Spaces:
Paused
Paused
#!/usr/bin/python | |
#-*- coding: utf-8 -*- | |
import time, pdb, argparse, subprocess | |
import glob | |
import os | |
from tqdm import tqdm | |
from SyncNetInstance_calc_scores import * | |
# ==================== LOAD PARAMS ==================== | |
parser = argparse.ArgumentParser(description = "SyncNet"); | |
parser.add_argument('--initial_model', type=str, default="data/syncnet_v2.model", help=''); | |
parser.add_argument('--batch_size', type=int, default='20', help=''); | |
parser.add_argument('--vshift', type=int, default='15', help=''); | |
parser.add_argument('--data_root', type=str, required=True, help=''); | |
parser.add_argument('--tmp_dir', type=str, default="data/work/pytmp", help=''); | |
parser.add_argument('--reference', type=str, default="demo", help=''); | |
opt = parser.parse_args(); | |
# ==================== RUN EVALUATION ==================== | |
s = SyncNetInstance(); | |
s.loadParameters(opt.initial_model); | |
#print("Model %s loaded."%opt.initial_model); | |
path = os.path.join(opt.data_root, "*.mp4") | |
all_videos = glob.glob(path) | |
prog_bar = tqdm(range(len(all_videos))) | |
avg_confidence = 0. | |
avg_min_distance = 0. | |
for videofile_idx in prog_bar: | |
videofile = all_videos[videofile_idx] | |
offset, confidence, min_distance = s.evaluate(opt, videofile=videofile) | |
avg_confidence += confidence | |
avg_min_distance += min_distance | |
prog_bar.set_description('Avg Confidence: {}, Avg Minimum Dist: {}'.format(round(avg_confidence / (videofile_idx + 1), 3), round(avg_min_distance / (videofile_idx + 1), 3))) | |
prog_bar.refresh() | |
print ('Average Confidence: {}'.format(avg_confidence/len(all_videos))) | |
print ('Average Minimum Distance: {}'.format(avg_min_distance/len(all_videos))) | |