def main():
info_dir = "/mnt/nfs/work3/youngwookim/job_man/ppnc_50_pers_val"
#prediction_file = os.path.join(output_path, "ppnc_50_val_prediction")
prediction_file = os.path.join(output_path, "ppnc_pred_100K")
score_d = summarize_score(info_dir, prediction_file)
map_score = eval_map("train", score_d)
print(map_score)
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, sys.argv[2])
pred_file_path = os.path.join(out_dir, save_name + ".score")
score_d = summarize_score(info_file_path, pred_file_path)
save_to_pickle(score_d, "score_d")
print("Saved as 'score_d'")
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, save_name + ".info")
pred_file_path = os.path.join(out_dir, save_name + ".score")
score_d = summarize_score(info_file_path, pred_file_path)
map_score = eval_map("dev", score_d, False)
print(map_score)
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, save_name + ".info")
pred_file_path = os.path.join(out_dir, save_name + ".score")
score_d = summarize_score(info_file_path, pred_file_path)
# load pre-computed perspectives
split = "dev"
ap_list, cids = get_ap_list_from_score_d(score_d, split)
print_table(zip(cids, ap_list))
def main():
save_name = sys.argv[1]
out_dir = os.path.join(output_path, "cppnc")
exist_or_mkdir(out_dir)
info_file_path = os.path.join(out_dir, sys.argv[2])
pred_file_path = os.path.join(out_dir, save_name + ".score")
debug = False
split = "dev"
if len(sys.argv) > 3:
if sys.argv[3] == "debug":
debug = True
if len(sys.argv) > 4:
if sys.argv[4] == "train":
split = "train"
score_d = summarize_score(info_file_path, pred_file_path)
map_score = eval_map(split, score_d, debug)
print(map_score)
def main():
info_dir = "/mnt/nfs/work3/youngwookim/job_man/cppnc_val_info"
prediction_file = os.path.join(output_path, "cppnc_pred")
score_d = summarize_score(info_dir, prediction_file)
map_score = eval_map("train", score_d)
print(map_score)