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from opencompass.multimodal.models.minigpt_4 import (
MiniGPT4COCOCaotionPromptConstructor,
MiniGPT4COCOCaptionPostProcessor,
)
# dataloader settings
val_pipeline = [
dict(type='mmpretrain.LoadImageFromFile'),
dict(type='mmpretrain.ToPIL', to_rgb=True),
dict(type='mmpretrain.torchvision/Resize',
size=(384, 384),
interpolation=3),
dict(type='mmpretrain.torchvision/ToTensor'),
dict(type='mmpretrain.torchvision/Normalize',
mean=(0.48145466, 0.4578275, 0.40821073),
std=(0.26862954, 0.26130258, 0.27577711)),
dict(type='mmpretrain.PackInputs', algorithm_keys=['image_id'])
]
dataset = dict(type='mmpretrain.COCOCaption',
data_root='data/coco',
data_prefix=dict(img_path='images'),
ann_file='annotations/coco_karpathy_val.json',
pipeline=val_pipeline)
minigpt_4_coco_caption_dataloader = dict(
batch_size=1,
num_workers=4,
dataset=dataset,
collate_fn=dict(type='pseudo_collate'),
sampler=dict(type='DefaultSampler', shuffle=False))
# model settings
minigpt_4_coco_caption_model = dict(
type='minigpt-4',
low_resource=False,
img_size=384,
llama_model='/path/to/vicuna_weights_7b/',
is_caption_task=True,
prompt_constructor=dict(type=MiniGPT4COCOCaotionPromptConstructor,
image_prompt='###Human: <Img><ImageHere></Img>',
reply_prompt='###Assistant:'),
post_processor=dict(type=MiniGPT4COCOCaptionPostProcessor))
# evaluation settings
minigpt_4_coco_caption_evaluator = [
dict(
type='mmpretrain.COCOCaption',
ann_file='data/coco/annotations/coco_karpathy_val_gt.json',
) # noqa
]
minigpt_4_coco_caption_load_from = '/path/to/prerained_minigpt4_7b.pth' # noqa
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