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Speedup data transport

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hzwer
2020-12-03 11:05:35 +08:00
committed by GitHub
parent 3932b4af0c
commit 5362648819
1 changed files with 3 additions and 3 deletions
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6
Pkgs/rife-cuda/interp-basic.py
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@@ -78,8 +78,8 @@ with torch.no_grad():
frame0 = cv2.imread(frame_0_path)
frame1 = cv2.imread(frame_1_path)
img0 = (torch.tensor(frame0.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0)
img1 = (torch.tensor(frame1.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0)
img0 = (torch.tensor(frame0.transpose(2, 0, 1)).to(device, non_blocking=True) / 255.).unsqueeze(0)
img1 = (torch.tensor(frame1.transpose(2, 0, 1)).to(device, non_blocking=True) / 255.).unsqueeze(0)
n, c, h, w = img0.shape
ph = ((h - 1) // 32 + 1) * 32
pw = ((w - 1) // 32 + 1) * 32
@@ -101,7 +101,7 @@ with torch.no_grad():
for i in range(len(img_list)):
if i == 0:
continue
cv2.imwrite('{:s}/{:08d}.{}'.format(interp_output_path, output_frame_number, ext), img_list[i][0].cpu().numpy().transpose(1, 2, 0)[:h, :w] * 255)
cv2.imwrite('{:s}/{:08d}.{}'.format(interp_output_path, output_frame_number, ext), (img_list[i][0] * 255).byte().cpu().numpy().transpose(1, 2, 0)[:h, :w])
#print("Writing image from array")
#print("Out Frame Num: {0}".format(output_frame_number))
output_frame_number += 1