size

update branch

.python-version

@@ -0,0 +1 @@
+3.10.0

README.md

@@ -9,52 +9,90 @@
 </p>
 
 <p align="center">
-  <img src="media/demo.gif" alt="Demo GIF">
-  <img src="media/avgpcperformancedemo.gif" alt="Performance Demo GIF">
+  <img src="media/demo.gif" alt="Demo GIF" width="800">
 </p>
 
 ##  Disclaimer
-###### This software is intended as a productive contribution to the AI-generated media industry. It aims to assist artists with tasks like animating custom characters or using them as models for clothing, etc.
 
-###### We are aware of the potential for unethical applications and are committed to preventative measures. A built-in check prevents the program from processing inappropriate media (nudity, graphic content, sensitive material like war footage, etc.). We will continue to develop this project responsibly, adhering to the law and ethics. We may shut down the project or add watermarks if legally required.
+This deepfake software is designed to be a productive tool for the AI-generated media industry. It can assist artists in animating custom characters, creating engaging content, and even using models for clothing design.
 
-###### Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online. We are not responsible for end-user actions.
+We are aware of the potential for unethical applications and are committed to preventative measures. A built-in check prevents the program from processing inappropriate media (nudity, graphic content, sensitive material like war footage, etc.). We will continue to develop this project responsibly, adhering to the law and ethics. We may shut down the project or add watermarks if legally required.
 
-## Quick Start - Pre-built
-<div align="center">
-  <a href="https://hacksider.gumroad.com/l/vccdmm">
-    <img src="https://github.com/user-attachments/assets/7d993b32-e3e8-4cd3-bbfb-a549152ebdd5" width="285" height="77" />
-  </a>
-  <a href="https://krshh.gumroad.com/l/Deep-Live-Cam-Mac">
-    <img src="https://github.com/user-attachments/assets/d5d913b5-a7de-4609-96b9-979a5749a703" width="285" height="77" />
-  </a>
-</div>
+- Ethical Use: Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online.
 
-## Features - Everything is real-time
+- Content Restrictions: The software includes built-in checks to prevent processing inappropriate media, such as nudity, graphic content, or sensitive material.
+
+- Legal Compliance: We adhere to all relevant laws and ethical guidelines. If legally required, we may shut down the project or add watermarks to the output.
+
+- User Responsibility: We are not responsible for end-user actions. Users must ensure their use of the software aligns with ethical standards and legal requirements.
+
+By using this software, you agree to these terms and commit to using it in a manner that respects the rights and dignity of others.
+
+Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online. We are not responsible for end-user actions.
+
+
+## Quick Start - Pre-built (Windows / Nvidia)
+
+  <a href="https://hacksider.gumroad.com/l/vccdmm"> <img src="https://github.com/user-attachments/assets/7d993b32-e3e8-4cd3-bbfb-a549152ebdd5" width="285" height="77" />
+
+##### This is the fastest build you can get if you have a discrete NVIDIA GPU.
+
+## Quick Start - Pre-built (Mac / Silicon)
+    
+  <a href="https://krshh.gumroad.com/l/Deep-Live-Cam-Mac"> <img src="https://github.com/user-attachments/assets/d5d913b5-a7de-4609-96b9-979a5749a703" width="285" height="77" />
+ 
+###### These Pre-builts are perfect for non-technical users or those who don’t have time to, or can't manually install all the requirements. Just a heads-up: this is an open-source project, so you can also install it manually.
+
+## TLDR; Live Deepfake in just 3 Clicks
+![easysteps](https://github.com/user-attachments/assets/af825228-852c-411b-b787-ffd9aac72fc6)
+1. Select a face
+2. Select which camera to use
+3. Press live!
+
+## Features & Uses - Everything is real-time
 
 ### Mouth Mask
 
-**Retain your original mouth using Mouth Mask**
+**Retain your original mouth for accurate movement using Mouth Mask**
 
-![resizable-gif](media/ludwig.gif)
+<p align="center">
+  <img src="media/ludwig.gif" alt="resizable-gif">
+</p>
 
 ### Face Mapping
 
-**Use different faces on multiple subjects**
+**Use different faces on multiple subjects simultaneously**
 
-![face\_mapping\_source](media/streamers.gif)
+<p align="center">
+  <img src="media/streamers.gif" alt="face_mapping_source">
+</p>
 
 ### Your Movie, Your Face
 
 **Watch movies with any face in real-time**
 
-![movie](media/movie.gif)
+<p align="center">
+  <img src="media/movie.gif" alt="movie">
+</p>
 
-## Benchmarks
+### Live Show
 
-**Nearly 0% detection!**
+**Run Live shows and performances**
+
+<p align="center">
+  <img src="media/live_show.gif" alt="show">
+</p>
+
+### Memes
+
+**Create Your most viral meme yet**
+
+<p align="center">
+  <img src="media/meme.gif" alt="show" width="450"> 
+  <br>
+  <sub>Created using Many Faces feature in Deep-Live-Cam</sub>
+</p>
 
-![bench](media/deepwarebench.gif)
 
 ## Installation (Manual)
 
@@ -72,7 +110,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
 -   Python (3.10 recommended)
 -   pip
 -   git
--   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA)
+-   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) - ```iex (irm ffmpeg.tc.ht)```
 -   [Visual Studio 2022 Runtimes (Windows)](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
 
 **2. Clone the Repository**
@@ -84,7 +122,7 @@ https://github.com/hacksider/Deep-Live-Cam.git
 **3. Download the Models**
 
 1. [GFPGANv1.4](https://huggingface.co/hacksider/deep-live-cam/resolve/main/GFPGANv1.4.pth)
-2. [inswapper\_128\_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx) (Note: Use this [replacement version](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128.onnx) if you encounter issues)
+2. [inswapper\_128\_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx)
 
 Place these files in the "**models**" folder.
 
@@ -217,7 +255,6 @@ options:
   --many-faces                                             process every face
   --map-faces                                              map source target faces
   --mouth-mask                                             mask the mouth region
-  --nsfw-filter                                            filter the NSFW image or video
   --video-encoder {libx264,libx265,libvpx-vp9}             adjust output video encoder
   --video-quality [0-51]                                   adjust output video quality
   --live-mirror                                            the live camera display as you see it in the front-facing camera frame
@@ -276,3 +313,5 @@ Looking for a CLI mode? Using the -s/--source argument will make the run program
    <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=hacksider/deep-live-cam&type=Date" />
  </picture>
 </a>
+
+

modules/core.py

@@ -20,6 +20,7 @@ import modules.metadata
 import modules.ui as ui
 from modules.processors.frame.core import get_frame_processors_modules
 from modules.utilities import has_image_extension, is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clean_temp, normalize_output_path
+from modules.fake_face_handler import cleanup_fake_face
 
 if 'ROCMExecutionProvider' in modules.globals.execution_providers:
     del torch
@@ -35,9 +36,7 @@ def parse_args() -> None:
     program.add_argument('-t', '--target', help='select an target image or video', dest='target_path')
     program.add_argument('-o', '--output', help='select output file or directory', dest='output_path')
     program.add_argument('--frame-processor', help='pipeline of frame processors', dest='frame_processor', default=['face_swapper'], choices=['face_swapper', 'face_enhancer'], nargs='+')
-    program.add_argument('--keep-fps', help='keep original fps', dest='keep_fps', action='store_true', default=False)
     program.add_argument('--keep-audio', help='keep original audio', dest='keep_audio', action='store_true', default=True)
-    program.add_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true', default=False)
     program.add_argument('--many-faces', help='process every face', dest='many_faces', action='store_true', default=False)
     program.add_argument('--nsfw-filter', help='filter the NSFW image or video', dest='nsfw_filter', action='store_true', default=False)
     program.add_argument('--map-faces', help='map source target faces', dest='map_faces', action='store_true', default=False)
@@ -65,9 +64,9 @@ def parse_args() -> None:
     modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path, args.output_path)
     modules.globals.frame_processors = args.frame_processor
     modules.globals.headless = args.source_path or args.target_path or args.output_path
-    modules.globals.keep_fps = args.keep_fps
+    modules.globals.keep_fps = True
+    modules.globals.keep_frames = True
     modules.globals.keep_audio = args.keep_audio
-    modules.globals.keep_frames = args.keep_frames
     modules.globals.many_faces = args.many_faces
     modules.globals.mouth_mask = args.mouth_mask
     modules.globals.nsfw_filter = args.nsfw_filter
@@ -241,6 +240,7 @@ def start() -> None:
 def destroy(to_quit=True) -> None:
     if modules.globals.target_path:
         clean_temp(modules.globals.target_path)
+    cleanup_fake_face()
     if to_quit: quit()
 
