AutoV-data / metadata /data_json.py
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Upload AutoV attention-map training data
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import json
import os
data = json.load(open('llava_v1_5_mix1k_filter.json'))
LAYERS = [15, 20, 22, 23]
collection = []
for item in data:
new_item = {}
image_path = item['image']
qs = item['conversations'][0]['value']
label = item['conversations'][1]['value']
idx_list =[]
attn_path = []
loss_list = []
for idx, l in enumerate(LAYERS):
idx_list.append(idx)
attn_path.append(f'APICLIP_llava_ViT-L-14-336_{l}/1_3_BICUBIC_0/{image_path}')
img = os.path.join(f'/mnt/bn/bes-mllm-shared/zhangyuan.kevin/attnmap/APICLIP_llava_ViT-L-14-336_{l}/1_3_BICUBIC_0/', image_path)
# TODO: 计算loss
# loss = Model(img, qs, label)
loss = 1
loss_list.append(loss)
new_item['image'] = item['image']
new_item['conversations'] = item['conversations']
new_item['id'] = item['id']
new_item['attn_map_path'] = attn_path
new_item['attn_map_idx'] = idx_list
new_item['llava_loss'] = loss_list
collection.append(new_item)
with open('llava_v1_5_mix1k_reward.json', 'w') as f:
json.dump(collection, f, indent=4)