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