 

modules/fake_face_handler.py

@@ -0,0 +1,120 @@
+import os
+import requests
+import tempfile
+from pathlib import Path
+import cv2
+import numpy as np
+import modules.globals
+
+def add_padding_to_face(image, padding_ratio=0.3):
+    """Add padding around the face image
+    
+    Args:
+        image: The input face image
+        padding_ratio: Amount of padding to add as a ratio of image dimensions
+        
+    Returns:
+        Padded image with background padding added
+    """
+    if image is None:
+        return None
+        
+    height, width = image.shape[:2]
+    pad_x = int(width * padding_ratio)
+    pad_y = int(height * padding_ratio)
+    
+    # Create larger image with padding
+    padded_height = height + 2 * pad_y
+    padded_width = width + 2 * pad_x
+    padded_image = np.zeros((padded_height, padded_width, 3), dtype=np.uint8)
+    
+    # Fill padded area with blurred and darkened edge pixels
+    edge_color = cv2.blur(image, (15, 15))
+    edge_color = (edge_color * 0.6).astype(np.uint8)  # Darken the padding
+    
+    # Fill the padded image with original face
+    padded_image[pad_y:pad_y+height, pad_x:pad_x+width] = image
+    
+    # Fill padding areas with edge color
+    # Top padding - repeat first row
+    top_edge = edge_color[0, :, :]
+    for i in range(pad_y):
+        padded_image[i, pad_x:pad_x+width] = top_edge
+        
+    # Bottom padding - repeat last row
+    bottom_edge = edge_color[-1, :, :]
+    for i in range(pad_y):
+        padded_image[pad_y+height+i, pad_x:pad_x+width] = bottom_edge
+        
+    # Left padding - repeat first column
+    left_edge = edge_color[:, 0, :]
+    for i in range(pad_x):
+        padded_image[pad_y:pad_y+height, i] = left_edge
+        
+    # Right padding - repeat last column
+    right_edge = edge_color[:, -1, :]
+    for i in range(pad_x):
+        padded_image[pad_y:pad_y+height, pad_x+width+i] = right_edge
+        
+    # Fill corners with nearest edge colors
+    # Top-left corner
+    padded_image[:pad_y, :pad_x] = edge_color[0, 0, :]
+    # Top-right corner
+    padded_image[:pad_y, pad_x+width:] = edge_color[0, -1, :]
+    # Bottom-left corner
+    padded_image[pad_y+height:, :pad_x] = edge_color[-1, 0, :]
+    # Bottom-right corner
+    padded_image[pad_y+height:, pad_x+width:] = edge_color[-1, -1, :]
+    
+    return padded_image
+
+def get_fake_face() -> str:
+    """Fetch a face from thispersondoesnotexist.com and save it temporarily"""
+    try:
+        # Create temp directory if it doesn't exist
+        temp_dir = Path(tempfile.gettempdir()) / "deep-live-cam"
+        temp_dir.mkdir(parents=True, exist_ok=True)
+        
+        # Generate temp file path
+        temp_file = temp_dir / "fake_face.jpg"
+        
+        # Basic headers to mimic a browser request
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
+        }
+        
+        # Fetch the image
+        response = requests.get('https://thispersondoesnotexist.com', headers=headers)
+        
+        if response.status_code == 200:
+            # Read image from response
+            image_array = np.asarray(bytearray(response.content), dtype=np.uint8)
+            image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
+            
+            # Add padding around the face
+            padded_image = add_padding_to_face(image)
+            
+            # Save the padded image
+            cv2.imwrite(str(temp_file), padded_image)
+            return str(temp_file)
+        else:
+            print(f"Failed to fetch fake face: {response.status_code}")
+            return None
+    except Exception as e:
+        print(f"Error fetching fake face: {str(e)}")
+        return None
+
+def cleanup_fake_face():
+    """Clean up the temporary fake face image"""
+    try:
+        if modules.globals.fake_face_path and os.path.exists(modules.globals.fake_face_path):
+            os.remove(modules.globals.fake_face_path)
+            modules.globals.fake_face_path = None
+    except Exception as e:
+        print(f"Error cleaning up fake face: {str(e)}")
+
+def refresh_fake_face():
+    """Refresh the fake face image"""
+    cleanup_fake_face()
+    modules.globals.fake_face_path = get_fake_face()
+    return modules.globals.fake_face_path is not None 

modules/globals.py

@@ -21,7 +21,7 @@ keep_audio = True
 keep_frames = False
 many_faces = False
 map_faces = False
-color_correction = False  # New global variable for color correction toggle
+color_correction = False
 nsfw_filter = False
 video_encoder = None
 video_quality = None
@@ -41,3 +41,12 @@ show_mouth_mask_box = False
 mask_feather_ratio = 8
 mask_down_size = 0.50
 mask_size = 1
+mouth_mask_size = 1.0
+eyes_mask = False
+show_eyes_mask_box = False
+eyebrows_mask = False
+show_eyebrows_mask_box = False
+eyes_mask_size = 1.0
+eyebrows_mask_size = 1.0
+use_fake_face = False
+fake_face_path = None

