" means something?
What the meaning of Train net output #0, Train net output "#1", Train net output "#2"? "#0", "#1", "#2" means something?
Thanks for any suggestion!
Hey. Did you figure out how to get the validation accuracy or loss? I also want to do that.
Hello, There is no test net accuracy in the log file even I specified the test data layer in the train.prototxt file:
Only loss and train net accuracy in the log file, such as:
How do I get the test accuracy during training?
What the meaning of Train net output #0, Train net output "#1", Train net output "#2"? "#0", "#1", "#2" means something?
Thanks for any suggestion!