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In the postprocess method of FastSAMPredictor, when critical_iou_index is > 1, it raises the following error:

Error:  expand(torch.FloatTensor{[2]}, size=[]): the number of sizes provided (0) must be greater or equal to the number of dimensions in the tensor (1)

In line 34 of fastsam.predict.py:

full_box = full_box.view(1, -1)
critical_iou_index = bbox_iou(full_box[0][:4], p[0][:, :4], iou_thres=0.9, image_shape=img.shape[2:])
if critical_iou_index.numel() != 0:
    full_box[0][4] = p[0][critical_iou_index][:,4] # ERROR HERE!
    full_box[0][6:] = p[0][critical_iou_index][:,6:]
    p[0][critical_iou_index] = full_box

It has been solved by returning the bboxes indices sorted by IoU in descending order, and taking the first critical_iou_index.

This may solve #202

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