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why still need to use conf_mask but not y_true[...,4] #454
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why need to make a distinction between coord_mask, conf_mask, and class_mask , use the y_true[..., 4] directly is work well ,right? hope to receive you reply, thanks in advance |
the code :
is total equals to : |
no, it's not right to use y_true[..., 0] directly, if we do that it more like to random choice some cell to compute the conf_loss, not relative to the y_pred, so it's wrong |
because tf.exp(pred[..., 2:4]) is always NAN in training |
I have the same quesion, please tell me that if you solve the problem. |
I stil not got this |
I m very confused with this, I still read know the loss_code but still don't know why,
what directly different with this,
here compute the pred_box and true_box iou in each picture, and get the best anchor for each per cell prod anchor_box,
1、iou_scores shape = [batch_size, grid_w, grid_h, anchor_num, max_box_per_image],
2、and then use,best_iou = tf.reduce_max(iou_scores, axis=4), get each best iou for each cell,
shape =[batch_size, grid_w, grid_h, anchor_num]
3、if the iou <0.6, it means the iou is not enough, so conf_mask[I]=0,
if iou >0.6, if means here probability have box, so conf_mask[i]=1
why still need to calculate the conf_mask but not use y_ture[...,4], just like the coord_mask, it's not easy to got is , every little help is very appreciate, thank in advance
@experiencor @hobson @mrshu @sirotenko @usatenko
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