Example #1
0
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 #2
0
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 #3
0
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 #4
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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 #5
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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
0
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_ar, im_scale_ar = im_conv_body_only(model, im, target_scale,
                                                      target_max_size)
        # _, im_scale, _ = blob_utils.get_image_blob(im, target_scale, target_max_size)
        masks_ar = im_detect_mask(model, im_scale_ar, boxes_ar, blob_conv_ar)
    return masks_ar
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 = blob_utils.pack_sequence([
        image_utils.aspect_ratio_rel(x, aspect_ratio)
        for x in blob_utils.unpack_sequence(im)
    ])
    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
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 = blob_utils.pack_sequence([
        image_utils.aspect_ratio_rel(x, aspect_ratio)
        for x in blob_utils.unpack_sequence(im)
    ])
    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