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)