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⚡️ Speed up method EmbedMaxDct.infer_dct_svd by 109% #162

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⚡️ Speed up method EmbedMaxDct.infer_dct_svd by 109% #162

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17 changes: 10 additions & 7 deletions invokeai/backend/image_util/imwatermark/vendor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,9 +7,10 @@
# `opencv-contrib-python`. It's easier to copy the code over than complicate the installation process by
# requiring an extra post-install step of removing `opencv-python` and installing `opencv-contrib-python`.

import base64
import struct
import uuid
import base64

import cv2
import numpy as np
import pywt
Expand Down Expand Up @@ -244,12 +245,14 @@ def diffuse_dct_svd(self, block, wmBit, scale):
return cv2.idct(np.dot(u, np.dot(np.diag(s), v)))

def infer_dct_svd(self, block, scale):
u, s, v = np.linalg.svd(cv2.dct(block))

score = 0
score = int((s[0] % scale) > scale * 0.5)
return score
if score >= 0.5:
# Compute the DCT and its singular values more efficiently (in-place where possible)
dct_block = cv2.dct(block)
# Use compute_uv=False for smaller arrays, but only for performance—keep return type/behavior the same
# For compatibility: SVD is computed only for singular values
s = np.linalg.svd(dct_block, compute_uv=False)
return int((s[0] % scale) > scale * 0.5)
# unreachable code below left as is for behavioral preservation, but not executed
if ((s[0] % scale) > scale * 0.5) >= 0.5:
return 1.0
else:
return 0.0
Expand Down