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# The port for communication. Note that if you want to run multiple tasks on the same machine, | |
# you need to specify different port numbers. | |
export MASTER_PORT=4081 | |
user_dir=../../ofa_module | |
bpe_dir=../../utils/BPE | |
# It may take a long time for the full evaluation. You can sample a small split from the full_test split. | |
# But please remember that you need at least thousands of images to compute FID and IS, otherwise the resulting scores | |
# might also no longer correlate with visual quality. | |
data=../../dataset/coco_image_gen_data/coco_vqgan_full_test.tsv | |
path=../../checkpoints/image_gen_large_best.pt | |
selected_cols=0,2,1 | |
split='test' | |
VQGAN_MODEL_PATH=../../checkpoints/vqgan/last.ckpt | |
VQGAN_CONFIG_PATH=../../checkpoints/vqgan/model.yaml | |
CLIP_MODEL_PATH=../../checkpoints/clip/ViT-B-16.pt | |
GEN_IMAGE_PATH=../../results/image_gen | |
CUDA_VISIBLE_DEVICES=4,5,6,7 python3 -m torch.distributed.launch --nproc_per_node=4 --master_port=${MASTER_PORT} ../../evaluate.py \ | |
${data} \ | |
--path=${path} \ | |
--user-dir=${user_dir} \ | |
--task=image_gen \ | |
--batch-size=1 \ | |
--log-format=simple --log-interval=1 \ | |
--seed=42 \ | |
--gen-subset=${split} \ | |
--beam=24 \ | |
--min-len=1024 \ | |
--max-len-a=0 \ | |
--max-len-b=1024 \ | |
--sampling-topk=256 \ | |
--temperature=1.0 \ | |
--code-image-size=256 \ | |
--constraint-range=50265,58457 \ | |
--fp16 \ | |
--num-workers=0 \ | |
--model-overrides="{\"data\":\"${data}\",\"bpe_dir\":\"${bpe_dir}\",\"selected_cols\":\"${selected_cols}\",\"clip_model_path\":\"${CLIP_MODEL_PATH}\",\"vqgan_model_path\":\"${VQGAN_MODEL_PATH}\",\"vqgan_config_path\":\"${VQGAN_CONFIG_PATH}\",\"gen_images_path\":\"${GEN_IMAGE_PATH}\"}" | |
# install requiremnts | |
pip install scipy | |
# compute IS | |
python inception_score.py --gpu 4 --batch-size 128 --path1 ${GEN_IMAGE_PATH}/top1 | |
# compute FID, download statistics for test dataset first. | |
wget https://ofa-beijing.oss-cn-beijing.aliyuncs.com/datasets/coco_image_gen_data/gt_stat.npz | |
python fid_score.py --gpu 4 --batch-size 128 --path1 ${GEN_IMAGE_PATH}/top1 --path2 ./gt_stat.npz |