File size: 1,879 Bytes
10bc78d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | """Check a video against the dataset to guess whether it matches something already stored."""
import imagehash
import storage
from fingerprint import extract_fingerprint
# hash_size=8 -> 64-bit phash, so distances range 0-64.
DEFAULT_HAMMING_THRESHOLD = 10
DEFAULT_MATCH_RATIO = 0.5
def _hex_to_hash(h: str):
return imagehash.hex_to_hash(h)
def compare_to_video(query_hashes: list, stored_hashes: list, hamming_threshold: int) -> float:
"""Fraction of query frames that have a close match somewhere in the stored video."""
if not query_hashes or not stored_hashes:
return 0.0
stored_decoded = [_hex_to_hash(f["hash"]) for f in stored_hashes]
hits = 0
for qf in query_hashes:
qh = _hex_to_hash(qf["hash"])
best = min(qh - sh for sh in stored_decoded)
if best <= hamming_threshold:
hits += 1
return hits / len(query_hashes)
def check_video(
query_path: str,
hamming_threshold: int = DEFAULT_HAMMING_THRESHOLD,
match_ratio_threshold: float = DEFAULT_MATCH_RATIO,
samples_per_second: float = 1.0,
) -> dict:
query_hashes = extract_fingerprint(query_path, samples_per_second=samples_per_second)
candidates = []
for meta in storage.list_videos():
video_id = meta["id"]
stored_hashes = storage.load_all_hashes(video_id)
ratio = compare_to_video(query_hashes, stored_hashes, hamming_threshold)
candidates.append({"id": video_id, "title": meta["title"], "match_ratio": round(ratio, 3)})
candidates.sort(key=lambda c: c["match_ratio"], reverse=True)
best = candidates[0] if candidates else None
is_match = bool(best and best["match_ratio"] >= match_ratio_threshold)
return {
"query_path": query_path,
"is_likely_copyrighted": is_match,
"best_match": best,
"top_candidates": candidates[:5],
}
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