636c1cff7a91c0b54c996ef48b36274b08e4a8b8,models.py,YOLOLayer,forward,#YOLOLayer#Any#Any#Any#,110

Before Change

            xy = torch.sigmoid(p[..., 0:2]) + grid_xy  // x, y
            wh = torch.exp(p[..., 2:4]) * anchor_wh  // width, height
            p_conf = torch.sigmoid(p[..., 4:5])  // Conf
            p_cls = p[..., 5:5 + self.nc]
            // Broadcasting only supported on first dimension in CoreML. See onnx-coreml/_operators.py
            // p_cls = F.softmax(p_cls, 2) * p_conf  // SSD-like conf
            p_cls = torch.exp(p_cls).permute((2, 1, 0))

After Change

            xy = torch.sigmoid(p[..., 0:2]) + grid_xy[0]  // x, y
            wh = torch.exp(p[..., 2:4]) * anchor_wh[0]  // width, height
            p_conf = torch.sigmoid(p[:, 4:5])  // Conf
            p_cls = F.softmax(p[:, 5:85], 1) * p_conf  // SSD-like conf
            return torch.cat((xy / ngu[0], wh, p_conf, p_cls), 1).t()

            // p = p.view(1, -1, 5 + self.nc)
            // xy = torch.sigmoid(p[..., 0:2]) + grid_xy  // x, y

Instances