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SEMS-model
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main
Author | SHA1 | Date | |
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c821a77d75 |
15
main.py
15
main.py
@ -26,7 +26,10 @@ def register():
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data=msgpack.unpackb(gzip.decompress(request.data) )
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data=msgpack.unpackb(gzip.decompress(request.data) )
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# print(len(data["c"]),data["c"])
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# print(len(data["c"]),data["c"])
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data=np.frombuffer(data["spectral_data_bin"],dtype=np.uint16).reshape(1,1,224,512)
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data=np.frombuffer(data["spectral_data_bin"],dtype=np.uint16).reshape(int(len(data["spectral_data_bin"])/224/512/2),1,224,512)
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data=np.mean(data,axis=0, keepdims=True)
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# print(data.shape)
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# print(data.shape)
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# input_data=torch.tensor(data,dtype=torch.float32)/4095
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# input_data=torch.tensor(data,dtype=torch.float32)/4095
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@ -38,8 +41,14 @@ def register():
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print(output)
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print(output)
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response={}
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response={}
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response["temp"]= float(output[0,0]*(1692-1516)+1516)
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response["Temperature"]= float(output[0,0]*(1663-1496)+1496)
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response["C"]= float(output[0,1]*(0.915-0.062)+0.062)
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response["C"]= float(output[0,1]*(0.829-0.079)+0.079)
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response["P"]=float(output[0,1]*(0.797-0.001)+0.001)
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response["S"]=0.04402615384615385
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response["Mn"]=0.138787
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response["Ni"]=0.035104
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response["Mo"]=0.093789
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response["Cr"]=0.002983
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d=gzip.compress(msgpack.packb(response))
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d=gzip.compress(msgpack.packb(response))
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print(d)
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print(d)
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