本文整理汇总了Python中utils.boxes.flip_boxes方法的典型用法代码示例。如果您正苦于以下问题：Python boxes.flip_boxes方法的具体用法？Python boxes.flip_boxes怎么用？Python boxes.flip_boxes使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类utils.boxes的用法示例。
在下文中一共展示了boxes.flip_boxes方法的11个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: im_detect_bbox_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_bbox_hflip(
model, im, target_scale, target_max_size, box_proposals=None):
"""Performs bbox detection on the horizontally flipped image.
Function signature is the same as for im_detect_bbox.
"""
# Compute predictions on the flipped image
im_hf = im[:, ::-1, :]
im_width = im.shape[1]
if not cfg.MODEL.FASTER_RCNN:
box_proposals_hf = box_utils.flip_boxes(box_proposals, im_width)
else:
box_proposals_hf = None
scores_hf, boxes_hf, im_scale, _ = im_detect_bbox(
model, im_hf, target_scale, target_max_size, boxes=box_proposals_hf
)
# Invert the detections computed on the flipped image
boxes_inv = box_utils.flip_boxes(boxes_hf, im_width)
return scores_hf, boxes_inv, im_scale 示例2: im_detect_bbox_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_bbox_hflip(
model, im, target_scale, target_max_size, box_proposals=None):
"""Performs bbox detection on the horizontally flipped image.
Function signature is the same as for im_detect_bbox.
"""
# Compute predictions on the flipped image
im_hf = im[:, ::-1, :]
im_width = im.shape[1]
box_proposals_hf = box_utils.flip_boxes(box_proposals, im_width)
scores_hf, boxes_hf, im_scale, _ = im_detect_bbox(
model, im_hf, target_scale, target_max_size, boxes=box_proposals_hf
)
# Invert the detections computed on the flipped image
boxes_inv = box_utils.flip_boxes(boxes_hf, im_width)
return scores_hf, boxes_inv, im_scale 示例3: im_detect_bbox_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_bbox_hflip(
model, im, target_scale, target_max_size, box_proposals=None
):
"""Performs bbox detection on the horizontally flipped image.
Function signature is the same as for im_detect_bbox.
"""
# Compute predictions on the flipped image
im_hf = im[:, ::-1, :]
im_width = im.shape[1]
if not cfg.MODEL.FASTER_RCNN:
box_proposals_hf = box_utils.flip_boxes(box_proposals, im_width)
else:
box_proposals_hf = None
scores_hf, boxes_hf, im_scale = im_detect_bbox(
model, im_hf, target_scale, target_max_size, boxes=box_proposals_hf
)
# Invert the detections computed on the flipped image
boxes_inv = box_utils.flip_boxes(boxes_hf, im_width)
return scores_hf, boxes_inv, im_scale 示例4: im_detect_bbox_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_bbox_hflip(model, im, box_proposals=None):
"""Performs bbox detection on the horizontally flipped image.
Function signature is the same as for im_detect_bbox.
"""
# Compute predictions on the flipped image
im_hf = im[:, ::-1, :]
im_width = im.shape[1]
if not cfg.MODEL.FASTER_RCNN:
box_proposals_hf = box_utils.flip_boxes(box_proposals, im_width)
else:
box_proposals_hf = None
scores_hf, boxes_hf, im_scales = im_detect_bbox(
model, im_hf, box_proposals_hf
)
# Invert the detections computed on the flipped image
boxes_inv = box_utils.flip_boxes(boxes_hf, im_width)
return scores_hf, boxes_inv, im_scales 示例5: im_detect_mask_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_mask_hflip(model, im, boxes):
"""Performs mask detection on the horizontally flipped image.
Function signature is the same as for im_detect_mask_aug.
"""
# Compute the masks for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
im_scales = im_conv_body_only(model, im_hf)
global_masks_hf, char_masks_hf, char_boxes_hf = im_detect_mask(model, im_scales, boxes_hf)
# Invert the predicted soft masks
global_masks_inv = global_masks_hf[:, :, :, ::-1]
# char_masks_inv = char_masks_hf[:, :, :, ::-1]
# char_boxes_inv = char_boxes_hf[:, :, :, ::-1]
return global_masks_inv, char_masks_inv, None 示例6: im_detect_bbox_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_bbox_hflip(model, im, box_proposals=None):
"""Performs bbox detection on the horizontally flipped image.
Function signature is the same as for im_detect_bbox.
"""
# Compute predictions on the flipped image
# im is a list now, to be compat with video case
im_hf = [e[:, ::-1, :] for e in im]
# Since all frames would be same shape, just take values from 1st
im_width = im[0].shape[1]
if not cfg.MODEL.FASTER_RCNN:
box_proposals_hf = box_utils.flip_boxes(box_proposals, im_width)
else:
box_proposals_hf = None
scores_hf, boxes_hf, im_scales = im_detect_bbox(
model, im_hf, box_proposals_hf)
# Invert the detections computed on the flipped image
boxes_inv = box_utils.flip_boxes(boxes_hf, im_width)
return scores_hf, boxes_inv, im_scales 示例7: im_detect_mask_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_mask_hflip(model, im, target_scale, target_max_size, boxes):
"""Performs mask detection on the horizontally flipped image.
Function signature is the same as for im_detect_mask_aug.
"""
# Compute the masks for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
masks_hf = im_detect_mask(model, im_scale, boxes_hf, blob_conv)
# Invert the predicted soft masks
masks_inv = masks_hf[:, :, :, ::-1]
return masks_inv 示例8: im_detect_keypoints_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
"""Computes keypoint predictions on the horizontally flipped image.
Function signature is the same as for im_detect_keypoints_aug.
"""
# Compute keypoints for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
blob_conv, im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf, blob_conv)
# Invert the predicted keypoints
heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)
return heatmaps_inv 示例9: im_detect_mask_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_mask_hflip(model, im, target_scale, target_max_size, boxes):
"""Performs mask detection on the horizontally flipped image.
Function signature is the same as for im_detect_mask_aug.
"""
# Compute the masks for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
masks_hf = im_detect_mask(model, im_scale, boxes_hf)
# Invert the predicted soft masks
masks_inv = masks_hf[:, :, :, ::-1]
return masks_inv 示例10: im_detect_keypoints_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_keypoints_hflip(model, im, target_scale, target_max_size, boxes):
"""Computes keypoint predictions on the horizontally flipped image.
Function signature is the same as for im_detect_keypoints_aug.
"""
# Compute keypoints for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
im_scale = im_conv_body_only(model, im_hf, target_scale, target_max_size)
heatmaps_hf = im_detect_keypoints(model, im_scale, boxes_hf)
# Invert the predicted keypoints
heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)
return heatmaps_inv 示例11: im_detect_keypoints_hflip
# 需要导入模块: from utils import boxes [as 别名]
# 或者: from utils.boxes import flip_boxes [as 别名]
def im_detect_keypoints_hflip(model, im, boxes):
"""Computes keypoint predictions on the horizontally flipped image.
Function signature is the same as for im_detect_keypoints_aug.
"""
# Compute keypoints for the flipped image
im_hf = im[:, ::-1, :]
boxes_hf = box_utils.flip_boxes(boxes, im.shape[1])
im_scales = im_conv_body_only(model, im_hf)
heatmaps_hf = im_detect_keypoints(model, im_scales, boxes_hf)
# Invert the predicted keypoints
heatmaps_inv = keypoint_utils.flip_heatmaps(heatmaps_hf)
return heatmaps_inv