Python utils.image.aspect_ratio_rel() Examples

The following are 30 code examples of utils.image.aspect_ratio_rel(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module utils.image , or try the search function .
Example #1
Source File: test.py    From PANet with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #2
Source File: test.py    From detectron-self-train with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #3
Source File: test.py    From detectron-self-train with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #4
Source File: test.py    From Large-Scale-VRD.pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #5
Source File: test.py    From masktextspotter.caffe2 with Apache License 2.0 6 votes vote down vote up 
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, boxes_ar)
    else:
        im_scales = im_conv_body_only(model, im_ar)
        heatmaps_ar = im_detect_keypoints(model, im_scales, boxes_ar)

    return heatmaps_ar
Example #6
Source File: test.py    From DIoU-pytorch-detectron with GNU General Public License v3.0 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #7
Source File: test.py    From masktextspotter.caffe2 with Apache License 2.0 6 votes vote down vote up 
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, box_proposals_ar
        )
    else:
        scores_ar, boxes_ar, _ = im_detect_bbox(model, im_ar, box_proposals_ar)

    # Invert the detected boxes
    boxes_inv = box_utils.aspect_ratio(boxes_ar, 1.0 / aspect_ratio)

    return scores_ar, boxes_inv
Example #8
Source File: test.py    From PMFNet with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #9
Source File: test.py    From PMFNet with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #10
Source File: test.py    From DIoU-pytorch-detectron with GNU General Public License v3.0 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #11
Source File: test.py    From seg_every_thing with Apache License 2.0 6 votes vote down vote up 
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
Example #12
Source File: test.py    From seg_every_thing with Apache License 2.0 6 votes vote down vote up 
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
Example #13
Source File: test.py    From NucleiDetectron with Apache License 2.0 6 votes vote down vote up 
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, box_proposals_ar
        )
    else:
        scores_ar, boxes_ar, _ = im_detect_bbox(model, im_ar, box_proposals_ar)

    # Invert the detected boxes
    boxes_inv = box_utils.aspect_ratio(boxes_ar, 1.0 / aspect_ratio)

    return scores_ar, boxes_inv
Example #14
Source File: test.py    From PANet with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #15
Source File: test.py    From Context-aware-ZSR with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #16
Source File: test.py    From Context-aware-ZSR with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #17
Source File: test.py    From NucleiDetectron with Apache License 2.0 6 votes vote down vote up 
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, boxes_ar)
    else:
        im_scales = im_conv_body_only(model, im_ar)
        heatmaps_ar = im_detect_keypoints(model, im_scales, boxes_ar)

    return heatmaps_ar
Example #18
Source File: test.py    From Detectron.pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #19
Source File: test.py    From Detectron.pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #20
Source File: test.py    From DetectAndTrack with Apache License 2.0 6 votes vote down vote up 
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(el, aspect_ratio) for el in im]

    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, box_proposals_ar)
    else:
        scores_ar, boxes_ar, _ = im_detect_bbox(
            model, im_ar, box_proposals_ar)

    # Invert the detected boxes
    boxes_inv = box_utils.aspect_ratio(boxes_ar, 1.0 / aspect_ratio)

    return scores_ar, boxes_inv
Example #21
Source File: test.py    From FPN-Pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #22
Source File: test.py    From FPN-Pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #23
Source File: test.py    From Detectron.pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return heatmaps_ar
Example #24
Source File: test.py    From Detectron.pytorch with MIT License 6 votes vote down vote up 
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:
        blob_conv, 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, blob_conv)

    return masks_ar
Example #25
Source File: test.py    From DetectAndTrack with Apache License 2.0 5 votes vote down vote up 
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, boxes_ar)
    else:
        im_scales = im_conv_body_only(model, im_ar)
        heatmaps_ar = im_detect_keypoints(model, im_scales, boxes_ar)

    return heatmaps_ar
Example #26
Source File: test.py    From NucleiDetectron with Apache License 2.0 5 votes vote down vote up 
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, boxes_ar)
    else:
        im_scales = im_conv_body_only(model, im_ar)
        masks_ar = im_detect_mask(model, im_scales, boxes_ar)

    return masks_ar
Example #27
Source File: test.py    From DetectAndTrack with Apache License 2.0 5 votes vote down vote up 
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, boxes_ar)
    else:
        im_scales = im_conv_body_only(model, im_ar)
        masks_ar = im_detect_mask(model, im_scales, boxes_ar)

    return masks_ar
Example #28
Source File: test.py    From DIoU-pytorch-detectron with GNU General Public License v3.0 5 votes vote down vote up 
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
Example #29
Source File: test.py    From Detectron.pytorch with MIT License 5 votes vote down vote up 
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
Example #30
Source File: test.py    From detectron-self-train with MIT License 5 votes vote down vote up 
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