implement a batch inference

[wingskh]

I would like to modify the top_down_pose_tracking_demo_with_mmdet.py for batch inference.
After reading #608, I aggregate the bboxes from multiple images before collating the batch.
However, I have a question about this line of code:

mmpose/mmpose/apis/inference.py

Line 299 in e7f929f

batch_data = collate(batch_data, samples_per_gpu=1)

Since the model hasn't utilized the GPUs fully, I want to increase the size of samples_per_gpu but I got the error as below
assert img.size(0) == len(img_metas)

[jin-s13]

see #25

[jin-s13]

I will recommend using slurm_test or dist_test for batch-inference.

[wingskh]

see #25

Thank you so much for the speedy reply.
I am sorry that I have some problems about the function estimate_batch in #25
Q1: What is input_transforms in estimate_batch?
Q2: As pose detection should be processed after human detection, is the variable imgs a list of cropped human images?

[dongrongliang]

For those who still stuck on this issue, here is quick fix:"img_metas = img_metas.data[0]"

[Lingyun97]

For those who still stuck on this issue, here is quick fix:"img_metas = img_metas.data[0]"

@dongrongliang Where to apply the fix and which version you are using?
I am still stuck on this.