jongwoopark7978

chore: add project files

54216bc over 1 year ago

1.42 kB

# 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.

	# 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.