资源算法TFFRCN_resnet50

TFFRCN_resnet50

2020-02-21 | |  44 |   0 |   0

TFFRCN_Resnet50

This is the faster rcnn based on Tensorflow and resnet50

  • fork from the TFFRCN website is https://github.com/CharlesShang/TFFRCNN

  • just change the python file factory.py , __ init __.py ,networks.py in /lib/networks

  • add resnet50 networks

  • resnet101 hasn't been tested

You can find how to use it from the above website

the model file is convert from the caffemodel, you can download from the baiduyun
link: http://pan.baidu.com/s/1eSuUO1s pwd: 24cf
the fine-tune model link: http://pan.baidu.com/s/1nuUYfMh pwd:5bve
resnet101 imagenet file link http://pan.baidu.com/s/1i5odxNv pwd:d8y4

USing voc07_trainval to train the Resnet50 and test on the voc07_test
The result is : Mean AP = 0.7124

AP for aeroplane = 0.7801
AP for bicycle = 0.7931
AP for bird = 0.6836
AP for boat = 0.5750
AP for bottle = 0.4892
AP for bus = 0.8322
AP for car = 0.8412
AP for cat = 0.8380
AP for chair = 0.5186
AP for cow = 0.7550
AP for diningtable = 0.6369
AP for dog = 0.7861
AP for horse = 0.7966
AP for motorbike = 0.7692
AP for person = 0.7765
AP for pottedplant = 0.4454
AP for sheep = 0.7131
AP for sofa = 0.7074
AP for train = 0.8150
AP for tvmonitor = 0.6953






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