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ultralytics 8.0.221 fix Apple MPS inference bug (#6694)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Johnny <johnnync13@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2023-11-30 13:46:17 +01:00 • committed by GitHub
parent e504520448
commit 2e71f7f50e
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4 changed files with 22 additions and 25 deletions
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40
ultralytics/utils/ops.py
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@ -109,8 +109,7 @@ def scale_boxes(img1_shape, boxes, img0_shape, ratio_pad=None, padding=True):
boxes[..., [0, 2]] -= pad[0] # x padding
boxes[..., [1, 3]] -= pad[1] # y padding
boxes[..., :4] /= gain
clip_boxes(boxes, img0_shape)
return boxes
return clip_boxes(boxes, img0_shape)
def make_divisible(x, divisor):
@ -179,10 +178,6 @@ def non_max_suppression(
if isinstance(prediction, (list, tuple)): # YOLOv8 model in validation model, output = (inference_out, loss_out)
prediction = prediction[0] # select only inference output
device = prediction.device
mps = 'mps' in device.type # Apple MPS
if mps: # MPS not fully supported yet, convert tensors to CPU before NMS
prediction = prediction.cpu()
bs = prediction.shape[0] # batch size
nc = nc or (prediction.shape[1] - 4) # number of classes
nm = prediction.shape[1] - nc - 4
@ -256,8 +251,6 @@ def non_max_suppression(
# i = i[iou.sum(1) > 1] # require redundancy
output[xi] = x[i]
if mps:
output[xi] = output[xi].to(device)
if (time.time() - t) > time_limit:
LOGGER.warning(f'WARNING ⚠️ NMS time limit {time_limit:.3f}s exceeded')
break # time limit exceeded
@ -270,17 +263,21 @@ def clip_boxes(boxes, shape):
Takes a list of bounding boxes and a shape (height, width) and clips the bounding boxes to the shape.
Args:
boxes (torch.Tensor): the bounding boxes to clip
shape (tuple): the shape of the image
boxes (torch.Tensor): the bounding boxes to clip
shape (tuple): the shape of the image
Returns:
(torch.Tensor | numpy.ndarray): Clipped boxes
"""
if isinstance(boxes, torch.Tensor): # faster individually
boxes[..., 0].clamp_(0, shape[1]) # x1
boxes[..., 1].clamp_(0, shape[0]) # y1
boxes[..., 2].clamp_(0, shape[1]) # x2
boxes[..., 3].clamp_(0, shape[0]) # y2
if isinstance(boxes, torch.Tensor): # faster individually (WARNING: inplace .clamp_() Apple MPS bug)
boxes[..., 0] = boxes[..., 0].clamp(0, shape[1]) # x1
boxes[..., 1] = boxes[..., 1].clamp(0, shape[0]) # y1
boxes[..., 2] = boxes[..., 2].clamp(0, shape[1]) # x2
boxes[..., 3] = boxes[..., 3].clamp(0, shape[0]) # y2
else: # np.array (faster grouped)
boxes[..., [0, 2]] = boxes[..., [0, 2]].clip(0, shape[1]) # x1, x2
boxes[..., [1, 3]] = boxes[..., [1, 3]].clip(0, shape[0]) # y1, y2
return boxes
def clip_coords(coords, shape):
@ -292,14 +289,15 @@ def clip_coords(coords, shape):
shape (tuple): A tuple of integers representing the size of the image in the format (height, width).
Returns:
(None): The function modifies the input `coordinates` in place, by clipping each coordinate to the image boundaries.
(torch.Tensor | numpy.ndarray): Clipped coordinates
"""
if isinstance(coords, torch.Tensor): # faster individually
coords[..., 0].clamp_(0, shape[1]) # x
coords[..., 1].clamp_(0, shape[0]) # y
if isinstance(coords, torch.Tensor): # faster individually (WARNING: inplace .clamp_() Apple MPS bug)
coords[..., 0] = coords[..., 0].clamp(0, shape[1]) # x
coords[..., 1] = coords[..., 1].clamp(0, shape[0]) # y
else: # np.array (faster grouped)
coords[..., 0] = coords[..., 0].clip(0, shape[1]) # x
coords[..., 1] = coords[..., 1].clip(0, shape[0]) # y
return coords
def scale_image(masks, im0_shape, ratio_pad=None):
@ -418,7 +416,7 @@ def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
y (np.ndarray | torch.Tensor): The bounding box coordinates in (x, y, width, height, normalized) format
"""
if clip:
clip_boxes(x, (h - eps, w - eps)) # warning: inplace clip
x = clip_boxes(x, (h - eps, w - eps))
assert x.shape[-1] == 4, f'input shape last dimension expected 4 but input shape is {x.shape}'
y = torch.empty_like(x) if isinstance(x, torch.Tensor) else np.empty_like(x) # faster than clone/copy
y[..., 0] = ((x[..., 0] + x[..., 2]) / 2) / w # x center
@ -740,7 +738,7 @@ def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None, normalize=False
coords[..., 1] -= pad[1] # y padding
coords[..., 0] /= gain
coords[..., 1] /= gain
clip_coords(coords, img0_shape)
coords = clip_coords(coords, img0_shape)
if normalize:
coords[..., 0] /= img0_shape[1] # width
coords[..., 1] /= img0_shape[0] # height