modules/processors/frame/face_masking.py

@@ -0,0 +1,634 @@
+import cv2
+import numpy as np
+from modules.typing import Face, Frame
+import modules.globals
+
+def apply_color_transfer(source, target):
+    """
+    Apply color transfer from target to source image
+    """
+    source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
+    target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
+
+    source_mean, source_std = cv2.meanStdDev(source)
+    target_mean, target_std = cv2.meanStdDev(target)
+
+    # Reshape mean and std to be broadcastable
+    source_mean = source_mean.reshape(1, 1, 3)
+    source_std = source_std.reshape(1, 1, 3)
+    target_mean = target_mean.reshape(1, 1, 3)
+    target_std = target_std.reshape(1, 1, 3)
+
+    # Perform the color transfer
+    source = (source - source_mean) * (target_std / source_std) + target_mean
+
+    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)
+
+def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        # Convert landmarks to int32
+        landmarks = landmarks.astype(np.int32)
+
+        # Extract facial features
+        right_side_face = landmarks[0:16]
+        left_side_face = landmarks[17:32]
+        right_eye = landmarks[33:42]
+        right_eye_brow = landmarks[43:51]
+        left_eye = landmarks[87:96]
+        left_eye_brow = landmarks[97:105]
+
+        # Calculate forehead extension
+        right_eyebrow_top = np.min(right_eye_brow[:, 1])
+        left_eyebrow_top = np.min(left_eye_brow[:, 1])
+        eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
+
+        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%
+
+        # Create forehead points
+        forehead_left = right_side_face[0].copy()
+        forehead_right = left_side_face[-1].copy()
+        forehead_left[1] -= extended_forehead_height
+        forehead_right[1] -= extended_forehead_height
+
+        # Combine all points to create the face outline
+        face_outline = np.vstack(
+            [
+                [forehead_left],
+                right_side_face,
+                left_side_face[::-1],  # Reverse left side to create a continuous outline
+                [forehead_right],
+            ]
+        )
+
+        # Calculate padding
+        padding = int(
+            np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
+        )  # 5% of face width
+
+        # Create a slightly larger convex hull for padding
+        hull = cv2.convexHull(face_outline)
+        hull_padded = []
+        for point in hull:
+            x, y = point[0]
+            center = np.mean(face_outline, axis=0)
+            direction = np.array([x, y]) - center
+            direction = direction / np.linalg.norm(direction)
+            padded_point = np.array([x, y]) + direction * padding
+            hull_padded.append(padded_point)
+
+        hull_padded = np.array(hull_padded, dtype=np.int32)
+
+        # Fill the padded convex hull
+        cv2.fillConvexPoly(mask, hull_padded, 255)
+
+        # Smooth the mask edges
+        mask = cv2.GaussianBlur(mask, (5, 5), 3)
+
+    return mask
+
+def create_lower_mouth_mask(
+    face: Face, frame: Frame
+) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    mouth_cutout = None
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        #                  0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20
+        lower_lip_order = [
+            65,
+            66,
+            62,
+            70,
+            69,
+            18,
+            19,
+            20,
+            21,
+            22,
+            23,
+            24,
+            0,
+            8,
+            7,
+            6,
+            5,
+            4,
+            3,
+            2,
+            65,
+        ]
+        lower_lip_landmarks = landmarks[lower_lip_order].astype(
+            np.float32
+        )  # Use float for precise calculations
+
+        # Calculate the center of the landmarks
+        center = np.mean(lower_lip_landmarks, axis=0)
+
+        # Expand the landmarks outward using the mouth_mask_size
+        expansion_factor = (
+            1 + modules.globals.mask_down_size * modules.globals.mouth_mask_size
+        )  # Adjust expansion based on slider
+        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
+
+        # Extend the top lip part
+        toplip_indices = [
+            20,
+            0,
+            1,
+            2,
+            3,
+            4,
+            5,
+        ]  # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
+        toplip_extension = (
+            modules.globals.mask_size * modules.globals.mouth_mask_size * 0.5
+        )  # Adjust extension based on slider
+        for idx in toplip_indices:
+            direction = expanded_landmarks[idx] - center
+            direction = direction / np.linalg.norm(direction)
+            expanded_landmarks[idx] += direction * toplip_extension
+
+        # Extend the bottom part (chin area)
+        chin_indices = [
+            11,
+            12,
+            13,
+            14,
+            15,
+            16,
+        ]  # Indices for landmarks 21, 22, 23, 24, 0, 8
+        chin_extension = 2 * 0.2  # Adjust this factor to control the extension
+        for idx in chin_indices:
+            expanded_landmarks[idx][1] += (
+                expanded_landmarks[idx][1] - center[1]
+            ) * chin_extension
+
+        # Convert back to integer coordinates
+        expanded_landmarks = expanded_landmarks.astype(np.int32)
+
+        # Calculate bounding box for the expanded lower mouth
+        min_x, min_y = np.min(expanded_landmarks, axis=0)
+        max_x, max_y = np.max(expanded_landmarks, axis=0)
+
+        # Add some padding to the bounding box
+        padding = int((max_x - min_x) * 0.1)  # 10% padding
+        min_x = max(0, min_x - padding)
+        min_y = max(0, min_y - padding)
+        max_x = min(frame.shape[1], max_x + padding)
+        max_y = min(frame.shape[0], max_y + padding)
+
+        # Ensure the bounding box dimensions are valid
+        if max_x <= min_x or max_y <= min_y:
+            if (max_x - min_x) <= 1:
+                max_x = min_x + 1
+            if (max_y - min_y) <= 1:
+                max_y = min_y + 1
+
+        # Create the mask
+        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
+        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)
+
+        # Place the mask ROI in the full-sized mask
+        mask[min_y:max_y, min_x:max_x] = mask_roi
+
+        # Extract the masked area from the frame
+        mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
+
+        # Return the expanded lower lip polygon in original frame coordinates
+        lower_lip_polygon = expanded_landmarks
+
+    return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
+
+def create_eyes_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    eyes_cutout = None
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        # Left eye landmarks (87-96) and right eye landmarks (33-42)
+        left_eye = landmarks[87:96]
+        right_eye = landmarks[33:42]
+        
+        # Calculate centers and dimensions for each eye
+        left_eye_center = np.mean(left_eye, axis=0).astype(np.int32)
+        right_eye_center = np.mean(right_eye, axis=0).astype(np.int32)
+        
+        # Calculate eye dimensions with size adjustment
+        def get_eye_dimensions(eye_points):
+            x_coords = eye_points[:, 0]
+            y_coords = eye_points[:, 1]
+            width = int((np.max(x_coords) - np.min(x_coords)) * (1 + modules.globals.mask_down_size * modules.globals.eyes_mask_size))
+            height = int((np.max(y_coords) - np.min(y_coords)) * (1 + modules.globals.mask_down_size * modules.globals.eyes_mask_size))
+            return width, height
+        
+        left_width, left_height = get_eye_dimensions(left_eye)
+        right_width, right_height = get_eye_dimensions(right_eye)
+        
+        # Add extra padding
+        padding = int(max(left_width, right_width) * 0.2)
+        
+        # Calculate bounding box for both eyes
+        min_x = min(left_eye_center[0] - left_width//2, right_eye_center[0] - right_width//2) - padding
+        max_x = max(left_eye_center[0] + left_width//2, right_eye_center[0] + right_width//2) + padding
+        min_y = min(left_eye_center[1] - left_height//2, right_eye_center[1] - right_height//2) - padding
+        max_y = max(left_eye_center[1] + left_height//2, right_eye_center[1] + right_height//2) + padding
+        
+        # Ensure coordinates are within frame bounds
+        min_x = max(0, min_x)
+        min_y = max(0, min_y)
+        max_x = min(frame.shape[1], max_x)
+        max_y = min(frame.shape[0], max_y)
+        
+        # Create mask for the eyes region
+        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
+        
+        # Draw ellipses for both eyes
+        left_center = (left_eye_center[0] - min_x, left_eye_center[1] - min_y)
+        right_center = (right_eye_center[0] - min_x, right_eye_center[1] - min_y)
+        
+        # Calculate axes lengths (half of width and height)
+        left_axes = (left_width//2, left_height//2)
+        right_axes = (right_width//2, right_height//2)
+        
+        # Draw filled ellipses
+        cv2.ellipse(mask_roi, left_center, left_axes, 0, 0, 360, 255, -1)
+        cv2.ellipse(mask_roi, right_center, right_axes, 0, 0, 360, 255, -1)
+        
+        # Apply Gaussian blur to soften mask edges
+        mask_roi = cv2.GaussianBlur(mask_roi, (15, 15), 5)
+        
+        # Place the mask ROI in the full-sized mask
+        mask[min_y:max_y, min_x:max_x] = mask_roi
+        
+        # Extract the masked area from the frame
+        eyes_cutout = frame[min_y:max_y, min_x:max_x].copy()
+        
+        # Create polygon points for visualization
+        def create_ellipse_points(center, axes):
+            t = np.linspace(0, 2*np.pi, 32)
+            x = center[0] + axes[0] * np.cos(t)
+            y = center[1] + axes[1] * np.sin(t)
+            return np.column_stack((x, y)).astype(np.int32)
+        
+        # Generate points for both ellipses
+        left_points = create_ellipse_points((left_eye_center[0], left_eye_center[1]), (left_width//2, left_height//2))
+        right_points = create_ellipse_points((right_eye_center[0], right_eye_center[1]), (right_width//2, right_height//2))
+        
+        # Combine points for both eyes
+        eyes_polygon = np.vstack([left_points, right_points])
+        
+    return mask, eyes_cutout, (min_x, min_y, max_x, max_y), eyes_polygon
+
+def create_curved_eyebrow(points):
+    if len(points) >= 5:
+        # Sort points by x-coordinate
+        sorted_idx = np.argsort(points[:, 0])
+        sorted_points = points[sorted_idx]
+        
+        # Calculate dimensions
+        x_min, y_min = np.min(sorted_points, axis=0)
+        x_max, y_max = np.max(sorted_points, axis=0)
+        width = x_max - x_min
+        height = y_max - y_min
+        
+        # Create more points for smoother curve
+        num_points = 50
+        x = np.linspace(x_min, x_max, num_points)
+        
+        # Fit quadratic curve through points for more natural arch
+        coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 2)
+        y = np.polyval(coeffs, x)
+        
+        # Increased offsets to create more separation
+        top_offset = height * 0.5  # Increased from 0.3 to shift up more
+        bottom_offset = height * 0.2  # Increased from 0.1 to shift down more
+        
+        # Create smooth curves
+        top_curve = y - top_offset
+        bottom_curve = y + bottom_offset
+        
+        # Create curved endpoints with more pronounced taper
+        end_points = 5
+        start_x = np.linspace(x[0] - width * 0.15, x[0], end_points)  # Increased taper
+        end_x = np.linspace(x[-1], x[-1] + width * 0.15, end_points)  # Increased taper
+        
+        # Create tapered ends
+        start_curve = np.column_stack((
+            start_x,
+            np.linspace(bottom_curve[0], top_curve[0], end_points)
+        ))
+        end_curve = np.column_stack((
+            end_x,
+            np.linspace(bottom_curve[-1], top_curve[-1], end_points)
+        ))
+        
+        # Combine all points to form a smooth contour
+        contour_points = np.vstack([
+            start_curve,
+            np.column_stack((x, top_curve)),
+            end_curve,
+            np.column_stack((x[::-1], bottom_curve[::-1]))
+        ])
+        
+        # Add slight padding for better coverage
+        center = np.mean(contour_points, axis=0)
+        vectors = contour_points - center
+        padded_points = center + vectors * 1.2  # Increased padding slightly
+        
+        return padded_points
+    return points
+
+def create_eyebrows_mask(face: Face, frame: Frame) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
+    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
+    eyebrows_cutout = None
+    landmarks = face.landmark_2d_106
+    if landmarks is not None:
+        # Left eyebrow landmarks (97-105) and right eyebrow landmarks (43-51)
+        left_eyebrow = landmarks[97:105].astype(np.float32)
+        right_eyebrow = landmarks[43:51].astype(np.float32)
+        
+        # Calculate centers and dimensions for each eyebrow
+        left_center = np.mean(left_eyebrow, axis=0)
+        right_center = np.mean(right_eyebrow, axis=0)
+        
+        # Calculate bounding box with padding adjusted by size
+        all_points = np.vstack([left_eyebrow, right_eyebrow])
+        padding_factor = modules.globals.eyebrows_mask_size
+        min_x = np.min(all_points[:, 0]) - 25 * padding_factor
+        max_x = np.max(all_points[:, 0]) + 25 * padding_factor
+        min_y = np.min(all_points[:, 1]) - 20 * padding_factor
+        max_y = np.max(all_points[:, 1]) + 15 * padding_factor
+        
+        # Ensure coordinates are within frame bounds
+        min_x = max(0, int(min_x))
+        min_y = max(0, int(min_y))
+        max_x = min(frame.shape[1], int(max_x))
+        max_y = min(frame.shape[0], int(max_y))
+        
+        # Create mask for the eyebrows region
+        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
+        
+        try:
+            # Convert points to local coordinates
+            left_local = left_eyebrow - [min_x, min_y]
+            right_local = right_eyebrow - [min_x, min_y]
+            
+            def create_curved_eyebrow(points):
+                if len(points) >= 5:
+                    # Sort points by x-coordinate
+                    sorted_idx = np.argsort(points[:, 0])
+                    sorted_points = points[sorted_idx]
+                    
+                    # Calculate dimensions
+                    x_min, y_min = np.min(sorted_points, axis=0)
+                    x_max, y_max = np.max(sorted_points, axis=0)
+                    width = x_max - x_min
+                    height = y_max - y_min
+                    
+                    # Create more points for smoother curve
+                    num_points = 50
+                    x = np.linspace(x_min, x_max, num_points)
+                    
+                    # Fit quadratic curve through points for more natural arch
+                    coeffs = np.polyfit(sorted_points[:, 0], sorted_points[:, 1], 2)
+                    y = np.polyval(coeffs, x)
+                    
+                    # Increased offsets to create more separation
+                    top_offset = height * 0.5  # Increased from 0.3 to shift up more
+                    bottom_offset = height * 0.2  # Increased from 0.1 to shift down more
+                    
+                    # Create smooth curves
+                    top_curve = y - top_offset
+                    bottom_curve = y + bottom_offset
+                    
+                    # Create curved endpoints with more pronounced taper
+                    end_points = 5
+                    start_x = np.linspace(x[0] - width * 0.15, x[0], end_points)  # Increased taper
+                    end_x = np.linspace(x[-1], x[-1] + width * 0.15, end_points)  # Increased taper
+                    
+                    # Create tapered ends
+                    start_curve = np.column_stack((
+                        start_x,
+                        np.linspace(bottom_curve[0], top_curve[0], end_points)
+                    ))
+                    end_curve = np.column_stack((
+                        end_x,
+                        np.linspace(bottom_curve[-1], top_curve[-1], end_points)
+                    ))
+                    
+                    # Combine all points to form a smooth contour
+                    contour_points = np.vstack([
+                        start_curve,
+                        np.column_stack((x, top_curve)),
+                        end_curve,
+                        np.column_stack((x[::-1], bottom_curve[::-1]))
+                    ])
+                    
+                    # Add slight padding for better coverage
+                    center = np.mean(contour_points, axis=0)
+                    vectors = contour_points - center
+                    padded_points = center + vectors * 1.2  # Increased padding slightly
+                    
+                    return padded_points
+                return points
+            
+            # Generate and draw eyebrow shapes
+            left_shape = create_curved_eyebrow(left_local)
+            right_shape = create_curved_eyebrow(right_local)
+            
+            # Apply multi-stage blurring for natural feathering
+            # First, strong Gaussian blur for initial softening
+            mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
+            
+            # Second, medium blur for transition areas
+            mask_roi = cv2.GaussianBlur(mask_roi, (11, 11), 3)
+            
+            # Finally, light blur for fine details
+            mask_roi = cv2.GaussianBlur(mask_roi, (5, 5), 1)
+            
+            # Normalize mask values
+            mask_roi = cv2.normalize(mask_roi, None, 0, 255, cv2.NORM_MINMAX)
+            
+            # Place the mask ROI in the full-sized mask
+            mask[min_y:max_y, min_x:max_x] = mask_roi
+            
+            # Extract the masked area from the frame
+            eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
+            
+            # Combine points for visualization
+            eyebrows_polygon = np.vstack([
+                left_shape + [min_x, min_y],
+                right_shape + [min_x, min_y]
+            ]).astype(np.int32)
+            
+        except Exception as e:
+            # Fallback to simple polygons if curve fitting fails
+            left_local = left_eyebrow - [min_x, min_y]
+            right_local = right_eyebrow - [min_x, min_y]
+            cv2.fillPoly(mask_roi, [left_local.astype(np.int32)], 255)
+            cv2.fillPoly(mask_roi, [right_local.astype(np.int32)], 255)
+            mask_roi = cv2.GaussianBlur(mask_roi, (21, 21), 7)
+            mask[min_y:max_y, min_x:max_x] = mask_roi
+            eyebrows_cutout = frame[min_y:max_y, min_x:max_x].copy()
+            eyebrows_polygon = np.vstack([left_eyebrow, right_eyebrow]).astype(np.int32)
+        
+    return mask, eyebrows_cutout, (min_x, min_y, max_x, max_y), eyebrows_polygon
+
+def apply_mask_area(
+    frame: np.ndarray,
+    cutout: np.ndarray,
+    box: tuple,
+    face_mask: np.ndarray,
+    polygon: np.ndarray,
+) -> np.ndarray:
+    min_x, min_y, max_x, max_y = box
+    box_width = max_x - min_x
+    box_height = max_y - min_y
+
+    if (
+        cutout is None
+        or box_width is None
+        or box_height is None
+        or face_mask is None
+        or polygon is None
+    ):
+        return frame
+
+    try:
+        resized_cutout = cv2.resize(cutout, (box_width, box_height))
+        roi = frame[min_y:max_y, min_x:max_x]
+
+        if roi.shape != resized_cutout.shape:
+            resized_cutout = cv2.resize(
+                resized_cutout, (roi.shape[1], roi.shape[0])
+            )
+
+        color_corrected_area = apply_color_transfer(resized_cutout, roi)
+
+        # Create mask for the area
+        polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
+        
+        # Split points for left and right parts if needed
+        if len(polygon) > 50:  # Arbitrary threshold to detect if we have multiple parts
+            mid_point = len(polygon) // 2
+            left_points = polygon[:mid_point] - [min_x, min_y]
+            right_points = polygon[mid_point:] - [min_x, min_y]
+            cv2.fillPoly(polygon_mask, [left_points], 255)
+            cv2.fillPoly(polygon_mask, [right_points], 255)
+        else:
+            adjusted_polygon = polygon - [min_x, min_y]
+            cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
+
+        # Apply strong initial feathering
+        polygon_mask = cv2.GaussianBlur(polygon_mask, (21, 21), 7)
+
+        # Apply additional feathering
+        feather_amount = min(
+            30,
+            box_width // modules.globals.mask_feather_ratio,
+            box_height // modules.globals.mask_feather_ratio,
+        )
+        feathered_mask = cv2.GaussianBlur(
+            polygon_mask.astype(float), (0, 0), feather_amount
+        )
+        feathered_mask = feathered_mask / feathered_mask.max()
+
+        # Apply additional smoothing to the mask edges
+        feathered_mask = cv2.GaussianBlur(feathered_mask, (5, 5), 1)
+
+        face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
+        combined_mask = feathered_mask * (face_mask_roi / 255.0)
+
+        combined_mask = combined_mask[:, :, np.newaxis]
+        blended = (
+            color_corrected_area * combined_mask + roi * (1 - combined_mask)
+        ).astype(np.uint8)
+
+        # Apply face mask to blended result
+        face_mask_3channel = (
+            np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
+        )
+        final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
+
+        frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
+    except Exception as e:
+        pass
+
+    return frame
+
+def draw_mask_visualization(
+    frame: Frame,
+    mask_data: tuple,
+    label: str,
+    draw_method: str = "polygon"
+) -> Frame:
+    mask, cutout, (min_x, min_y, max_x, max_y), polygon = mask_data
+
+    vis_frame = frame.copy()
+
+    # Ensure coordinates are within frame bounds
+    height, width = vis_frame.shape[:2]
+    min_x, min_y = max(0, min_x), max(0, min_y)
+    max_x, max_y = min(width, max_x), min(height, max_y)
+
+    if draw_method == "ellipse" and len(polygon) > 50:  # For eyes
+        # Split points for left and right parts
+        mid_point = len(polygon) // 2
+        left_points = polygon[:mid_point]
+        right_points = polygon[mid_point:]
+        
+        try:
+            # Fit ellipses to points - need at least 5 points
+            if len(left_points) >= 5 and len(right_points) >= 5:
+                # Convert points to the correct format for ellipse fitting
+                left_points = left_points.astype(np.float32)
+                right_points = right_points.astype(np.float32)
+                
+                # Fit ellipses
+                left_ellipse = cv2.fitEllipse(left_points)
+                right_ellipse = cv2.fitEllipse(right_points)
+                
+                # Draw the ellipses
+                cv2.ellipse(vis_frame, left_ellipse, (0, 255, 0), 2)
+                cv2.ellipse(vis_frame, right_ellipse, (0, 255, 0), 2)
+        except Exception as e:
+            # If ellipse fitting fails, draw simple rectangles as fallback
+            left_rect = cv2.boundingRect(left_points)
+            right_rect = cv2.boundingRect(right_points)
+            cv2.rectangle(vis_frame, 
+                        (left_rect[0], left_rect[1]), 
+                        (left_rect[0] + left_rect[2], left_rect[1] + left_rect[3]), 
+                        (0, 255, 0), 2)
+            cv2.rectangle(vis_frame,
+                        (right_rect[0], right_rect[1]),
+                        (right_rect[0] + right_rect[2], right_rect[1] + right_rect[3]),
+                        (0, 255, 0), 2)
+    else:  # For mouth and eyebrows
+        # Draw the polygon
+        if len(polygon) > 50:  # If we have multiple parts
+            mid_point = len(polygon) // 2
+            left_points = polygon[:mid_point]
+            right_points = polygon[mid_point:]
+            cv2.polylines(vis_frame, [left_points], True, (0, 255, 0), 2, cv2.LINE_AA)
+            cv2.polylines(vis_frame, [right_points], True, (0, 255, 0), 2, cv2.LINE_AA)
+        else:
+            cv2.polylines(vis_frame, [polygon], True, (0, 255, 0), 2, cv2.LINE_AA)
+
+    # Add label
+    cv2.putText(
+        vis_frame,
+        label,
+        (min_x, min_y - 10),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.5,
+        (255, 255, 255),
+        1,
+    )
+
+    return vis_frame 

