#!/usr/bin/env python
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
# Reval = re-eval. Re-evaluate saved detections.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import _init_paths
from model.test import apply_nms
from model.config import cfg
from datasets.factory import get_imdb
import pickle
import os, sys, argparse
import numpy as np
import pprint
def parse_args():
"""
Parse input arguments
"""
parser = argparse.ArgumentParser(description='Re-evaluate results')
parser.add_argument('output_dir', nargs=1, help='results directory',
type=str)
parser.add_argument('--imdb', dest='imdb_name',
help='dataset to re-evaluate',
default='voc_2007_test', type=str)
parser.add_argument('--comp', dest='comp_mode', help='competition mode',
action='store_true')
if len(sys.argv) == 1:
parser.print_help()
sys.exit(1)
args = parser.parse_args()
return args
def from_dets(imdb_name, output_dir, args):
imdb = get_imdb(imdb_name)
imdb.competition_mode(args.comp_mode)
with open(os.path.join(output_dir, 'discovery.pkl'), 'rb') as f:
dets = pickle.load(f)
print('Evaluating detections')
imdb.evaluate_discovery(dets, output_dir)
if __name__ == '__main__':
args = parse_args()
pprint.pprint(args)
output_dir = os.path.abspath(args.output_dir[0])
imdb_name = args.imdb_name
from_dets(imdb_name, output_dir, args)
