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clks-wzz / PRNet-Depth-Generation

A implementaion of depth generation based on [PRNet](https://github.com/YadiraF/PRNet), which was used in the paper ***Exploiting Temporal and Depth Information for Multi-frame Face Anti-spoofing***
MIT License
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The passed save_path is not a valid checkpoint: ./Data/net-data/256_256_resfcn256_weight #3

Open leelongch opened 4 years ago

leelongch commented 4 years ago

The passed save_path is not a valid checkpoint: ./Data/net-data/256_256_resfcn256_weight

harrismohammed commented 4 years ago

Check the original PRnet Implementation and download the missing file in Data/net-data/....

xiao-keeplearning commented 4 years ago

add 256_256_resfcn256_weight.index file

sonfire186 commented 4 years ago

where to get 256_256_resfcn256_weight. index file ?

xiao-keeplearning commented 4 years ago

where to get 256_256_resfcn256_weight. index file ?

https://github.com/YadiraF/PRNet/blob/master/Data/net-data/256_256_resfcn256_weight.index

sonfire186 commented 4 years ago

I don't think these are exactly the same weights, since there shouldn't be a depth map for fake images

xiao-keeplearning commented 4 years ago

The depth map for fake images is set to 0, you can found the detail in related papers. This code for generating the facial depth map for training.

sonfire186 commented 4 years ago

I’m talking about this. He will issue the same card for the original and fake image. It should immediately generate 0 to fake. The article had a link to this repository.

punitha-valli commented 3 years ago

@leelongch @sonfire86 @xiao-keeplearning @harrismohammed @clks-wzz your code, it will be a great help Thanks for sharing Even the Dlib= False, and Open_cv= False, at here

def init(self, is_dlib = False, is_opencv = False, prefix = 'E:\yzu\lab\face anti spoofing\PRNet-Depth-Generation-master'):

It should pass into here

self.pos_predictor = PosPrediction(self.resolution_inp, self.resolution_op) prn_path = os.path.join(prefix,'Data\net-data\256_256_resfcn256_weight') if not os.path.isfile(prn_path +'.data-00000-of-00001'): print("please download PRN trained model first.") exit() self.pos_predictor.restore(prn_path)

for further process,

but in my case, its still gives the error like this,

AttributeError: 'PRN' object has no attribute 'face_detector'

How to carry out this, thanks in advance