update retinafaceAntiCov
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@ -27,7 +27,7 @@ sudo ./retinafaceAntiCov -s // build and serialize model to file i.e. 'retinafa
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wget http://www.kaixian.tv/gd/d/file/201611/07/23efff3a26e2385620e719378c654fb1.jpg -O test.jpg
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sudo ./retinafaceAntiCov -d // deserialize model file and run inference.
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3. check the images generated, as follows. out.jpg
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3. check the image generated, as follows 'out.jpg'
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```
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<p align="center">
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23
retinafaceAntiCov/gen_wts.py
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23
retinafaceAntiCov/gen_wts.py
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@ -0,0 +1,23 @@
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import struct
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from retinaface_cov import RetinaFaceCoV
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gpuid = 0
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model = RetinaFaceCoV('./cov2/mnet_cov2', 0, gpuid, 'net3l')
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f = open('retinafaceAntiCov.wts', 'w')
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f.write('{}\n'.format(len(model.model.get_params()[0].keys()) + len(model.model.get_params()[1].keys())))
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for k, v in model.model.get_params()[0].items():
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vr = v.reshape(-1).asnumpy()
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f.write('{} {} '.format(k, len(vr)))
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for vv in vr:
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f.write(' ')
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f.write(struct.pack('>f',float(vv)).hex())
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f.write('\n')
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for k, v in model.model.get_params()[1].items():
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vr = v.reshape(-1).asnumpy()
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f.write('{} {} '.format(k, len(vr)))
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for vv in vr:
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f.write(' ')
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f.write(struct.pack('>f',float(vv)).hex())
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f.write('\n')
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@ -29,8 +29,8 @@
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using namespace nvinfer1;
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// stuff we know about the network and the input/output blobs
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static const int INPUT_H = 640;
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static const int INPUT_W = 640;
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static const int INPUT_H = decodeplugin::INPUT_H;
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static const int INPUT_W = decodeplugin::INPUT_W;
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static const int DETECTION_SIZE = sizeof(decodeplugin::Detection) / sizeof(float);
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static const int OUTPUT_SIZE = (INPUT_H / 8 * INPUT_W / 8 + INPUT_H / 16 * INPUT_W / 16 + INPUT_H / 32 * INPUT_W / 32) * 2 * DETECTION_SIZE + 1;
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const char* INPUT_BLOB_NAME = "data";
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