modules/processors/frame/face_swapper.py

@@ -14,6 +14,14 @@ from modules.utilities import (
     is_video,
 )
 from modules.cluster_analysis import find_closest_centroid
+from modules.processors.frame.face_masking import (
+    create_face_mask,
+    create_lower_mouth_mask,
+    create_eyes_mask,
+    create_eyebrows_mask,
+    apply_mask_area,
+    draw_mask_visualization
+)
 import os
 
 FACE_SWAPPER = None
@@ -74,24 +82,62 @@ def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
         temp_frame, target_face, source_face, paste_back=True
     )
 
-    if modules.globals.mouth_mask:
-        # Create a mask for the target face
+    # Create face mask for both mouth and eyes masking
     face_mask = create_face_mask(target_face, temp_frame)
 
-        # Create the mouth mask
-        mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon = (
-            create_lower_mouth_mask(target_face, temp_frame)
-        )
-
-        # Apply the mouth area
-        swapped_frame = apply_mouth_area(
-            swapped_frame, mouth_cutout, mouth_box, face_mask, lower_lip_polygon
+    if modules.globals.mouth_mask:
+        # Create and apply mouth mask
+        mouth_mask_data = create_lower_mouth_mask(target_face, temp_frame)
+        swapped_frame = apply_mask_area(
+            swapped_frame, 
+            mouth_mask_data[1],  # mouth_cutout
+            mouth_mask_data[2],  # mouth_box
+            face_mask, 
+            mouth_mask_data[3]   # mouth_polygon
         )
 
         if modules.globals.show_mouth_mask_box:
-            mouth_mask_data = (mouth_mask, mouth_cutout, mouth_box, lower_lip_polygon)
-            swapped_frame = draw_mouth_mask_visualization(
-                swapped_frame, target_face, mouth_mask_data
+            swapped_frame = draw_mask_visualization(
+                swapped_frame, 
+                mouth_mask_data,
+                "Lower Mouth Mask"
+            )
+
+    if modules.globals.eyes_mask:
+        # Create and apply eyes mask
+        eyes_mask_data = create_eyes_mask(target_face, temp_frame)
+        swapped_frame = apply_mask_area(
+            swapped_frame, 
+            eyes_mask_data[1],  # eyes_cutout
+            eyes_mask_data[2],  # eyes_box
+            face_mask, 
+            eyes_mask_data[3]   # eyes_polygon
+        )
+
+        if modules.globals.show_eyes_mask_box:
+            swapped_frame = draw_mask_visualization(
+                swapped_frame, 
+                eyes_mask_data,
+                "Eyes Mask",
+                draw_method="ellipse"
+            )
+
+    if modules.globals.eyebrows_mask:
+        # Create and apply eyebrows mask
+        eyebrows_mask_data = create_eyebrows_mask(target_face, temp_frame)
+        swapped_frame = apply_mask_area(
+            swapped_frame, 
+            eyebrows_mask_data[1],  # eyebrows_cutout
+            eyebrows_mask_data[2],  # eyebrows_box
+            face_mask, 
+            eyebrows_mask_data[3]   # eyebrows_polygon
+        )
+
+        if modules.globals.show_eyebrows_mask_box:
+            swapped_frame = draw_mask_visualization(
+                swapped_frame, 
+                eyebrows_mask_data,
+                "Eyebrows Mask"
             )
 
     return swapped_frame
@@ -255,361 +301,3 @@ def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
     modules.processors.frame.core.process_video(
         source_path, temp_frame_paths, process_frames
     )
-
-
-def create_lower_mouth_mask(
-    face: Face, frame: Frame
-) -> (np.ndarray, np.ndarray, tuple, np.ndarray):
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    mouth_cutout = None
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        #                  0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20
-        lower_lip_order = [
-            65,
-            66,
-            62,
-            70,
-            69,
-            18,
-            19,
-            20,
-            21,
-            22,
-            23,
-            24,
-            0,
-            8,
-            7,
-            6,
-            5,
-            4,
-            3,
-            2,
-            65,
-        ]
-        lower_lip_landmarks = landmarks[lower_lip_order].astype(
-            np.float32
-        )  # Use float for precise calculations
-
-        # Calculate the center of the landmarks
-        center = np.mean(lower_lip_landmarks, axis=0)
-
-        # Expand the landmarks outward
-        expansion_factor = (
-            1 + modules.globals.mask_down_size
-        )  # Adjust this for more or less expansion
-        expanded_landmarks = (lower_lip_landmarks - center) * expansion_factor + center
-
-        # Extend the top lip part
-        toplip_indices = [
-            20,
-            0,
-            1,
-            2,
-            3,
-            4,
-            5,
-        ]  # Indices for landmarks 2, 65, 66, 62, 70, 69, 18
-        toplip_extension = (
-            modules.globals.mask_size * 0.5
-        )  # Adjust this factor to control the extension
-        for idx in toplip_indices:
-            direction = expanded_landmarks[idx] - center
-            direction = direction / np.linalg.norm(direction)
-            expanded_landmarks[idx] += direction * toplip_extension
-
-        # Extend the bottom part (chin area)
-        chin_indices = [
-            11,
-            12,
-            13,
-            14,
-            15,
-            16,
-        ]  # Indices for landmarks 21, 22, 23, 24, 0, 8
-        chin_extension = 2 * 0.2  # Adjust this factor to control the extension
-        for idx in chin_indices:
-            expanded_landmarks[idx][1] += (
-                expanded_landmarks[idx][1] - center[1]
-            ) * chin_extension
-
-        # Convert back to integer coordinates
-        expanded_landmarks = expanded_landmarks.astype(np.int32)
-
-        # Calculate bounding box for the expanded lower mouth
-        min_x, min_y = np.min(expanded_landmarks, axis=0)
-        max_x, max_y = np.max(expanded_landmarks, axis=0)
-
-        # Add some padding to the bounding box
-        padding = int((max_x - min_x) * 0.1)  # 10% padding
-        min_x = max(0, min_x - padding)
-        min_y = max(0, min_y - padding)
-        max_x = min(frame.shape[1], max_x + padding)
-        max_y = min(frame.shape[0], max_y + padding)
-
-        # Ensure the bounding box dimensions are valid
-        if max_x <= min_x or max_y <= min_y:
-            if (max_x - min_x) <= 1:
-                max_x = min_x + 1
-            if (max_y - min_y) <= 1:
-                max_y = min_y + 1
-
-        # Create the mask
-        mask_roi = np.zeros((max_y - min_y, max_x - min_x), dtype=np.uint8)
-        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)
-
-        # Place the mask ROI in the full-sized mask
-        mask[min_y:max_y, min_x:max_x] = mask_roi
-
-        # Extract the masked area from the frame
-        mouth_cutout = frame[min_y:max_y, min_x:max_x].copy()
-
-        # Return the expanded lower lip polygon in original frame coordinates
-        lower_lip_polygon = expanded_landmarks
-
-    return mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon
-
-
-def draw_mouth_mask_visualization(
-    frame: Frame, face: Face, mouth_mask_data: tuple
-) -> Frame:
-    landmarks = face.landmark_2d_106
-    if landmarks is not None and mouth_mask_data is not None:
-        mask, mouth_cutout, (min_x, min_y, max_x, max_y), lower_lip_polygon = (
-            mouth_mask_data
-        )
-
-        vis_frame = frame.copy()
-
-        # Ensure coordinates are within frame bounds
-        height, width = vis_frame.shape[:2]
-        min_x, min_y = max(0, min_x), max(0, min_y)
-        max_x, max_y = min(width, max_x), min(height, max_y)
-
-        # Adjust mask to match the region size
-        mask_region = mask[0 : max_y - min_y, 0 : max_x - min_x]
-
-        # Remove the color mask overlay
-        # color_mask = cv2.applyColorMap((mask_region * 255).astype(np.uint8), cv2.COLORMAP_JET)
-
-        # Ensure shapes match before blending
-        vis_region = vis_frame[min_y:max_y, min_x:max_x]
-        # Remove blending with color_mask
-        # if vis_region.shape[:2] == color_mask.shape[:2]:
-        #     blended = cv2.addWeighted(vis_region, 0.7, color_mask, 0.3, 0)
-        #     vis_frame[min_y:max_y, min_x:max_x] = blended
-
-        # Draw the lower lip polygon
-        cv2.polylines(vis_frame, [lower_lip_polygon], True, (0, 255, 0), 2)
-
-        # Remove the red box
-        # cv2.rectangle(vis_frame, (min_x, min_y), (max_x, max_y), (0, 0, 255), 2)
-
-        # Visualize the feathered mask
-        feather_amount = max(
-            1,
-            min(
-                30,
-                (max_x - min_x) // modules.globals.mask_feather_ratio,
-                (max_y - min_y) // modules.globals.mask_feather_ratio,
-            ),
-        )
-        # Ensure kernel size is odd
-        kernel_size = 2 * feather_amount + 1
-        feathered_mask = cv2.GaussianBlur(
-            mask_region.astype(float), (kernel_size, kernel_size), 0
-        )
-        feathered_mask = (feathered_mask / feathered_mask.max() * 255).astype(np.uint8)
-        # Remove the feathered mask color overlay
-        # color_feathered_mask = cv2.applyColorMap(feathered_mask, cv2.COLORMAP_VIRIDIS)
-
-        # Ensure shapes match before blending feathered mask
-        # if vis_region.shape == color_feathered_mask.shape:
-        #     blended_feathered = cv2.addWeighted(vis_region, 0.7, color_feathered_mask, 0.3, 0)
-        #     vis_frame[min_y:max_y, min_x:max_x] = blended_feathered
-
-        # Add labels
-        cv2.putText(
-            vis_frame,
-            "Lower Mouth Mask",
-            (min_x, min_y - 10),
-            cv2.FONT_HERSHEY_SIMPLEX,
-            0.5,
-            (255, 255, 255),
-            1,
-        )
-        cv2.putText(
-            vis_frame,
-            "Feathered Mask",
-            (min_x, max_y + 20),
-            cv2.FONT_HERSHEY_SIMPLEX,
-            0.5,
-            (255, 255, 255),
-            1,
-        )
-
-        return vis_frame
-    return frame
-
-
-def apply_mouth_area(
-    frame: np.ndarray,
-    mouth_cutout: np.ndarray,
-    mouth_box: tuple,
-    face_mask: np.ndarray,
-    mouth_polygon: np.ndarray,
-) -> np.ndarray:
-    min_x, min_y, max_x, max_y = mouth_box
-    box_width = max_x - min_x
-    box_height = max_y - min_y
-
-    if (
-        mouth_cutout is None
-        or box_width is None
-        or box_height is None
-        or face_mask is None
-        or mouth_polygon is None
-    ):
-        return frame
-
-    try:
-        resized_mouth_cutout = cv2.resize(mouth_cutout, (box_width, box_height))
-        roi = frame[min_y:max_y, min_x:max_x]
-
-        if roi.shape != resized_mouth_cutout.shape:
-            resized_mouth_cutout = cv2.resize(
-                resized_mouth_cutout, (roi.shape[1], roi.shape[0])
-            )
-
-        color_corrected_mouth = apply_color_transfer(resized_mouth_cutout, roi)
-
-        # Use the provided mouth polygon to create the mask
-        polygon_mask = np.zeros(roi.shape[:2], dtype=np.uint8)
-        adjusted_polygon = mouth_polygon - [min_x, min_y]
-        cv2.fillPoly(polygon_mask, [adjusted_polygon], 255)
-
-        # Apply feathering to the polygon mask
-        feather_amount = min(
-            30,
-            box_width // modules.globals.mask_feather_ratio,
-            box_height // modules.globals.mask_feather_ratio,
-        )
-        feathered_mask = cv2.GaussianBlur(
-            polygon_mask.astype(float), (0, 0), feather_amount
-        )
-        feathered_mask = feathered_mask / feathered_mask.max()
-
-        face_mask_roi = face_mask[min_y:max_y, min_x:max_x]
-        combined_mask = feathered_mask * (face_mask_roi / 255.0)
-
-        combined_mask = combined_mask[:, :, np.newaxis]
-        blended = (
-            color_corrected_mouth * combined_mask + roi * (1 - combined_mask)
-        ).astype(np.uint8)
-
-        # Apply face mask to blended result
-        face_mask_3channel = (
-            np.repeat(face_mask_roi[:, :, np.newaxis], 3, axis=2) / 255.0
-        )
-        final_blend = blended * face_mask_3channel + roi * (1 - face_mask_3channel)
-
-        frame[min_y:max_y, min_x:max_x] = final_blend.astype(np.uint8)
-    except Exception as e:
-        pass
-
-    return frame
-
-
-def create_face_mask(face: Face, frame: Frame) -> np.ndarray:
-    mask = np.zeros(frame.shape[:2], dtype=np.uint8)
-    landmarks = face.landmark_2d_106
-    if landmarks is not None:
-        # Convert landmarks to int32
-        landmarks = landmarks.astype(np.int32)
-
-        # Extract facial features
-        right_side_face = landmarks[0:16]
-        left_side_face = landmarks[17:32]
-        right_eye = landmarks[33:42]
-        right_eye_brow = landmarks[43:51]
-        left_eye = landmarks[87:96]
-        left_eye_brow = landmarks[97:105]
-
-        # Calculate forehead extension
-        right_eyebrow_top = np.min(right_eye_brow[:, 1])
-        left_eyebrow_top = np.min(left_eye_brow[:, 1])
-        eyebrow_top = min(right_eyebrow_top, left_eyebrow_top)
-
-        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%
-
-        # Create forehead points
-        forehead_left = right_side_face[0].copy()
-        forehead_right = left_side_face[-1].copy()
-        forehead_left[1] -= extended_forehead_height
-        forehead_right[1] -= extended_forehead_height
-
-        # Combine all points to create the face outline
-        face_outline = np.vstack(
-            [
-                [forehead_left],
-                right_side_face,
-                left_side_face[
-                    ::-1
-                ],  # Reverse left side to create a continuous outline
-                [forehead_right],
-            ]
-        )
-
-        # Calculate padding
-        padding = int(
-            np.linalg.norm(right_side_face[0] - left_side_face[-1]) * 0.05
-        )  # 5% of face width
-
-        # Create a slightly larger convex hull for padding
-        hull = cv2.convexHull(face_outline)
-        hull_padded = []
-        for point in hull:
-            x, y = point[0]
-            center = np.mean(face_outline, axis=0)
-            direction = np.array([x, y]) - center
-            direction = direction / np.linalg.norm(direction)
-            padded_point = np.array([x, y]) + direction * padding
-            hull_padded.append(padded_point)
-
-        hull_padded = np.array(hull_padded, dtype=np.int32)
-
-        # Fill the padded convex hull
-        cv2.fillConvexPoly(mask, hull_padded, 255)
-
-        # Smooth the mask edges
-        mask = cv2.GaussianBlur(mask, (5, 5), 3)
-
-    return mask
-
-
-def apply_color_transfer(source, target):
-    """
-    Apply color transfer from target to source image
-    """
-    source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
-    target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
-
-    source_mean, source_std = cv2.meanStdDev(source)
-    target_mean, target_std = cv2.meanStdDev(target)
-
-    # Reshape mean and std to be broadcastable
-    source_mean = source_mean.reshape(1, 1, 3)
-    source_std = source_std.reshape(1, 1, 3)
-    target_mean = target_mean.reshape(1, 1, 3)
-    target_std = target_std.reshape(1, 1, 3)
-
-    # Perform the color transfer
-    source = (source - source_mean) * (target_std / source_std) + target_mean
-
-    return cv2.cvtColor(np.clip(source, 0, 255).astype("uint8"), cv2.COLOR_LAB2BGR)

modules/ui.py

@@ -3,7 +3,7 @@ import webbrowser
 import customtkinter as ctk
 from typing import Callable, Tuple
 import cv2
-from cv2_enumerate_cameras import enumerate_cameras  # Add this import
+from cv2_enumerate_cameras import enumerate_cameras
 from PIL import Image, ImageOps
 import time
 import json
@@ -28,6 +28,7 @@ from modules.utilities import (
 from modules.video_capture import VideoCapturer
 from modules.gettext import LanguageManager
 import platform
+from modules.fake_face_handler import cleanup_fake_face, refresh_fake_face
 
 if platform.system() == "Windows":
     from pygrabber.dshow_graph import FilterGraph
@@ -35,7 +36,7 @@ if platform.system() == "Windows":
 ROOT = None
 POPUP = None
 POPUP_LIVE = None
-ROOT_HEIGHT = 700
+ROOT_HEIGHT = 730
 ROOT_WIDTH = 600
 
 PREVIEW = None
@@ -78,9 +79,12 @@ target_label_dict_live = {}
 
 img_ft, vid_ft = modules.globals.file_types
 
+fake_face_switch = None
+fake_face_value = None
+
 
 def init(start: Callable[[], None], destroy: Callable[[], None], lang: str) -> ctk.CTk:
-    global ROOT, PREVIEW, _
+    global ROOT, PREVIEW, _, fake_face_switch, fake_face_value
 
     lang_manager = LanguageManager(lang)
     _ = lang_manager._
@@ -91,7 +95,8 @@ def init(start: Callable[[], None], destroy: Callable[[], None], lang: str) -> c
 
 
 def save_switch_states():
-    switch_states = {
+    try:
+        states = {
             "keep_fps": modules.globals.keep_fps,
             "keep_audio": modules.globals.keep_audio,
             "keep_frames": modules.globals.keep_frames,
@@ -105,37 +110,41 @@ def save_switch_states():
             "show_fps": modules.globals.show_fps,
             "mouth_mask": modules.globals.mouth_mask,
             "show_mouth_mask_box": modules.globals.show_mouth_mask_box,
+            "use_fake_face": modules.globals.use_fake_face
         }
-    with open("switch_states.json", "w") as f:
-        json.dump(switch_states, f)
+        with open(get_config_path(), 'w') as f:
+            json.dump(states, f)
+    except Exception as e:
+        print(f"Error saving switch states: {str(e)}")
 
 
 def load_switch_states():
     try:
-        with open("switch_states.json", "r") as f:
-            switch_states = json.load(f)
-        modules.globals.keep_fps = switch_states.get("keep_fps", True)
-        modules.globals.keep_audio = switch_states.get("keep_audio", True)
-        modules.globals.keep_frames = switch_states.get("keep_frames", False)
-        modules.globals.many_faces = switch_states.get("many_faces", False)
-        modules.globals.map_faces = switch_states.get("map_faces", False)
-        modules.globals.color_correction = switch_states.get("color_correction", False)
-        modules.globals.nsfw_filter = switch_states.get("nsfw_filter", False)
-        modules.globals.live_mirror = switch_states.get("live_mirror", False)
-        modules.globals.live_resizable = switch_states.get("live_resizable", False)
-        modules.globals.fp_ui = switch_states.get("fp_ui", {"face_enhancer": False})
-        modules.globals.show_fps = switch_states.get("show_fps", False)
-        modules.globals.mouth_mask = switch_states.get("mouth_mask", False)
-        modules.globals.show_mouth_mask_box = switch_states.get(
+        if os.path.exists(get_config_path()):
+            with open(get_config_path(), 'r') as f:
+                states = json.load(f)
+                modules.globals.keep_fps = states.get("keep_fps", True)
+                modules.globals.keep_audio = states.get("keep_audio", True)
+                modules.globals.keep_frames = states.get("keep_frames", False)
+                modules.globals.many_faces = states.get("many_faces", False)
+                modules.globals.map_faces = states.get("map_faces", False)
+                modules.globals.color_correction = states.get("color_correction", False)
+                modules.globals.nsfw_filter = states.get("nsfw_filter", False)
+                modules.globals.live_mirror = states.get("live_mirror", False)
+                modules.globals.live_resizable = states.get("live_resizable", False)
+                modules.globals.fp_ui = states.get("fp_ui", {"face_enhancer": False})
+                modules.globals.show_fps = states.get("show_fps", False)
+                modules.globals.mouth_mask = states.get("mouth_mask", False)
+                modules.globals.show_mouth_mask_box = states.get(
                     "show_mouth_mask_box", False
                 )
-    except FileNotFoundError:
-        # If the file doesn't exist, use default values
-        pass
+                modules.globals.use_fake_face = False
+    except Exception as e:
+        print(f"Error loading switch states: {str(e)}")
 
 
 def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global source_label, target_label, status_label, show_fps_switch
+    global source_label, target_label, status_label, show_fps_switch, fake_face_switch, fake_face_value
 
     load_switch_states()
 
@@ -151,21 +160,27 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
     root.configure()
     root.protocol("WM_DELETE_WINDOW", lambda: destroy())
     
+    # Add icon to the main window
+    icon_path = resolve_relative_path("deeplivecam.ico")
+    if os.path.exists(icon_path):
+        root.iconbitmap(icon_path)
+
+    # Image Selection Area (Top)
     source_label = ctk.CTkLabel(root, text=None)
-    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
+    source_label.place(relx=0.1, rely=0.05, relwidth=0.3, relheight=0.25)
 
     target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
+    target_label.place(relx=0.6, rely=0.05, relwidth=0.3, relheight=0.25)
 
     select_face_button = ctk.CTkButton(
         root, text=_("Select a face"), cursor="hand2", command=lambda: select_source_path()
     )
-    select_face_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)
+    select_face_button.place(relx=0.1, rely=0.35, relwidth=0.3, relheight=0.1)
 
     swap_faces_button = ctk.CTkButton(
         root, text="↔", cursor="hand2", command=lambda: swap_faces_paths()
     )
-    swap_faces_button.place(relx=0.45, rely=0.4, relwidth=0.1, relheight=0.1)
+    swap_faces_button.place(relx=0.45, rely=0.35, relwidth=0.1, relheight=0.1)
 
     select_target_button = ctk.CTkButton(
         root,
@@ -173,60 +188,30 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
         cursor="hand2",
         command=lambda: select_target_path(),
     )
-    select_target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)
+    select_target_button.place(relx=0.6, rely=0.35, relwidth=0.3, relheight=0.1)
 
-    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
-    keep_fps_checkbox = ctk.CTkSwitch(
+    # AI Generated Face controls
+    fake_face_value = ctk.BooleanVar(value=modules.globals.use_fake_face)
+    fake_face_switch = ctk.CTkSwitch(
         root,
-        text=_("Keep fps"),
-        variable=keep_fps_value,
+        text=_("Privacy Mode"),
+        variable=fake_face_value,
         cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "keep_fps", keep_fps_value.get()),
-            save_switch_states(),
-        ),
+        command=lambda: toggle_fake_face(fake_face_value)
     )
-    keep_fps_checkbox.place(relx=0.1, rely=0.6)
+    fake_face_switch.place(relx=0.1, rely=0.50)
 
-    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
-    keep_frames_switch = ctk.CTkSwitch(
+    # Add refresh button next to the switch
+    refresh_face_button = ctk.CTkButton(
         root,
-        text=_("Keep frames"),
-        variable=keep_frames_value,
+        text="↻",
+        width=30,
         cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "keep_frames", keep_frames_value.get()),
-            save_switch_states(),
-        ),
+        command=lambda: refresh_fake_face_clicked()
     )
-    keep_frames_switch.place(relx=0.1, rely=0.65)
-
-    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui["face_enhancer"])
-    enhancer_switch = ctk.CTkSwitch(
-        root,
-        text=_("Face Enhancer"),
-        variable=enhancer_value,
-        cursor="hand2",
-        command=lambda: (
-            update_tumbler("face_enhancer", enhancer_value.get()),
-            save_switch_states(),
-        ),
-    )
-    enhancer_switch.place(relx=0.1, rely=0.7)
-
-    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
-    keep_audio_switch = ctk.CTkSwitch(
-        root,
-        text=_("Keep audio"),
-        variable=keep_audio_value,
-        cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "keep_audio", keep_audio_value.get()),
-            save_switch_states(),
-        ),
-    )
-    keep_audio_switch.place(relx=0.6, rely=0.6)
+    refresh_face_button.place(relx=0.35, rely=0.50)
 
+    # Face Processing Options (Middle Left)
     many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
     many_faces_switch = ctk.CTkSwitch(
         root,
@@ -238,24 +223,7 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             save_switch_states(),
         ),
     )
-    many_faces_switch.place(relx=0.6, rely=0.65)
-
-    color_correction_value = ctk.BooleanVar(value=modules.globals.color_correction)
-    color_correction_switch = ctk.CTkSwitch(
-        root,
-        text=_("Fix Blueish Cam"),
-        variable=color_correction_value,
-        cursor="hand2",
-        command=lambda: (
-            setattr(modules.globals, "color_correction", color_correction_value.get()),
-            save_switch_states(),
-        ),
-    )
-    color_correction_switch.place(relx=0.6, rely=0.70)
-
-    #    nsfw_value = ctk.BooleanVar(value=modules.globals.nsfw_filter)
-    #    nsfw_switch = ctk.CTkSwitch(root, text='NSFW filter', variable=nsfw_value, cursor='hand2', command=lambda: setattr(modules.globals, 'nsfw_filter', nsfw_value.get()))
-    #    nsfw_switch.place(relx=0.6, rely=0.7)
+    many_faces_switch.place(relx=0.1, rely=0.55)
 
     map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
     map_faces_switch = ctk.CTkSwitch(
@@ -269,8 +237,35 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             close_mapper_window() if not map_faces.get() else None
         ),
     )
-    map_faces_switch.place(relx=0.1, rely=0.75)
+    map_faces_switch.place(relx=0.1, rely=0.60)
 
+    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui["face_enhancer"])
+    enhancer_switch = ctk.CTkSwitch(
+        root,
+        text=_("Face Enhancer"),
+        variable=enhancer_value,
+        cursor="hand2",
+        command=lambda: (
+            update_tumbler("face_enhancer", enhancer_value.get()),
+            save_switch_states(),
+        ),
+    )
+    enhancer_switch.place(relx=0.1, rely=0.65)
+
+    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
+    keep_audio_switch = ctk.CTkSwitch(
+        root,
+        text=_("Keep audio"),
+        variable=keep_audio_value,
+        cursor="hand2",
+        command=lambda: (
+            setattr(modules.globals, "keep_audio", keep_audio_value.get()),
+            save_switch_states(),
+        ),
+    )
+    keep_audio_switch.place(relx=0.1, rely=0.70)
+
+    # Add show FPS switch right after keep_audio_switch
     show_fps_value = ctk.BooleanVar(value=modules.globals.show_fps)
     show_fps_switch = ctk.CTkSwitch(
         root,
@@ -282,8 +277,9 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             save_switch_states(),
         ),
     )
-    show_fps_switch.place(relx=0.6, rely=0.75)
+    show_fps_switch.place(relx=0.1, rely=0.75)
 
+    # Mask Switches (Middle Right - Top Section)
     mouth_mask_var = ctk.BooleanVar(value=modules.globals.mouth_mask)
     mouth_mask_switch = ctk.CTkSwitch(
         root,
@@ -292,38 +288,117 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
         cursor="hand2",
         command=lambda: setattr(modules.globals, "mouth_mask", mouth_mask_var.get()),
     )
-    mouth_mask_switch.place(relx=0.1, rely=0.55)
+    mouth_mask_switch.place(relx=0.6, rely=0.50)
 
