Some dependency versions and quick inference

[He-Chao]

pip install yapf==0.30.0
pip install numpy==1.23.0

you need to change L301~L304 of /mnt/anaconda3/envs/smplerx/lib/python3.8/site-packages/torchgeometry/core/conversions.py（https://github.com/mks0601/I2L-MeshNet_RELEASE/issues/6#issuecomment-675152527）

mask_c0 = mask_d2.float() * mask_d0_d1.float()
mask_c1 = mask_d2.float() * (1 - mask_d0_d1.float())
mask_c2 = (1 - mask_d2.float()) * mask_d0_nd1.float()
mask_c3 = (1 - mask_d2.float()) * (1 - mask_d0_nd1.float())

You can use inference.py directly for inference without using srun

#!/usr/bin/env bash
set -x

PARTITION=Zoetrope

INPUT_VIDEO=$1
FORMAT=$2
FPS=$3
CKPT=$4

GPUS=1
JOB_NAME=inference_${INPUT_VIDEO}

GPUS_PER_NODE=$((${GPUS}<8?${GPUS}:8))
CPUS_PER_TASK=4 # ${CPUS_PER_TASK:-2}
SRUN_ARGS=${SRUN_ARGS:-""}

IMG_PATH=../demo/images/${INPUT_VIDEO}
SAVE_DIR=../demo/results/${INPUT_VIDEO}

# video to images
mkdir $IMG_PATH
mkdir $SAVE_DIR
ffmpeg -i ../demo/videos/${INPUT_VIDEO}.${FORMAT} -f image2 -vf fps=${FPS}/1 -qscale 0 ../demo/images/${INPUT_VIDEO}/%06d.jpg 

end_count=$(find "$IMG_PATH" -type f | wc -l)
echo $end_count

# inference
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
# srun -p ${PARTITION} \
#     --job-name=${JOB_NAME} \
#     --gres=gpu:${GPUS_PER_NODE} \
#     --ntasks=${GPUS} \
#     --ntasks-per-node=${GPUS_PER_NODE} \
#     --cpus-per-task=${CPUS_PER_TASK} \
#     --kill-on-bad-exit=1 \
#     ${SRUN_ARGS} \
python inference.py \
    --num_gpus ${GPUS_PER_NODE} \
    --exp_name output/demo_${JOB_NAME} \
    --pretrained_model ${CKPT} \
    --agora_benchmark agora_model \
    --img_path ${IMG_PATH} \
    --start 1 \
    --end  $end_count \
    --output_folder ${SAVE_DIR} \
    --show_verts \
    --show_bbox \
    --save_mesh \
    # --multi_person \
    # --iou_thr 0.2 \
    # --bbox_thr 20


# images to video
ffmpeg -y -f image2 -r ${FPS} -i ${SAVE_DIR}/img/%06d.jpg -vcodec mjpeg -qscale 0 -pix_fmt yuv420p ../demo/results/${INPUT_VIDEO}.mp4