本文整理匯總了Python中detectron.utils.boxes.aspect_ratio方法的典型用法代碼示例。如果您正苦於以下問題：Python boxes.aspect_ratio方法的具體用法？Python boxes.aspect_ratio怎麽用？Python boxes.aspect_ratio使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類detectron.utils.boxes的用法示例。
在下文中一共展示了boxes.aspect_ratio方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: im_detect_mask_aspect_ratio
# 需要導入模塊: from detectron.utils import boxes [as 別名]
# 或者: from detectron.utils.boxes import aspect_ratio [as 別名]
def im_detect_mask_aspect_ratio(model, im, aspect_ratio, boxes, hflip=False):
"""Computes mask detections at the given width-relative aspect ratio."""
# Perform mask detection on the transformed image
im_ar = image_utils.aspect_ratio_rel(im, aspect_ratio)
boxes_ar = box_utils.aspect_ratio(boxes, aspect_ratio)
if hflip:
masks_ar = im_detect_mask_hflip(
model, im_ar, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE, boxes_ar
)
else:
im_scale = im_conv_body_only(
model, im_ar, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE
)
masks_ar = im_detect_mask(model, im_scale, boxes_ar)
return masks_ar 示例2: im_detect_keypoints_aspect_ratio
# 需要導入模塊: from detectron.utils import boxes [as 別名]
# 或者: from detectron.utils.boxes import aspect_ratio [as 別名]
def im_detect_keypoints_aspect_ratio(
model, im, aspect_ratio, boxes, hflip=False
):
"""Detects keypoints at the given width-relative aspect ratio."""
# Perform keypoint detectionon the transformed image
im_ar = image_utils.aspect_ratio_rel(im, aspect_ratio)
boxes_ar = box_utils.aspect_ratio(boxes, aspect_ratio)
if hflip:
heatmaps_ar = im_detect_keypoints_hflip(
model, im_ar, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE, boxes_ar
)
else:
im_scale = im_conv_body_only(
model, im_ar, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE
)
heatmaps_ar = im_detect_keypoints(model, im_scale, boxes_ar)
return heatmaps_ar 示例3: im_detect_bbox_aspect_ratio
# 需要導入模塊: from detectron.utils import boxes [as 別名]
# 或者: from detectron.utils.boxes import aspect_ratio [as 別名]
def im_detect_bbox_aspect_ratio(
model, im, aspect_ratio, box_proposals=None, hflip=False
):
"""Computes bbox detections at the given width-relative aspect ratio.
Returns predictions in the original image space.
"""
# Compute predictions on the transformed image
im_ar = image_utils.aspect_ratio_rel(im, aspect_ratio)
if not cfg.MODEL.FASTER_RCNN:
box_proposals_ar = box_utils.aspect_ratio(box_proposals, aspect_ratio)
else:
box_proposals_ar = None
if hflip:
scores_ar, boxes_ar, _ = im_detect_bbox_hflip(
model,
im_ar,
cfg.TEST.SCALE,
cfg.TEST.MAX_SIZE,
box_proposals=box_proposals_ar
)
else:
scores_ar, boxes_ar, _ = im_detect_bbox(
model,
im_ar,
cfg.TEST.SCALE,
cfg.TEST.MAX_SIZE,
boxes=box_proposals_ar
)
# Invert the detected boxes
boxes_inv = box_utils.aspect_ratio(boxes_ar, 1.0 / aspect_ratio)
return scores_ar, boxes_inv