+    # Add mouth mask size slider
+    mouth_mask_size_slider = ctk.CTkSlider(
+        root,
+        from_=0.5,
+        to=2.0,
+        number_of_steps=30,
+        command=lambda value: setattr(modules.globals, "mouth_mask_size", value)
+    )
+    mouth_mask_size_slider.set(modules.globals.mouth_mask_size)
+    mouth_mask_size_slider.place(relx=0.8, rely=0.50, relwidth=0.1)
+
+    eyes_mask_var = ctk.BooleanVar(value=modules.globals.eyes_mask)
+    eyes_mask_switch = ctk.CTkSwitch(
+        root,
+        text=_("Eyes Mask"),
+        variable=eyes_mask_var,
+        cursor="hand2",
+        command=lambda: setattr(modules.globals, "eyes_mask", eyes_mask_var.get()),
+    )
+    eyes_mask_switch.place(relx=0.6, rely=0.55)
+
+    # Add eyes mask size slider
+    eyes_mask_size_slider = ctk.CTkSlider(
+        root,
+        from_=0.5,
+        to=2.0,
+        number_of_steps=30,
+        command=lambda value: setattr(modules.globals, "eyes_mask_size", value)
+    )
+    eyes_mask_size_slider.set(modules.globals.eyes_mask_size)
+    eyes_mask_size_slider.place(relx=0.8, rely=0.55, relwidth=0.1)
+
+    eyebrows_mask_var = ctk.BooleanVar(value=modules.globals.eyebrows_mask)
+    eyebrows_mask_switch = ctk.CTkSwitch(
+        root,
+        text=_("Eyebrows Mask"),
+        variable=eyebrows_mask_var,
+        cursor="hand2",
+        command=lambda: setattr(modules.globals, "eyebrows_mask", eyebrows_mask_var.get()),
+    )
+    eyebrows_mask_switch.place(relx=0.6, rely=0.60)
+
+    # Add eyebrows mask size slider
+    eyebrows_mask_size_slider = ctk.CTkSlider(
+        root,
+        from_=0.5,
+        to=2.0,
+        number_of_steps=30,
+        command=lambda value: setattr(modules.globals, "eyebrows_mask_size", value)
+    )
+    eyebrows_mask_size_slider.set(modules.globals.eyebrows_mask_size)
+    eyebrows_mask_size_slider.place(relx=0.8, rely=0.60, relwidth=0.1)
+
+    # Box Visualization Switches (Middle Right - Bottom Section)
     show_mouth_mask_box_var = ctk.BooleanVar(value=modules.globals.show_mouth_mask_box)
     show_mouth_mask_box_switch = ctk.CTkSwitch(
         root,
-        text=_("Show Mouth Mask Box"),
+        text=_("Show Mouth Box"),
         variable=show_mouth_mask_box_var,
         cursor="hand2",
         command=lambda: setattr(
             modules.globals, "show_mouth_mask_box", show_mouth_mask_box_var.get()
         ),
     )
-    show_mouth_mask_box_switch.place(relx=0.6, rely=0.55)
+    show_mouth_mask_box_switch.place(relx=0.6, rely=0.65)
 
+    show_eyes_mask_box_var = ctk.BooleanVar(value=modules.globals.show_eyes_mask_box)
+    show_eyes_mask_box_switch = ctk.CTkSwitch(
+        root,
+        text=_("Show Eyes Box"),
+        variable=show_eyes_mask_box_var,
+        cursor="hand2",
+        command=lambda: setattr(
+            modules.globals, "show_eyes_mask_box", show_eyes_mask_box_var.get()
+        ),
+    )
+    show_eyes_mask_box_switch.place(relx=0.6, rely=0.70)
+
+    show_eyebrows_mask_box_var = ctk.BooleanVar(value=modules.globals.show_eyebrows_mask_box)
+    show_eyebrows_mask_box_switch = ctk.CTkSwitch(
+        root,
+        text=_("Show Eyebrows Box"),
+        variable=show_eyebrows_mask_box_var,
+        cursor="hand2",
+        command=lambda: setattr(
+            modules.globals, "show_eyebrows_mask_box", show_eyebrows_mask_box_var.get()
+        ),
+    )
+    show_eyebrows_mask_box_switch.place(relx=0.6, rely=0.75)
+
+    # Main Control Buttons (Bottom)
     start_button = ctk.CTkButton(
         root, text=_("Start"), cursor="hand2", command=lambda: analyze_target(start, root)
     )
     start_button.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)
 
-    stop_button = ctk.CTkButton(
-        root, text=_("Destroy"), cursor="hand2", command=lambda: destroy()
-    )
-    stop_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)
-
     preview_button = ctk.CTkButton(
         root, text=_("Preview"), cursor="hand2", command=lambda: toggle_preview()
     )
-    preview_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+    preview_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)
 
-    # --- Camera Selection ---
+    stop_button = ctk.CTkButton(
+        root, text=_("Destroy"), cursor="hand2", command=lambda: destroy()
+    )
+    stop_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+
+    # Camera Section (Bottom)
     camera_label = ctk.CTkLabel(root, text=_("Select Camera:"))
-    camera_label.place(relx=0.1, rely=0.86, relwidth=0.2, relheight=0.05)
+    camera_label.place(relx=0.1, rely=0.87, relwidth=0.2, relheight=0.05)
 
     available_cameras = get_available_cameras()
     camera_indices, camera_names = available_cameras
@@ -342,7 +417,7 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             root, variable=camera_variable, values=camera_names
         )
 
-    camera_optionmenu.place(relx=0.35, rely=0.86, relwidth=0.25, relheight=0.05)
+    camera_optionmenu.place(relx=0.35, rely=0.87, relwidth=0.25, relheight=0.05)
 
     live_button = ctk.CTkButton(
         root,
@@ -362,16 +437,16 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             else "disabled"
         ),
     )
-    live_button.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
-    # --- End Camera Selection ---
+    live_button.place(relx=0.65, rely=0.87, relwidth=0.2, relheight=0.05)
 
+    # Status and Links (Bottom)
     status_label = ctk.CTkLabel(root, text=None, justify="center")
-    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)
+    status_label.place(relx=0.1, rely=0.92, relwidth=0.8)
 
     donate_label = ctk.CTkLabel(
         root, text="Deep Live Cam", justify="center", cursor="hand2"
     )
-    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
+    donate_label.place(relx=0.1, rely=0.94, relwidth=0.8)
     donate_label.configure(
         text_color=ctk.ThemeManager.theme.get("URL").get("text_color")
     )
@@ -545,6 +620,11 @@ def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
     preview.protocol("WM_DELETE_WINDOW", lambda: toggle_preview())
     preview.resizable(width=True, height=True)
     
+    # Add icon to the preview window
+    icon_path = resolve_relative_path("deeplivecam.ico")
+    if os.path.exists(icon_path):
+        preview.iconbitmap(icon_path)
+
     preview_label = ctk.CTkLabel(preview, text=None)
     preview_label.pack(fill="both", expand=True)
 
@@ -580,7 +660,7 @@ def update_tumbler(var: str, value: bool) -> None:
 
 
 def select_source_path() -> None:
-    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft
+    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft, fake_face_switch, fake_face_value
 
     PREVIEW.withdraw()
     source_path = ctk.filedialog.askopenfilename(
@@ -589,6 +669,10 @@ def select_source_path() -> None:
         filetypes=[img_ft],
     )
     if is_image(source_path):
+        modules.globals.use_fake_face = False
+        fake_face_value.set(False)
+        cleanup_fake_face()
+        
         modules.globals.source_path = source_path
         RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
         image = render_image_preview(modules.globals.source_path, (200, 200))
@@ -761,8 +845,7 @@ def update_preview(frame_number: int = 0) -> None:
                 modules.globals.frame_processors
         ):
             temp_frame = frame_processor.process_frame(
-                get_one_face(cv2.imread(modules.globals.source_path)), temp_frame
-            )
+                get_one_face(cv2.imread(modules.globals.source_path)), temp_frame)
         image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
         image = ImageOps.contain(
             image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS
@@ -1200,3 +1283,42 @@ def update_webcam_target(
         else:
             update_pop_live_status("Face could not be detected in last upload!")
         return map
+
+def toggle_fake_face(switch_var: ctk.BooleanVar) -> None:
+    modules.globals.use_fake_face = switch_var.get()
+    if modules.globals.use_fake_face:
+        if not modules.globals.fake_face_path:
+            if refresh_fake_face():
+                modules.globals.source_path = modules.globals.fake_face_path
+                # Update the source image preview
+                image = render_image_preview(modules.globals.source_path, (200, 200))
+                source_label.configure(image=image)
+    else:
+        cleanup_fake_face()
+        # Clear the source image preview
+        source_label.configure(image=None)
+        modules.globals.source_path = None
+
+def refresh_fake_face_clicked() -> None:
+    """Handle refresh button click to update fake face during live preview"""
+    if not modules.globals.use_fake_face:
+        # If privacy mode is off, turn it on first
+        modules.globals.use_fake_face = True
+        fake_face_value.set(True)
+        
+    if refresh_fake_face():
+        modules.globals.source_path = modules.globals.fake_face_path
+        # Update the source image preview
+        image = render_image_preview(modules.globals.source_path, (200, 200))
+        source_label.configure(image=image)
+        
+        # Force reload of frame processors to use new source face
+        global FRAME_PROCESSORS_MODULES
+        FRAME_PROCESSORS_MODULES = []
+        frame_processors = get_frame_processors_modules(modules.globals.frame_processors)
+
+def get_config_path() -> str:
+    """Get the path to the config file"""
+    config_dir = os.path.join(os.path.expanduser("~"), ".deep-live-cam")
+    os.makedirs(config_dir, exist_ok=True)
+    return os.path.join(config_dir, "switch_states.json")

requirements.txt

@@ -8,7 +8,7 @@ insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
 customtkinter==5.2.2
-pillow==9.5.0
+pillow==11.1.0
 torch==2.0.1+cu118; sys_platform != 'darwin'
 torch==2.0.1; sys_platform == 'darwin'
 torchvision==0.15.2+cu118; sys_platform != 'darwin'