[object Object][object Object][object Object]undefined[object Object]

• Description: A loss function used for bounding box regression. Based on the IoU, the center point distance, aspect ratio, and overlapping area are considered to comprehensively measure the difference between the predicted box and the real box.
• Formulas:

$$CIoU = IoU - \frac{\rho^2(b^p, b^g)}{c^2} - \alpha v \\ v = \frac{4}{\pi^2}(arctan(\frac{w^g}{h^g}) - arctan(\frac{w^p}{h^p}))^2 \\ \alpha = \frac{v}{1 - IoU + v} \\$$ [object Object]

Each operator has calls. First, [object Object] is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, [object Object] is called to perform computation.

[object Object]

• Parameters

  [object Object]

• Returns:

  [object Object]: status code. For details, see .

  The first-phase API implements input parameter validation. The following error codes may be returned.

  [object Object]

[object Object]

• Parameters

  [object Object]

• Returns:

  [object Object]: status code. For details, see .

[object Object]

• Deterministic computation:
  • The aclnnCIoU is implemented in deterministic mode by default.
• If the input format is [x0, y0, x1, y1], (x0, y0) and (x1, y1) indicate the upper left corner and lower right corner of the bounding box, respectively. The following condition must be met: x1 > x0, y1 > y0
• M and N must be the same.
• Currently, isCross can only be set to false.

[object Object]

The following example is for reference only. For details, see .