alinlab / s-clip Goto Github PK

Hello:
Thank you for sharing such great code. But I have a question, I noticed in your paper the method for generating keywords: keywords can be obtained from class names or extracted by using algorithms like YAKE applied to captions.
Could you please send me your program for generating keywords ?
Thanks.

hello,Thank you for sharing such great code. But I have a question, what file is txtclasses_rsicd in your code? I tried to reproduce your code but could not find this file, this file has been confused for several days, could you give me some advice?
class RSICD_CLS(RSICD):
def init(self, *args, **kwargs):
super().init(*args, **kwargs)
self.load_class_info(os.path.join(self.root, "txtclasses_rsicd")) -------this i dont understand

def load_class_info(self, class_dir):
    classes = []
    path2class = {}
    for idx, fn in enumerate(sorted(os.listdir(class_dir))):
        classes.append(fn.split(".txt")[0])
        with open(os.path.join(class_dir, fn)) as f:
            for line in f.readlines():
                path2class[line.strip()] = idx

    self.classes = classes
    self.path2class = path2class

Hello,Thank you for sharing such great code. But I have a question, I noticed in your paper that the Image text retrieval R@1 parameter metric used in the RSICD dataset is 4.2, but my actual result of running the program is that the Image text retrieval R@1 is only about 0.04, the following is my parameter configuration.

`METHOD=(
"ours"
"base"
)
SEED=("0")
RATIO=(
"0.1"
)
MODEL=(
"RN50"
#"ViT-B-32"
#"ViT-B-16"
)
ImagenetVal=(
#"RSICD-CLS"
#"UCM-CLS",
#"WHU-RS19",
#"RSSCN7",
#"AID",
"RESISC45"
)

for val in "${ImagenetVal[@]}"; do
for model in "${MODEL[@]}"; do
for ratio in "${RATIO[@]}"; do
for method in "${METHOD[@]}"; do
for seed in "${SEED[@]}"; do
torchrun --nproc_per_node 2 -m main
--model "${model}"
--pretrained openai
--train-data "RS-ALL"
--label-ratio "${ratio}"
--val-data "RS-ALL"
--imagenet-val "${val}"
--keyword-path "keywords/RS/class-name.txt"
--lr 5e-5
--batch-size 64
--warmup 10
--epochs 25
--zeroshot-frequency 3
--precision amp
--method "${method}"
--seed "${seed}"
--report-to wandb
--wandb-project-name "S-CLIP" \

done
done
done
done
done`

Could you give me some advice?