def im_detect(net, im, boxes):
    blobs, unused_im_scale_factors = _get_blobs(im, boxes)

    # When mapping from image ROIs to feature map ROIs, there's some aliasing
    # (some distinct image ROIs get mapped to the same feature ROI).
    # Here, we identify duplicate feature ROIs, so we only compute features
    # on the unique subset.
    if cfg.DEDUP_BOXES > 0:
        v = np.array([1, 1e3, 1e6, 1e9, 1e12])
        hashes = np.round(blobs['rois'] * cfg.DEDUP_BOXES).dot(v)
        _, index, inv_index = np.unique(hashes, return_index=True,
                                        return_inverse=True)
        blobs['rois'] = blobs['rois'][index, :]
        boxes = boxes[index, :]

    # reshape network inputs
    net.blobs['data'].reshape(*(blobs['data'].shape))
    net.blobs['rois'].reshape(*(blobs['rois'].shape))
    blobs_out = net.forward(data=blobs['data'].astype(np.float32, copy=False),
                            rois=blobs['rois'].astype(np.float32, copy=False))
    if cfg.TEST.SVM:
        # use the raw scores before softmax under the assumption they
        # were trained as linear SVMs
        scores = net.blobs['cls_score'].data
    else:
        # use softmax estimated probabilities
        scores = blobs_out['cls_prob']

    if cfg.TEST.BBOX_REG:
        # Apply bounding-box regression deltas
        box_deltas = blobs_out['bbox_pred']
        pred_boxes = _bbox_pred(boxes, box_deltas)
        pred_boxes = _clip_boxes(pred_boxes, im.shape)
    else:
        # Simply repeat the boxes, once for each class
        pred_boxes = np.tile(boxes, (1, scores.shape[1]))

    if cfg.DEDUP_BOXES > 0:
        # Map scores and predictions back to the original set of boxes
        scores = scores[inv_index, :]
        pred_boxes = pred_boxes[inv_index, :]

    return scores, pred_boxes
list any shading groups in the future of this object - works for
dataset/ETHPy150Open rbgirshick/fast-rcnn/lib/fast_rcnn/test.py/im_detect--crossover with--dataset/ETHPy150Open CountZer0/PipelineConstructionSet/python/maya/site-packages/pymel-1.0.3/pymel/core/nodetypes.py/DependNode.shadingGroups