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import numpy as np
import torch.nn as nn
import torch.nn.functional as F
def str2ind(categoryname, classlist):
return [
i for i in range(len(classlist)) if categoryname == classlist[i].decode("utf-8")
][0]
def strlist2indlist(strlist, classlist):
return [str2ind(s, classlist) for s in strlist]
def strlist2multihot(strlist, classlist):
return np.sum(np.eye(len(classlist))[strlist2indlist(strlist, classlist)], axis=0)
def idx2multihot(id_list, num_class):
return np.sum(np.eye(num_class)[id_list], axis=0)
def write_results_to_eval_file(args, dmap, itr1, itr2):
file_folder = "./ckpt/" + args.dataset_name + "/eval/"
file_name = args.dataset_name + "-results.log"
fid = open(file_folder + file_name, "a+")
string_to_write = str(itr1)
string_to_write += " " + str(itr2)
for item in dmap:
string_to_write += " " + "%.2f" % item
fid.write(string_to_write + "\n")
fid.close()
def write_results_to_file(args, dmap, cmap, itr):
file_folder = "./ckpt/" + args.dataset_name + "/" + str(args.model_id) + "/"
file_name = args.dataset_name + "-results.log"
fid = open(file_folder + file_name, "a+")
string_to_write = str(itr)
for item in dmap:
string_to_write += " " + "%.2f" % item
string_to_write += " " + "%.2f" % cmap
fid.write(string_to_write + "\n")
fid.close()
def write_settings_to_file(args):
file_folder = "./ckpt/" + args.dataset_name + "/" + str(args.model_id) + "/"
file_name = args.dataset_name + "-results.log"
fid = open(file_folder + file_name, "a+")
string_to_write = "#" * 80 + "\n"
for arg in vars(args):
string_to_write += str(arg) + ": " + str(getattr(args, arg)) + "\n"
string_to_write += "*" * 80 + "\n"
fid.write(string_to_write)
fid.close()
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