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Update ui.py

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DETECT_EVERY_N = 2 reuses cached face positions on alternate frames
This commit is contained in:
Kenneth Estanislao
2026-02-12 18:54:18 +08:00
parent 523ee53c34
commit 36b6ea0019
1 changed files with 42 additions and 1 deletions
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modules/ui.py
+42 -1
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@@ -9,10 +9,12 @@ import time
import json
import queue
import threading
import numpy as np
import modules.globals
import modules.metadata
from modules.face_analyser import (
get_one_face,
get_many_faces,
get_unique_faces_from_target_image,
get_unique_faces_from_target_video,
add_blank_map,
@@ -971,16 +973,28 @@ def _capture_thread_func(cap, capture_queue, stop_event):
pass
# How often to run full face detection. On intermediate frames the last
# detected face positions are reused, which significantly reduces the
# per-frame cost of the processing thread.
DETECT_EVERY_N = 2
def _processing_thread_func(capture_queue, processed_queue, stop_event):
"""Processing thread: takes raw frames from capture_queue, applies face
processing, and puts results into processed_queue. Drops processed frames
when the output queue is full so the UI always gets the latest result."""
when the output queue is full so the UI always gets the latest result.
Uses DETECT_EVERY_N to skip expensive face detection on intermediate
frames, reusing cached face positions instead."""
frame_processors = get_frame_processors_modules(modules.globals.frame_processors)
source_image = None
prev_time = time.time()
fps_update_interval = 0.5
frame_count = 0
fps = 0
proc_frame_index = 0
cached_target_face = None # cached single-face result
cached_many_faces = None # cached many-faces result
while not stop_event.is_set():
try:
@@ -989,6 +1003,8 @@ def _processing_thread_func(capture_queue, processed_queue, stop_event):
continue
temp_frame = frame.copy()
run_detection = (proc_frame_index % DETECT_EVERY_N == 0)
proc_frame_index += 1
if modules.globals.live_mirror:
temp_frame = cv2.flip(temp_frame, 1)
@@ -997,10 +1013,35 @@ def _processing_thread_func(capture_queue, processed_queue, stop_event):
if source_image is None and modules.globals.source_path:
source_image = get_one_face(cv2.imread(modules.globals.source_path))
# Update face detection cache on detection frames
if run_detection or (cached_target_face is None and cached_many_faces is None):
if modules.globals.many_faces:
cached_many_faces = get_many_faces(temp_frame)
cached_target_face = None
else:
cached_target_face = get_one_face(temp_frame)
cached_many_faces = None
for frame_processor in frame_processors:
if frame_processor.NAME == "DLC.FACE-ENHANCER":
if modules.globals.fp_ui["face_enhancer"]:
temp_frame = frame_processor.process_frame(None, temp_frame)
elif frame_processor.NAME == "DLC.FACE-SWAPPER":
# Use cached face positions to skip redundant detection
swapped_bboxes = []
if modules.globals.many_faces and cached_many_faces:
result = temp_frame.copy()
for t_face in cached_many_faces:
result = frame_processor.swap_face(source_image, t_face, result)
if hasattr(t_face, 'bbox') and t_face.bbox is not None:
swapped_bboxes.append(t_face.bbox.astype(int))
temp_frame = result
elif cached_target_face is not None:
temp_frame = frame_processor.swap_face(source_image, cached_target_face, temp_frame)
if hasattr(cached_target_face, 'bbox') and cached_target_face.bbox is not None:
swapped_bboxes.append(cached_target_face.bbox.astype(int))
# Apply post-processing (sharpening, interpolation)
temp_frame = frame_processor.apply_post_processing(temp_frame, swapped_bboxes)
else:
temp_frame = frame_processor.process_frame(source_image, temp_frame)
else: