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model:
pretrain: ckpt/ek100mir.pt
freeze_vis_backbone: true
freeze_txt_backbone: true
inflat_posemb: true # false for cascade models; true for single-stage models (default: true)
num_frames: 16
text_prompt:
n_ctx: 8
use_bank: true
visual_prompt:
num_layers: 12
prompt_dim: 512
num_tokens: 128
deep: true
deep_shared: false
split_st: false
pt_spt: true
pt_tmp: false
style: VoP_c_pool
n_seg: 16 # number of segments per video (n_seg=clip_length -> 1 frame/seg)
K_s: 8 # boundary of intra-frame/inter-frame attention (VoP_f+c)
pool:
size: 10
data:
dataset: ek100_mir
#root: /data/EK100/video_ht256px
#metadata: /data/EK100/epic-kitchens-100-annotations/retrieval_annotations/EPIC_100_retrieval_train.csv
#metadata_val: /data/EK100/epic-kitchens-100-annotations/retrieval_annotations/EPIC_100_retrieval_test.csv
#relevancy_path: /data/EK100/epic-kitchens-100-annotations/retrieval_annotations/relevancy/caption_relevancy_EPIC_100_retrieval_test.pkl
root: data/ek100_mir/video
metadata_val: data/ek100_mir/csv/{}.csv
relevancy_path: meta/ek100_mir/relevancy_sel.npy
narrations: meta/ek100_mir/EPIC_100_retrieval_test_sentence.csv
clip_length: 16
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