File size: 1,424 Bytes
54216bc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
# base
dict_api = {
"api_key":"ADD",
}
base_dir = "your_path" # your data path ex) img_folder_path/egoschema
# scene clustering
divlam = 12
f_path = "your_path" # files from keywords dir
q_path = "your_path" # files from questions dir
a_path = "your_path"
img_folder = "your_path" # your img folder path ex) img_folder_path/egoschema/frames_900_4531/q_uid/image_sec_millisec.jpg
# coarse key frame detector
maximgslen = 32
limit_keywords = 25
concatname = "LVnet"
modelpath = "your_path" # model path
question_path = "your_path" # recommend using the same path with scene clustering answer path
answerpath = f"{base_dir}/kwkfmatching/kf_{concatname}.jsonl" # kwkfmatching is not necessary.
concatdir = f"{base_dir}/kwkfmatching/concatimg_{concatname}" # kwkfmatching is not necessary.
# fine key frame detector
kf_vlm = "gpt-4o"
kf_temp = None
kf_num_select = 3
kf_num_input_imgs = 32
kf_question_path = "your_path" # recommend using the same path with coarse key frame detector answer path
kf_answer_path = f"{base_dir}/kf_VLM/kf_VLM{kf_num_input_imgs}sel{kf_num_select}_{kf_question_path.split('/')[-1].split('.')[0]}.jsonl" # kf_VLM is not necessary.
# fine key frame detector refine
refine_num_group = 4
refine_kflen = 12
refine_output_path = f"{base_dir}/kf_VLM/refine/" + kf_answer_path.split('/')[-1] # kf_VLM is not necessary.
|