def main(opt): if opt["mode"] == "train": BMN_Train(opt) elif opt["mode"] == "inference": if not os.path.exists("output/BMN_results"): os.makedirs("output/BMN_results") BMN_inference(opt) print("Post processing start") BMN_post_processing(opt) print("Post processing finished") evaluation_proposal(opt)
def main(opt): if opt["mode"] == "train": with open(opt["checkpoint_path"] + "/opts.json", "w") as opt_file: json.dump(opt, opt_file) BMN_Train(opt) elif opt["mode"] == "inference": if not os.path.exists(opt["output"] + "/BMN_results"): os.makedirs(opt["output"] + "/BMN_results") BMN_inference(opt) print("Post processing start") BMN_post_processing(opt) print("Post processing finished") evaluation_proposal(opt)
def main(opt): if opt["module"] == "BMN": mask = np.load(opt["bm_mask_path"]) opt["bm_mask"] = mask if opt["mode"] == "train": BMN_Train(opt) elif opt["mode"] == "inference": if not os.path.exists("output/BMN_results"): os.makedirs("output/BMN_results") BMN_inference(opt) else: print("Wrong mode. BMN has two modes: train and inference") elif opt["module"] == "Post_processing": print("Post processing start") BMN_post_processing(opt) print("Post processing finished") elif opt["module"] == "Evaluation": evaluation_proposal(opt) print("")