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https://github.com/iperov/DeepFaceLab.git
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added AMD/Intel cards support via DirectX12 ( DirectML backend )
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parent
fc4a49c3e7
commit
fdb143ff47
7 changed files with 166 additions and 116 deletions
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@ -161,11 +161,11 @@ class FaceEnhancer(object):
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if not model_path.exists():
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raise Exception("Unable to load FaceEnhancer.npy")
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with tf.device ('/CPU:0' if place_model_on_cpu else '/GPU:0'):
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with tf.device ('/CPU:0' if place_model_on_cpu else nn.tf_default_device_name):
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self.model = FaceEnhancer()
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self.model.load_weights (model_path)
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with tf.device ('/CPU:0' if run_on_cpu else '/GPU:0'):
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with tf.device ('/CPU:0' if run_on_cpu else nn.tf_default_device_name):
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self.model.build_for_run ([ (tf.float32, nn.get4Dshape (192,192,3) ),
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(tf.float32, (None,1,) ),
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(tf.float32, (None,1,) ),
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@ -39,7 +39,7 @@ class XSegNet(object):
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self.target_t = tf.placeholder (nn.floatx, nn.get4Dshape(resolution,resolution,1) )
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# Initializing model classes
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with tf.device ('/CPU:0' if place_model_on_cpu else '/GPU:0'):
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with tf.device ('/CPU:0' if place_model_on_cpu else nn.tf_default_device_name):
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self.model = nn.XSeg(3, 32, 1, name=name)
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self.model_weights = self.model.get_weights()
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if training:
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@ -53,7 +53,7 @@ class XSegNet(object):
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self.model_filename_list += [ [self.model, f'{model_name}.npy'] ]
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if not training:
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with tf.device ('/CPU:0' if run_on_cpu else '/GPU:0'):
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with tf.device ('/CPU:0' if run_on_cpu else nn.tf_default_device_name):
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_, pred = self.model(self.input_t)
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def net_run(input_np):
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