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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Test FCN-SyncNet and Original SyncNet with multiple offset videos.
Creates test videos with known offsets and compares detection accuracy.
"""
import subprocess
import os
import sys
# Enable UTF-8 output on Windows
if sys.platform == 'win32':
import io
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8', errors='replace')
sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8', errors='replace')
def create_offset_video(source_video, offset_frames, output_path):
"""
Create a video with audio offset.
Args:
source_video: Path to source video
offset_frames: Positive = audio delayed (behind), Negative = audio ahead
output_path: Output video path
"""
if os.path.exists(output_path):
return True
if offset_frames >= 0:
# Delay audio - add silence at start
delay_ms = offset_frames * 40 # 40ms per frame at 25fps
cmd = [
'ffmpeg', '-y', '-i', source_video,
'-af', f'adelay={delay_ms}|{delay_ms}',
'-c:v', 'copy', output_path
]
else:
# Advance audio - trim start of audio
trim_sec = abs(offset_frames) * 0.04
cmd = [
'ffmpeg', '-y', '-i', source_video,
'-af', f'atrim=start={trim_sec},asetpts=PTS-STARTPTS',
'-c:v', 'copy', output_path
]
result = subprocess.run(cmd, capture_output=True)
return result.returncode == 0
def test_fcn_model(video_path, verbose=False):
"""Test with FCN-SyncNet model."""
from SyncNetModel_FCN import StreamSyncFCN
import torch
model = StreamSyncFCN(
max_offset=15,
pretrained_syncnet_path=None,
auto_load_pretrained=False
)
checkpoint = torch.load('checkpoints/syncnet_fcn_epoch2.pth', map_location='cpu')
encoder_state = {k: v for k, v in checkpoint['model_state_dict'].items()
if 'audio_encoder' in k or 'video_encoder' in k}
model.load_state_dict(encoder_state, strict=False)
model.eval()
offset, confidence, raw_offset = model.detect_offset_correlation(
video_path,
calibration_offset=3,
calibration_scale=-0.5,
calibration_baseline=-15,
verbose=verbose
)
return int(round(offset)), confidence
def test_original_model(video_path, verbose=False):
"""Test with Original SyncNet model."""
import argparse
from SyncNetInstance import SyncNetInstance
model = SyncNetInstance()
model.loadParameters('data/syncnet_v2.model')
opt = argparse.Namespace()
opt.tmp_dir = 'data/work/pytmp'
opt.reference = 'offset_test'
opt.batch_size = 20
opt.vshift = 15
offset, confidence, dist = model.evaluate(opt, video_path)
return int(offset), confidence
def main():
print()
print("=" * 75)
print(" Multi-Offset Sync Detection Test")
print(" Comparing FCN-SyncNet vs Original SyncNet")
print("=" * 75)
print()
source_video = 'data/example.avi'
# The source video has an inherent offset of +3 frames
# So when we add offset X, the expected detection is (3 + X) for Original SyncNet
base_offset = 3 # Known offset in example.avi
# Test offsets to add
test_offsets = [0, 5, 10, -5, -10]
print("Creating test videos with various offsets...")
print()
results = []
for added_offset in test_offsets:
output_path = f'data/test_offset_{added_offset:+d}.avi'
expected = base_offset + added_offset
print(f" Creating {output_path} (adding {added_offset:+d} frames)...")
if not create_offset_video(source_video, added_offset, output_path):
print(f" Failed to create video!")
continue
print(f" Testing FCN-SyncNet...")
fcn_offset, fcn_conf = test_fcn_model(output_path)
print(f" Testing Original SyncNet...")
orig_offset, orig_conf = test_original_model(output_path)
results.append({
'added': added_offset,
'expected': expected,
'fcn': fcn_offset,
'original': orig_offset,
'fcn_error': abs(fcn_offset - expected),
'orig_error': abs(orig_offset - expected)
})
print()
# Print results table
print()
print("=" * 75)
print(" RESULTS")
print("=" * 75)
print()
print(f" {'Added':<8} {'Expected':<10} {'FCN':<10} {'Original':<10} {'FCN Err':<10} {'Orig Err':<10}")
print(" " + "-" * 68)
fcn_total_error = 0
orig_total_error = 0
for r in results:
fcn_mark = "✓" if r['fcn_error'] <= 2 else "✗"
orig_mark = "✓" if r['orig_error'] <= 2 else "✗"
print(f" {r['added']:+8d} {r['expected']:+10d} {r['fcn']:+10d} {r['original']:+10d} {r['fcn_error']:>6d} {fcn_mark:<3} {r['orig_error']:>6d} {orig_mark}")
fcn_total_error += r['fcn_error']
orig_total_error += r['orig_error']
print(" " + "-" * 68)
print(f" {'TOTAL ERROR:':<28} {fcn_total_error:>10d} {orig_total_error:>10d}")
print()
# Summary
fcn_correct = sum(1 for r in results if r['fcn_error'] <= 2)
orig_correct = sum(1 for r in results if r['orig_error'] <= 2)
print(f" FCN-SyncNet: {fcn_correct}/{len(results)} correct (within 2 frames)")
print(f" Original SyncNet: {orig_correct}/{len(results)} correct (within 2 frames)")
print()
# Cleanup test videos
print("Cleaning up test videos...")
for added_offset in test_offsets:
output_path = f'data/test_offset_{added_offset:+d}.avi'
if os.path.exists(output_path):
os.remove(output_path)
print("Done!")
if __name__ == "__main__":
main()
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