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Deep-Live-Cam
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pull/1376/head
google-labs-jules[bot] 2025-06-20 18:51:12 +00:00
parent d5a3fb0c47
commit 74ce8569f5
2 changed files with 31 additions and 12 deletions
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2
modules/processors/frame/face_enhancer.py
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@ -82,7 +82,7 @@ def get_face_enhancer() -> Any:
selected_device = torch.device("cpu")
device_priority.append("CPU")
FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1, device=selected_device)
FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=2, device=selected_device)
# for debug:
print(f"Selected device: {selected_device} and device priority: {device_priority}")

41
modules/processors/frame/face_swapper.py
View File

@ -32,7 +32,7 @@ def pre_check() -> bool:
conditional_download(
download_directory_path,
[
"https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx"
"https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128.onnx"
],
)
return True
@ -60,7 +60,7 @@ def get_face_swapper() -> Any:
with THREAD_LOCK:
if FACE_SWAPPER is None:
model_path = os.path.join(models_dir, "inswapper_128_fp16.onnx")
model_path = os.path.join(models_dir, "inswapper_128.onnx")
FACE_SWAPPER = insightface.model_zoo.get_model(
model_path, providers=modules.globals.execution_providers
)
@ -70,18 +70,34 @@ def get_face_swapper() -> Any:
def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
face_swapper = get_face_swapper()
# Apply the face swap
swapped_frame = face_swapper.get(
temp_frame, target_face, source_face, paste_back=True
)
# Statistical color correction
if getattr(modules.globals, 'statistical_color_correction', True) and target_face.bbox is not None:
x1, y1, x2, y2 = target_face.bbox.astype(int)
original_target_face_roi = temp_frame[y1:y2, x1:x2].copy()
# Apply the face swap
swapped_frame = face_swapper.get(
temp_frame, target_face, source_face, paste_back=True
)
if original_target_face_roi.size > 0:
swapped_face_roi = swapped_frame[y1:y2, x1:x2].copy()
if swapped_face_roi.size > 0:
corrected_swapped_face_roi = apply_color_transfer(swapped_face_roi, original_target_face_roi)
swapped_frame[y1:y2, x1:x2] = corrected_swapped_face_roi
else:
# Apply the face swap without statistical color correction
swapped_frame = face_swapper.get(
temp_frame, target_face, source_face, paste_back=True
)
if modules.globals.mouth_mask:
# Create a mask for the target face
face_mask = create_face_mask(target_face, temp_frame)
face_mask = create_face_mask(target_face, swapped_frame) # Use swapped_frame here
# Create the mouth mask
mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon = (
create_lower_mouth_mask(target_face, temp_frame)
create_lower_mouth_mask(target_face, swapped_frame) # Use swapped_frame here
)
# Apply the mouth area
@ -367,7 +383,8 @@ def create_lower_mouth_mask(
cv2.fillPoly(mask_roi, [expanded_landmarks - [min_x, min_y]], 255)
# Apply Gaussian blur to soften the mask edges
mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
kernel_size_mouth = getattr(modules.globals, 'mouth_mask_blur_kernel_size', (9, 9))
mask_roi = cv2.GaussianBlur(mask_roi, kernel_size_mouth, 0)
# Place the mask ROI in the full-sized mask
mask[min_y:max_y, min_x:max_x] = mask_roi
@ -553,7 +570,8 @@ def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
face_top = np.min([right_side_face[0, 1], left_side_face[-1, 1]])
forehead_height = face_top - eyebrow_top
extended_forehead_height = int(forehead_height * 5.0) # Extend by 50%
forehead_factor = getattr(modules.globals, 'forehead_extension_factor', 2.5)
extended_forehead_height = int(forehead_height * forehead_factor)
# Create forehead points
forehead_left = right_side_face[0].copy()
@ -595,7 +613,8 @@ def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
cv2.fillConvexPoly(mask, hull_padded, 255)
# Smooth the mask edges
mask = cv2.GaussianBlur(mask, (5, 5), 3)
kernel_size_face = getattr(modules.globals, 'face_mask_blur_kernel_size', (5, 5))
mask = cv2.GaussianBlur(mask, kernel_size_face, 0)
return mask