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Update depth.py 

fixing not able to use fp32
pull/111/head
Funofabot 2022-11-24 05:56:08 -07:00 committed by GitHub
parent 44070d0fb7
commit 0491256d16
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1 changed files with 6 additions and 3 deletions
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scripts/deforum_helpers/depth.py
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@ -57,9 +57,11 @@ class DepthModel():
if half_precision and self.device == torch.device("cuda"): if half_precision and self.device == torch.device("cuda"):
self.midas_model = self.midas_model.to(memory_format=torch.channels_last) self.midas_model = self.midas_model.to(memory_format=torch.channels_last)
self.midas_model = self.midas_model.half() self.midas_model = self.midas_model.half()
self.midas_model.to(self.device) self.midas_model.to(self.device)
else:
self.midas_model.to(self.device)
def predict(self, prev_img_cv2, anim_args) -> torch.Tensor: def predict(self, prev_img_cv2, anim_args, half_precision) -> torch.Tensor:
w, h = prev_img_cv2.shape[1], prev_img_cv2.shape[0] w, h = prev_img_cv2.shape[1], prev_img_cv2.shape[0]
# predict depth with AdaBins # predict depth with AdaBins
@ -109,7 +111,8 @@ class DepthModel():
sample = torch.from_numpy(img_midas_input).float().to(self.device).unsqueeze(0) sample = torch.from_numpy(img_midas_input).float().to(self.device).unsqueeze(0)
if self.device == torch.device("cuda"): if self.device == torch.device("cuda"):
sample = sample.to(memory_format=torch.channels_last) sample = sample.to(memory_format=torch.channels_last)
sample = sample.half() if half_precision:
sample = sample.half()
with torch.no_grad(): with torch.no_grad():
midas_depth = self.midas_model.forward(sample) midas_depth = self.midas_model.forward(sample)
midas_depth = torch.nn.functional.interpolate( midas_depth = torch.nn.functional.interpolate(