About motion.py

[Someone1Wu]

How to modify the code if the pointlstm layer is deployed in stage 4?

[ycmin95]

The main idea here is change the "self.stage4" module to PointLSTM module. You can compare the usage of them here[L66-L74 v.s. L76-L82] to implement this.

[Someone1Wu]

The main idea here is change the "self.stage4" module to PointLSTM module. You can compare the usage of them here[L66-L74 v.s. L76-L82] to implement this. First of all thank you for your reply, I tried to change the code of stage 3 and stage 4 to the following：

stage 3: inter-frame, middle, applying lstm in this stage

    in_dims = fea2.shape[1] * 2 - 4
    pts_num //= self.downsample[1]

    ret_group_array3 = self.group.st_group_points(fea2, 3, [0, 1, 2], self.knn[2], 3)
    ret_array3, inputs, ind = self.select_ind(ret_group_array3, inputs,
                                              batchsize, in_dims, timestep, pts_num)
    fea3 = self.pool3(self.stage3(ret_array3)).view(batchsize,-1,timestep,pts_num)
    fea3 = torch.cat((inputs, fea3), dim=1)

    # stage 4: inter-frame, late
    in_dims = fea3.shape[1] * 2 - 4
    pts_num //= self.downsample[2]

    output = self.lstm(fea3.permute(0, 2, 1, 3))  ##
    fea4 = output[0][0].squeeze(-1).permute(0, 2, 1, 3)
    ret_group_array4 = self.group.st_group_points(fea3, 3, [0, 1, 2], self.knn[3], 3)
    ret_array4, inputs, ind = self.select_ind(ret_group_array4, inputs,
                                              batchsize, in_dims, timestep, pts_num)
    fea4 = fea4.gather(-1, ind.unsqueeze(1).expand(-1, fea4.shape[1], -1, -1))

Unfortunately, it reported an error with the following：

RuntimeError: Sizes of tensors must match except in dimension 2. Got 64 and 32 (The offending index is 0)

I don't know where it went wrong.

[ycmin95]

You can check whether the number of points and the channel dimension are consistent.