| #!/bin/bash |
|
|
| baseModel='LLAVA' |
| |
|
|
| modelPath=${1} |
| if [ -z "${modelPath}" ] |
| then |
| echo "\$modelPath is empty Using robust model from here: " |
| modelPath=/path/to/ckpt.pt |
| modelPath1=ckpt_name |
| else |
| echo "\$modelPath is NOT empty" |
| modelPath1=${modelPath} |
| fi |
|
|
| answerFile="${baseModel}_${modelPath1}" |
| echo "Will save to the following json: " |
| echo $answerFile |
|
|
| python -m llava.eval.model_vqa_loader \ |
| --model-path liuhaotian/llava-v1.5-7b \ |
| --eval-model ${baseModel} \ |
| --pretrained_rob_path ${modelPath} \ |
| --question-file ./pope_eval/llava_pope_test.jsonl \ |
| --image-folder PATH_TO_COCO-VAL2014 \ |
| --answers-file ./pope_eval/${answerFile}.jsonl \ |
| --temperature 0 \ |
| --conv-mode vicuna_v1 |
|
|
|
|
| python llava/eval/eval_pope.py \ |
| --model-name $answerFile \ |
| --annotation-dir ./pope_eval/coco/ \ |
| --question-file ./pope_eval/llava_pope_test.jsonl \ |
| --result-file ./pope_eval/${answerFile}.jsonl |
|
|