fix: 修复 dedup.py 语法错误和 pHash DCT 实现，修复 chunked_upload.py 缩进错误

apps/api/app/api/routes/chunked_upload.py

@@ -173,7 +173,7 @@ def _cleanup_expired_uploads() -> int:
                 expires_at = expires_at.replace(tzinfo=timezone.utc)
 
             # Only cleanup uploads that are not actively being uploaded
-    if expires_at < now and meta.get("status") != "uploading":
+            if expires_at < now and meta.get("status") != "uploading":
                 upload_id = meta["upload_id"]
                 chunk_dir = _get_chunk_dir(upload_id)
                 if chunk_dir.exists():

apps/worker/video_processing/dedup.py

@@ -27,12 +27,20 @@ if SessionLocal is None:
 
 
 def compute_phash(image: np.ndarray, hash_size: int = 8) -> str:
-    """Compute perceptual hash of an image."""
-    image = cv2.resize(image, (hash_size * 4, hash_size * 4))
-    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    avg = gray.mean()
-    diff = (gray > avg).astype(int)
-    hash_str = """.join(str(b) for row in diff for b in row)
+    """Compute perceptual hash of an image using DCT."""
+    # Resize to 32x32 for DCT
+    resized = cv2.resize(image, (hash_size * 4, hash_size * 4))
+    gray = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY).astype(np.float32)
+    # Apply 2D DCT
+    dct = cv2.dct(gray)
+    # Take top-left 8x8 low-frequency components
+    dct_low = dct[:hash_size, :hash_size]
+    # Compute median (excluding DC component at [0,0])
+    dct_low[0, 0] = 0
+    median = np.median(dct_low)
+    # Generate hash based on comparison with median
+    diff = (dct_low > median).astype(int)
+    hash_str = "".join(str(b) for row in diff for b in row)
     return hex(int(hash_str, 2))[2:]