About finetune my own data about pva-faster-rcnn HOT 10 OPEN

@sanghoon
I finetune the pvanet/full/test.model using the train.prototxt in pvanet/example_fineturn on KITTI while the result is not good and even worse than the pvanet/full/test.model. Should I use imagenet/full/test.model as pre-train model if I want to train on a dataset with different classes with VOC?
Can you give me some advice? Thank you very much.
There are related files：
log.txt
solver_plateau.txt
train.txt

The ap @IOU0.7:
AP for Car = 0.7321
AP for Van = 0.6796
AP for Truck = 0.8270
AP for Pedestrian = 0.4119
AP for Person_sitting = 0.3100
AP for Tram = 0.6638
AP for Cyclist = 0.4930
Mean AP = 0.5882

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@catsdogone HI,I wonder how you draw the pictures

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@AITTSMD Using the parse.py in caffe-fast-rcnn/tools/extra to parse the log file than plot it.

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@catsdogone oh! Thank u,I''ll have a try.By the way,when you have limited data,you can use example_384 to finetune.The result will be better,but the speed will be slower!

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@AITTSMD Thank you. I will have a try.

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@AITTSMD HI, I wonder which model do you use for the initial weights while you use example_384 to fineturne, models/pvanet/full/test.model ?

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@catsdogone imagenet/train.model

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@catsdogone Could you please share the details that how you generate the log file and how to figure the plots of loss-iters?

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Hi all,
Sorry for a late comment.
I'm attending a conference right now, I'll check the issue when I get back to my home

One more thing,
We've trained a better model with a similar structure.
It'll be shared soon (maybe in a couple of weeks)

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@beihangzxm123 I use the format of script file as py-faster-rcnn/scripts/*.sh. The parse_log.py is from caffe-fast-rcnn/toos/extra. The attachment is the files you may need.
kitti_pva.txt--kitti_pva.sh
parse_log.txt--parse_log.py
plot_loss.txt--plot_loss.py

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