* TTA augument boxes one pixel shifted in de-flip ud and lr * PEP8 reformat Co-authored-by: Jaap van de Loosdrecht <jaap.van.de.loosdrecht@nhlstenden.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>5.0
@@ -110,9 +110,9 @@ class Model(nn.Module): | |||
# cv2.imwrite(f'img_{si}.jpg', 255 * xi[0].cpu().numpy().transpose((1, 2, 0))[:, :, ::-1]) # save | |||
yi[..., :4] /= si # de-scale | |||
if fi == 2: | |||
yi[..., 1] = img_size[0] - yi[..., 1] # de-flip ud | |||
yi[..., 1] = img_size[0] - 1 - yi[..., 1] # de-flip ud | |||
elif fi == 3: | |||
yi[..., 0] = img_size[1] - yi[..., 0] # de-flip lr | |||
yi[..., 0] = img_size[1] - 1 - yi[..., 0] # de-flip lr | |||
y.append(yi) | |||
return torch.cat(y, 1), None # augmented inference, train | |||
else: |