Nms

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1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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6. final def eq(arg0: AnyRef): Boolean

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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10. def hashCode(): Int

    

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11. final def isInstanceOf[T0]: Boolean

    

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12. def isKeepCurIndex(boxArray: Array[Float], offset: Int, rowLength: Int, areas: Array[Float], curInd: Int, adaptiveThresh: Float, indices: Array[Int], indexLength: Int, normalized: Boolean): Boolean

    

13. final def ne(arg0: AnyRef): Boolean

    

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14. def nms(scores: Tensor[Float], boxes: Tensor[Float], thresh: Float, indices: Array[Int], sorted: Boolean = false, orderWithBBox: Boolean = false): Int

    

    1.

    1. first sort the scores from highest to lowest and get indices 2. for the bbox of first index, get the overlap between this box and the remaining bboxes put the first index to result buffer 3. update the indices by keeping those bboxes with overlap less than thresh 4. repeat 2 and 3 until the indices are empty

    scores

    score tensor

    boxes

    box tensor, with the size N*4

    thresh

    overlap thresh

    indices

    buffer to store indices after nms

    sorted

    whether the scores are sorted

    orderWithBBox

    whether return indices in the order with original bbox index

    returns

    the length of indices after nms

15. def nmsFast(scores: Tensor[Float], boxes: Tensor[Float], nmsThresh: Float, scoreThresh: Float, indices: Array[Int], topk: Int = 1, eta: Float = 1, normalized: Boolean = true): Int

    

16. final def notify(): Unit

    

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20. final def wait(): Unit

    

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21. final def wait(arg0: Long, arg1: Int): Unit

    

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22. final def wait(arg0: Long): Unit

    

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