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Hi,
Thanks for your repo with multi-class sort. Currently, sort outputs the following parameters:
"frame_num, bbox_x1, bbox_y1, bbox_x2, bbox_y2, category, u_overdot, v_overdot, s_overdot, and identity".
How can I add confidence score value for the tracked objects? The output required is:
"frame_num, bbox_x1, bbox_y1, bbox_x2, bbox_y2, category, u_overdot, v_overdot, s_overdot, identity, and confidence_score".
Your help would be highly appreciated.
Thanks,
The text was updated successfully, but these errors were encountered:
In the same class, under get_state(), add the confidence to the returned tensor with: arr_conf = np.expand_dims(np.array([self.conf]), 0). Put arr_conf in the final np.concatenate function, wherever you'd like.
Hi,
Thanks for your repo with multi-class sort. Currently, sort outputs the following parameters:
"frame_num, bbox_x1, bbox_y1, bbox_x2, bbox_y2, category, u_overdot, v_overdot, s_overdot, and identity".
How can I add confidence score value for the tracked objects? The output required is:
"frame_num, bbox_x1, bbox_y1, bbox_x2, bbox_y2, category, u_overdot, v_overdot, s_overdot, identity, and confidence_score".
Your help would be highly appreciated.
Thanks,
The text was updated successfully, but these errors were encountered: