Update requirements.txt

update requirements.txt

.python-version

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

README.md

@@ -31,25 +31,13 @@ By using this software, you agree to these terms and commit to using it in a man
 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
+## Features & Uses - Everything is in real-time
 
 ### Mouth Mask
 
@@ -85,7 +73,7 @@ Users are expected to use this software responsibly and legally. If using a real
 
 ### Memes
 
-**Create Your most viral meme yet**
+**Create Your Most Viral Meme Yet**
 
 <p align="center">
   <img src="media/meme.gif" alt="show" width="450"> 
@@ -93,6 +81,13 @@ Users are expected to use this software responsibly and legally. If using a real
   <sub>Created using Many Faces feature in Deep-Live-Cam</sub>
 </p>
 
+### Omegle
+
+**Surprise people on Omegle**
+
+<p align="center">
+  <video src="https://github.com/user-attachments/assets/2e9b9b82-fa04-4b70-9f56-b1f68e7672d0" width="450" controls></video>
+</p>
 
 ## Installation (Manual)
 
@@ -116,7 +111,8 @@ This is more likely to work on your computer but will be slower as it utilizes t
 **2. Clone the Repository**
 
 ```bash
-https://github.com/hacksider/Deep-Live-Cam.git
+git clone https://github.com/hacksider/Deep-Live-Cam.git
+cd Deep-Live-Cam
 ```
 
 **3. Download the Models**
@@ -130,14 +126,44 @@ Place these files in the "**models**" folder.
 
 We highly recommend using a `venv` to avoid issues.
 
+For Windows:
 ```bash
+python -m venv venv
+venv\Scripts\activate
 pip install -r requirements.txt
 ```
 
-**For macOS:** Install or upgrade the `python-tk` package:
+**For macOS:**
+
+Apple Silicon (M1/M2/M3) requires specific setup:
 
 ```bash
+# Install Python 3.10 (specific version is important)
+brew install python@3.10
+
+# Install tkinter package (required for the GUI)
 brew install python-tk@3.10
+
+# Create and activate virtual environment with Python 3.10
+python3.10 -m venv venv
+source venv/bin/activate
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+** In case something goes wrong and you need to reinstall the virtual environment **
+
+```bash
+# Deactivate the virtual environment
+rm -rf venv
+
+# Reinstall the virtual environment
+python -m venv venv
+source venv/bin/activate
+
+# install the dependencies again
+pip install -r requirements.txt
 ```
 
 **Run:** If you don't have a GPU, you can run Deep-Live-Cam using `python run.py`. Note that initial execution will download models (~300MB).
@@ -146,7 +172,7 @@ brew install python-tk@3.10
 
 **CUDA Execution Provider (Nvidia)**
 
-1. Install [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive) or [CUDA Toolkit 12.1.1](https://developer.nvidia.com/cuda-12-1-1-download-archive)
+1. Install [CUDA Toolkit 11.8.0](https://developer.nvidia.com/cuda-11-8-0-download-archive)
 2. Install dependencies:
 
 ```bash
@@ -162,19 +188,39 @@ python run.py --execution-provider cuda
 
 **CoreML Execution Provider (Apple Silicon)**
 
-1. Install dependencies:
+Apple Silicon (M1/M2/M3) specific installation:
+
+1. Make sure you've completed the macOS setup above using Python 3.10.
+2. Install dependencies:
 
 ```bash
 pip uninstall onnxruntime onnxruntime-silicon
 pip install onnxruntime-silicon==1.13.1
 ```
 
-2. Usage:
+3. Usage (important: specify Python 3.10):
 
 ```bash
-python run.py --execution-provider coreml
+python3.10 run.py --execution-provider coreml
 ```
 
+**Important Notes for macOS:**
+- You **must** use Python 3.10, not newer versions like 3.11 or 3.13
+- Always run with `python3.10` command not just `python` if you have multiple Python versions installed
+- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.10`
+- If you get model loading errors, check that your models are in the correct folder
+- If you encounter conflicts with other Python versions, consider uninstalling them:
+  ```bash
+  # List all installed Python versions
+  brew list | grep python
+  
+  # Uninstall conflicting versions if needed
+  brew uninstall --ignore-dependencies python@3.11 python@3.13
+  
+  # Keep only Python 3.10
+  brew cleanup
+  ```
+
 **CoreML Execution Provider (Apple Legacy)**
 
 1. Install dependencies:
@@ -219,7 +265,6 @@ pip install onnxruntime-openvino==1.15.0
 ```bash
 python run.py --execution-provider openvino
 ```
-
 </details>
 
 ## Usage
@@ -240,6 +285,19 @@ python run.py --execution-provider openvino
 -   Use a screen capture tool like OBS to stream.
 -   To change the face, select a new source image.
 
+## Tips and Tricks
+
+Check out these helpful guides to get the most out of Deep-Live-Cam:
+
+- [Unlocking the Secrets to the Perfect Deepfake Image](https://deeplivecam.net/index.php/blog/tips-and-tricks/unlocking-the-secrets-to-the-perfect-deepfake-image) - Learn how to create the best deepfake with full head coverage
+- [Video Call with DeepLiveCam](https://deeplivecam.net/index.php/blog/tips-and-tricks/video-call-with-deeplivecam) - Make your meetings livelier by using DeepLiveCam with OBS and meeting software
+- [Have a Special Guest!](https://deeplivecam.net/index.php/blog/tips-and-tricks/have-a-special-guest) - Tutorial on how to use face mapping to add special guests to your stream
+- [Watch Deepfake Movies in Realtime](https://deeplivecam.net/index.php/blog/tips-and-tricks/watch-deepfake-movies-in-realtime) - See yourself star in any video without processing the video
+- [Better Quality without Sacrificing Speed](https://deeplivecam.net/index.php/blog/tips-and-tricks/better-quality-without-sacrificing-speed) - Tips for achieving better results without impacting performance
+- [Instant Vtuber!](https://deeplivecam.net/index.php/blog/tips-and-tricks/instant-vtuber) - Create a new persona/vtuber easily using Metahuman Creator
+
+Visit our [official blog](https://deeplivecam.net/index.php/blog/tips-and-tricks) for more tips and tutorials.
+
 ## Command Line Arguments (Unmaintained)
 
 ```
@@ -313,5 +371,3 @@ 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

@@ -20,7 +20,6 @@ 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
@@ -36,7 +35,9 @@ 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)
@@ -64,9 +65,9 @@ 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 = True
-    modules.globals.keep_frames = True
+    modules.globals.keep_fps = args.keep_fps
     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
@@ -240,7 +241,6 @@ 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/face_analyser.py

@@ -39,13 +39,13 @@ def get_many_faces(frame: Frame) -> Any:
         return None
 
 def has_valid_map() -> bool:
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
         if "source" in map and "target" in map:
             return True
     return False
 
 def default_source_face() -> Any:
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
         if "source" in map:
             return map['source']['face']
     return None
@@ -53,7 +53,7 @@ def default_source_face() -> Any:
 def simplify_maps() -> Any:
     centroids = []
     faces = []
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
         if "source" in map and "target" in map:
             centroids.append(map['target']['face'].normed_embedding)
             faces.append(map['source']['face'])
@@ -64,10 +64,10 @@ def simplify_maps() -> Any:
 def add_blank_map() -> Any:
     try:
         max_id = -1
-        if len(modules.globals.souce_target_map) > 0:
-            max_id = max(modules.globals.souce_target_map, key=lambda x: x['id'])['id']
+        if len(modules.globals.source_target_map) > 0:
+            max_id = max(modules.globals.source_target_map, key=lambda x: x['id'])['id']
 
-        modules.globals.souce_target_map.append({
+        modules.globals.source_target_map.append({
                 'id' : max_id + 1
                 })
     except ValueError:
@@ -75,14 +75,14 @@ def add_blank_map() -> Any:
     
 def get_unique_faces_from_target_image() -> Any:
     try:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
         target_frame = cv2.imread(modules.globals.target_path)
         many_faces = get_many_faces(target_frame)
         i = 0
 
         for face in many_faces:
             x_min, y_min, x_max, y_max = face['bbox']
-            modules.globals.souce_target_map.append({
+            modules.globals.source_target_map.append({
                 'id' : i, 
                 'target' : {
                             'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
@@ -96,7 +96,7 @@ def get_unique_faces_from_target_image() -> Any:
     
 def get_unique_faces_from_target_video() -> Any:
     try:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
         frame_face_embeddings = []
         face_embeddings = []
     
@@ -127,7 +127,7 @@ def get_unique_faces_from_target_video() -> Any:
                 face['target_centroid'] = closest_centroid_index
 
         for i in range(len(centroids)):
-            modules.globals.souce_target_map.append({
+            modules.globals.source_target_map.append({
                 'id' : i
             })
 
@@ -135,7 +135,7 @@ def get_unique_faces_from_target_video() -> Any:
             for frame in tqdm(frame_face_embeddings, desc=f"Mapping frame embeddings to centroids-{i}"):
                 temp.append({'frame': frame['frame'], 'faces': [face for face in frame['faces'] if face['target_centroid'] == i], 'location': frame['location']})
 
-            modules.globals.souce_target_map[i]['target_faces_in_frame'] = temp
+            modules.globals.source_target_map[i]['target_faces_in_frame'] = temp
 
         # dump_faces(centroids, frame_face_embeddings)
         default_target_face()
@@ -144,7 +144,7 @@ def get_unique_faces_from_target_video() -> Any:
     
 
 def default_target_face():
-    for map in modules.globals.souce_target_map:
+    for map in modules.globals.source_target_map:
         best_face = None
         best_frame = None
         for frame in map['target_faces_in_frame']:

modules/fake_face_handler.py

@@ -1,120 +0,0 @@
-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

@@ -9,7 +9,7 @@ file_types = [
     ("Video", ("*.mp4", "*.mkv")),
 ]
 
-souce_target_map = []
+source_target_map = []
 simple_map = {}
 
 source_path = None
@@ -21,7 +21,7 @@ keep_audio = True
 keep_frames = False
 many_faces = False
 map_faces = False
-color_correction = False
+color_correction = False  # New global variable for color correction toggle
 nsfw_filter = False
 video_encoder = None
 video_quality = None
@@ -41,12 +41,3 @@ 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/metadata.py

@@ -1,3 +1,3 @@
 name = 'Deep-Live-Cam'
-version = '1.8'
+version = '1.9'
 edition = 'GitHub Edition'

modules/processors/frame/face_masking.py

@@ -1,634 +0,0 @@
-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

@@ -1,63 +1,44 @@
+import os # <-- Added for os.path.exists
 from typing import Any, List
 import cv2
 import insightface
 import threading
-import numpy as np
+
 import modules.globals
 import modules.processors.frame.core
+# Ensure update_status is imported if not already globally accessible
+# If it's part of modules.core, it might already be accessible via modules.core.update_status
 from modules.core import update_status
 from modules.face_analyser import get_one_face, get_many_faces, default_source_face
 from modules.typing import Face, Frame
-from modules.utilities import (
-    conditional_download,
-    is_image,
-    is_video,
-)
+from modules.utilities import conditional_download, resolve_relative_path, is_image, 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
 THREAD_LOCK = threading.Lock()
-NAME = "DLC.FACE-SWAPPER"
-
-abs_dir = os.path.dirname(os.path.abspath(__file__))
-models_dir = os.path.join(
-    os.path.dirname(os.path.dirname(os.path.dirname(abs_dir))), "models"
-)
+NAME = 'DLC.FACE-SWAPPER'
 
 
 def pre_check() -> bool:
-    download_directory_path = abs_dir
-    conditional_download(
-        download_directory_path,
-        [
-            "https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx"
-        ],
-    )
+    download_directory_path = resolve_relative_path('../models')
+    # Ensure both models are mentioned or downloaded if necessary
+    # Conditional download might need adjustment if you want it to fetch FP32 too
+    conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx'])
+    # Add a check or download for the FP32 model if you have a URL
+    # conditional_download(download_directory_path, ['URL_TO_FP32_MODEL_HERE'])
     return True
 
 
 def pre_start() -> bool:
+    # --- No changes needed in pre_start ---
     if not modules.globals.map_faces and not is_image(modules.globals.source_path):
-        update_status("Select an image for source path.", NAME)
+        update_status('Select an image for source path.', NAME)
         return False
-    elif not modules.globals.map_faces and not get_one_face(
-        cv2.imread(modules.globals.source_path)
-    ):
-        update_status("No face in source path detected.", NAME)
+    elif not modules.globals.map_faces and not get_one_face(cv2.imread(modules.globals.source_path)):
+        update_status('No face in source path detected.', NAME)
         return False
-    if not is_image(modules.globals.target_path) and not is_video(
-        modules.globals.target_path
-    ):
-        update_status("Select an image or video for target path.", NAME)
+    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
+        update_status('Select an image or video for target path.', NAME)
         return False
     return True
 
@@ -67,85 +48,57 @@ def get_face_swapper() -> Any:
 
     with THREAD_LOCK:
         if FACE_SWAPPER is None:
-            model_path = os.path.join(models_dir, "inswapper_128_fp16.onnx")
-            FACE_SWAPPER = insightface.model_zoo.get_model(
-                model_path, providers=modules.globals.execution_providers
-            )
+            # --- MODIFICATION START ---
+            # Define paths for both FP32 and FP16 models
+            model_dir = resolve_relative_path('../models')
+            model_path_fp32 = os.path.join(model_dir, 'inswapper_128.onnx')
+            model_path_fp16 = os.path.join(model_dir, 'inswapper_128_fp16.onnx')
+            chosen_model_path = None
+
+            # Prioritize FP32 model
+            if os.path.exists(model_path_fp32):
+                chosen_model_path = model_path_fp32
+                update_status(f"Loading FP32 model: {os.path.basename(chosen_model_path)}", NAME)
+            # Fallback to FP16 model
+            elif os.path.exists(model_path_fp16):
+                chosen_model_path = model_path_fp16
+                update_status(f"FP32 model not found. Loading FP16 model: {os.path.basename(chosen_model_path)}", NAME)
+            # Error if neither model is found
+            else:
+                error_message = f"Face Swapper model not found. Please ensure 'inswapper_128.onnx' (recommended) or 'inswapper_128_fp16.onnx' exists in the '{model_dir}' directory."
+                update_status(error_message, NAME)
+                raise FileNotFoundError(error_message)
+
+            # Load the chosen model
+            try:
+                FACE_SWAPPER = insightface.model_zoo.get_model(chosen_model_path, providers=modules.globals.execution_providers)
+            except Exception as e:
+                update_status(f"Error loading Face Swapper model {os.path.basename(chosen_model_path)}: {e}", NAME)
+                # Optionally, re-raise the exception or handle it more gracefully
+                raise e
+            # --- MODIFICATION END ---
     return FACE_SWAPPER
 
 
 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
-    )
-
-    # Create face mask for both mouth and eyes masking
-    face_mask = create_face_mask(target_face, temp_frame)
-
-    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:
-            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
+    # --- No changes needed in swap_face ---
+    swapper = get_face_swapper()
+    if swapper is None:
+         # Handle case where model failed to load
+         update_status("Face swapper model not loaded, skipping swap.", NAME)
+         return temp_frame
+    return swapper.get(temp_frame, target_face, source_face, paste_back=True)
 
 
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
-    if modules.globals.color_correction:
-        temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
+    # --- No changes needed in process_frame ---
+    # Ensure the frame is in RGB format if color correction is enabled
+    # Note: InsightFace swapper often expects BGR by default. Double-check if color issues appear.
+    # If color correction is needed *before* swapping and insightface needs BGR:
+    # original_was_bgr = True # Assume input is BGR
+    # if modules.globals.color_correction:
+    #     temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
+    #     original_was_bgr = False # Now it's RGB
 
     if modules.globals.many_faces:
         many_faces = get_many_faces(temp_frame)
@@ -156,53 +109,51 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
         target_face = get_one_face(temp_frame)
         if target_face:
             temp_frame = swap_face(source_face, target_face, temp_frame)
+
+    # Convert back if necessary (example, might not be needed depending on workflow)
+    # if modules.globals.color_correction and not original_was_bgr:
+    #      temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_RGB2BGR)
+
     return temp_frame
 
 
 def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
+    # --- No changes needed in process_frame_v2 ---
+    # (Assuming swap_face handles the potential None return from get_face_swapper)
     if is_image(modules.globals.target_path):
         if modules.globals.many_faces:
             source_face = default_source_face()
-            for map in modules.globals.souce_target_map:
-                target_face = map["target"]["face"]
+            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+                target_face = map_entry['target']['face']
                 temp_frame = swap_face(source_face, target_face, temp_frame)
 
         elif not modules.globals.many_faces:
-            for map in modules.globals.souce_target_map:
-                if "source" in map:
-                    source_face = map["source"]["face"]
-                    target_face = map["target"]["face"]
+            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+                if "source" in map_entry:
+                    source_face = map_entry['source']['face']
+                    target_face = map_entry['target']['face']
                     temp_frame = swap_face(source_face, target_face, temp_frame)
 
     elif is_video(modules.globals.target_path):
         if modules.globals.many_faces:
             source_face = default_source_face()
-            for map in modules.globals.souce_target_map:
-                target_frame = [
-                    f
-                    for f in map["target_faces_in_frame"]
-                    if f["location"] == temp_frame_path
-                ]
+            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+                target_frame = [f for f in map_entry['target_faces_in_frame'] if f['location'] == temp_frame_path]
 
                 for frame in target_frame:
-                    for target_face in frame["faces"]:
+                    for target_face in frame['faces']:
                         temp_frame = swap_face(source_face, target_face, temp_frame)
 
         elif not modules.globals.many_faces:
-            for map in modules.globals.souce_target_map:
-                if "source" in map:
-                    target_frame = [
-                        f
-                        for f in map["target_faces_in_frame"]
-                        if f["location"] == temp_frame_path
-                    ]
-                    source_face = map["source"]["face"]
+            for map_entry in modules.globals.souce_target_map: # Renamed 'map' to 'map_entry'
+                if "source" in map_entry:
+                    target_frame = [f for f in map_entry['target_faces_in_frame'] if f['location'] == temp_frame_path]
+                    source_face = map_entry['source']['face']
 
                     for frame in target_frame:
-                        for target_face in frame["faces"]:
+                        for target_face in frame['faces']:
                             temp_frame = swap_face(source_face, target_face, temp_frame)
-
-    else:
+    else: # Fallback for neither image nor video (e.g., live feed?)
         detected_faces = get_many_faces(temp_frame)
         if modules.globals.many_faces:
             if detected_faces:
@@ -211,93 +162,97 @@ def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
                     temp_frame = swap_face(source_face, target_face, temp_frame)
 
         elif not modules.globals.many_faces:
-            if detected_faces:
-                if len(detected_faces) <= len(
-                    modules.globals.simple_map["target_embeddings"]
-                ):
+            if detected_faces and hasattr(modules.globals, 'simple_map') and modules.globals.simple_map: # Check simple_map exists
+                if len(detected_faces) <= len(modules.globals.simple_map['target_embeddings']):
                     for detected_face in detected_faces:
-                        closest_centroid_index, _ = find_closest_centroid(
-                            modules.globals.simple_map["target_embeddings"],
-                            detected_face.normed_embedding,
-                        )
-
-                        temp_frame = swap_face(
-                            modules.globals.simple_map["source_faces"][
-                                closest_centroid_index
-                            ],
-                            detected_face,
-                            temp_frame,
-                        )
+                        closest_centroid_index, _ = find_closest_centroid(modules.globals.simple_map['target_embeddings'], detected_face.normed_embedding)
+                        temp_frame = swap_face(modules.globals.simple_map['source_faces'][closest_centroid_index], detected_face, temp_frame)
                 else:
-                    detected_faces_centroids = []
-                    for face in detected_faces:
-                        detected_faces_centroids.append(face.normed_embedding)
+                    detected_faces_centroids = [face.normed_embedding for face in detected_faces]
                     i = 0
-                    for target_embedding in modules.globals.simple_map[
-                        "target_embeddings"
-                    ]:
-                        closest_centroid_index, _ = find_closest_centroid(
-                            detected_faces_centroids, target_embedding
-                        )
-
-                        temp_frame = swap_face(
-                            modules.globals.simple_map["source_faces"][i],
-                            detected_faces[closest_centroid_index],
-                            temp_frame,
-                        )
+                    for target_embedding in modules.globals.simple_map['target_embeddings']:
+                        closest_centroid_index, _ = find_closest_centroid(detected_faces_centroids, target_embedding)
+                        # Ensure index is valid before accessing detected_faces
+                        if closest_centroid_index < len(detected_faces):
+                            temp_frame = swap_face(modules.globals.simple_map['source_faces'][i], detected_faces[closest_centroid_index], temp_frame)
                         i += 1
     return temp_frame
 
 
-def process_frames(
-    source_path: str, temp_frame_paths: List[str], progress: Any = None
-) -> None:
+def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+    # --- No changes needed in process_frames ---
+    # Note: Ensure get_one_face is called only once if possible for efficiency if !map_faces
+    source_face = None
     if not modules.globals.map_faces:
-        source_face = get_one_face(cv2.imread(source_path))
-        for temp_frame_path in temp_frame_paths:
-            temp_frame = cv2.imread(temp_frame_path)
-            try:
-                result = process_frame(source_face, temp_frame)
-                cv2.imwrite(temp_frame_path, result)
-            except Exception as exception:
-                print(exception)
-                pass
-            if progress:
-                progress.update(1)
-    else:
-        for temp_frame_path in temp_frame_paths:
-            temp_frame = cv2.imread(temp_frame_path)
-            try:
-                result = process_frame_v2(temp_frame, temp_frame_path)
-                cv2.imwrite(temp_frame_path, result)
-            except Exception as exception:
-                print(exception)
-                pass
+        source_img = cv2.imread(source_path)
+        if source_img is not None:
+            source_face = get_one_face(source_img)
+        if source_face is None:
+             update_status(f"Could not find face in source image: {source_path}, skipping swap.", NAME)
+             # If no source face, maybe skip processing? Or handle differently.
+             # For now, it will proceed but swap_face might fail later.
+
+    for temp_frame_path in temp_frame_paths:
+        temp_frame = cv2.imread(temp_frame_path)
+        if temp_frame is None:
+            update_status(f"Warning: Could not read frame {temp_frame_path}", NAME)
+            if progress: progress.update(1) # Still update progress even if frame fails
+            continue # Skip to next frame
+
+        try:
+            if not modules.globals.map_faces:
+                if source_face: # Only process if source face was found
+                    result = process_frame(source_face, temp_frame)
+                else:
+                    result = temp_frame # No source face, return original frame
+            else:
+                 result = process_frame_v2(temp_frame, temp_frame_path)
+
+            cv2.imwrite(temp_frame_path, result)
+        except Exception as exception:
+            update_status(f"Error processing frame {os.path.basename(temp_frame_path)}: {exception}", NAME)
+            # Decide whether to 'pass' (continue processing other frames) or raise
+            pass # Continue processing other frames
+        finally:
             if progress:
                 progress.update(1)
 
 
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
+    # --- No changes needed in process_image ---
+    # Note: Added checks for successful image reads and face detection
+    target_frame = cv2.imread(target_path) # Read original target for processing
+    if target_frame is None:
+        update_status(f"Error: Could not read target image: {target_path}", NAME)
+        return
+
     if not modules.globals.map_faces:
-        source_face = get_one_face(cv2.imread(source_path))
-        target_frame = cv2.imread(target_path)
+        source_img = cv2.imread(source_path)
+        if source_img is None:
+             update_status(f"Error: Could not read source image: {source_path}", NAME)
+             return
+        source_face = get_one_face(source_img)
+        if source_face is None:
+            update_status(f"Error: No face found in source image: {source_path}", NAME)
+            return
+
         result = process_frame(source_face, target_frame)
-        cv2.imwrite(output_path, result)
     else:
         if modules.globals.many_faces:
-            update_status(
-                "Many faces enabled. Using first source image. Progressing...", NAME
-            )
-        target_frame = cv2.imread(output_path)
-        result = process_frame_v2(target_frame)
-        cv2.imwrite(output_path, result)
+            update_status('Many faces enabled. Using first source image (if applicable in v2). Processing...', NAME)
+        # For process_frame_v2 on single image, it reads the 'output_path' which should be a copy
+        # Let's process the 'target_frame' we read instead.
+        result = process_frame_v2(target_frame) # Process the frame directly
+
+    # Write the final result to the output path
+    success = cv2.imwrite(output_path, result)
+    if not success:
+        update_status(f"Error: Failed to write output image to: {output_path}", NAME)
 
 
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    # --- No changes needed in process_video ---
     if modules.globals.map_faces and modules.globals.many_faces:
-        update_status(
-            "Many faces enabled. Using first source image. Progressing...", NAME
-        )
-    modules.processors.frame.core.process_video(
-        source_path, temp_frame_paths, process_frames
-    )
+        update_status('Many faces enabled. Using first source image (if applicable in v2). Processing...', NAME)
+    # The core processing logic is delegated, which is good.
+    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)

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
+from cv2_enumerate_cameras import enumerate_cameras  # Add this import
 from PIL import Image, ImageOps
 import time
 import json
@@ -28,7 +28,6 @@ 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
@@ -36,7 +35,7 @@ if platform.system() == "Windows":
 ROOT = None
 POPUP = None
 POPUP_LIVE = None
-ROOT_HEIGHT = 730
+ROOT_HEIGHT = 700
 ROOT_WIDTH = 600
 
 PREVIEW = None
@@ -79,12 +78,9 @@ 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, _, fake_face_switch, fake_face_value
+    global ROOT, PREVIEW, _
 
     lang_manager = LanguageManager(lang)
     _ = lang_manager._
@@ -95,56 +91,51 @@ def init(start: Callable[[], None], destroy: Callable[[], None], lang: str) -> c
 
 
 def save_switch_states():
-    try:
-        states = {
-            "keep_fps": modules.globals.keep_fps,
-            "keep_audio": modules.globals.keep_audio,
-            "keep_frames": modules.globals.keep_frames,
-            "many_faces": modules.globals.many_faces,
-            "map_faces": modules.globals.map_faces,
-            "color_correction": modules.globals.color_correction,
-            "nsfw_filter": modules.globals.nsfw_filter,
-            "live_mirror": modules.globals.live_mirror,
-            "live_resizable": modules.globals.live_resizable,
-            "fp_ui": modules.globals.fp_ui,
-            "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(get_config_path(), 'w') as f:
-            json.dump(states, f)
-    except Exception as e:
-        print(f"Error saving switch states: {str(e)}")
+    switch_states = {
+        "keep_fps": modules.globals.keep_fps,
+        "keep_audio": modules.globals.keep_audio,
+        "keep_frames": modules.globals.keep_frames,
+        "many_faces": modules.globals.many_faces,
+        "map_faces": modules.globals.map_faces,
+        "color_correction": modules.globals.color_correction,
+        "nsfw_filter": modules.globals.nsfw_filter,
+        "live_mirror": modules.globals.live_mirror,
+        "live_resizable": modules.globals.live_resizable,
+        "fp_ui": modules.globals.fp_ui,
+        "show_fps": modules.globals.show_fps,
+        "mouth_mask": modules.globals.mouth_mask,
+        "show_mouth_mask_box": modules.globals.show_mouth_mask_box,
+    }
+    with open("switch_states.json", "w") as f:
+        json.dump(switch_states, f)
 
 
 def load_switch_states():
     try:
-        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
-                )
-                modules.globals.use_fake_face = False
-    except Exception as e:
-        print(f"Error loading switch states: {str(e)}")
+        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(
+            "show_mouth_mask_box", False
+        )
+    except FileNotFoundError:
+        # If the file doesn't exist, use default values
+        pass
 
 
 def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
-    global source_label, target_label, status_label, show_fps_switch, fake_face_switch, fake_face_value
+    global source_label, target_label, status_label, show_fps_switch
 
     load_switch_states()
 
@@ -159,28 +150,22 @@ 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=0.05, relwidth=0.3, relheight=0.25)
+    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
 
     target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.05, relwidth=0.3, relheight=0.25)
+    target_label.place(relx=0.6, rely=0.1, 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=0.35, relwidth=0.3, relheight=0.1)
+    select_face_button.place(relx=0.1, rely=0.4, 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=0.35, relwidth=0.1, relheight=0.1)
+    swap_faces_button.place(relx=0.45, rely=0.4, relwidth=0.1, relheight=0.1)
 
     select_target_button = ctk.CTkButton(
         root,
@@ -188,30 +173,60 @@ 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=0.35, relwidth=0.3, relheight=0.1)
+    select_target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)
 
-    # AI Generated Face controls
-    fake_face_value = ctk.BooleanVar(value=modules.globals.use_fake_face)
-    fake_face_switch = ctk.CTkSwitch(
+    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
+    keep_fps_checkbox = ctk.CTkSwitch(
         root,
-        text=_("Privacy Mode"),
-        variable=fake_face_value,
+        text=_("Keep fps"),
+        variable=keep_fps_value,
         cursor="hand2",
-        command=lambda: toggle_fake_face(fake_face_value)
+        command=lambda: (
+            setattr(modules.globals, "keep_fps", keep_fps_value.get()),
+            save_switch_states(),
+        ),
     )
-    fake_face_switch.place(relx=0.1, rely=0.50)
+    keep_fps_checkbox.place(relx=0.1, rely=0.6)
 
-    # Add refresh button next to the switch
-    refresh_face_button = ctk.CTkButton(
+    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
+    keep_frames_switch = ctk.CTkSwitch(
         root,
-        text="↻",
-        width=30,
+        text=_("Keep frames"),
+        variable=keep_frames_value,
         cursor="hand2",
-        command=lambda: refresh_fake_face_clicked()
+        command=lambda: (
+            setattr(modules.globals, "keep_frames", keep_frames_value.get()),
+            save_switch_states(),
+        ),
     )
-    refresh_face_button.place(relx=0.35, rely=0.50)
+    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)
 
-    # Face Processing Options (Middle Left)
     many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
     many_faces_switch = ctk.CTkSwitch(
         root,
@@ -223,7 +238,24 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             save_switch_states(),
         ),
     )
-    many_faces_switch.place(relx=0.1, rely=0.55)
+    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)
 
     map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
     map_faces_switch = ctk.CTkSwitch(
@@ -237,35 +269,8 @@ 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=0.60)
+    map_faces_switch.place(relx=0.1, rely=0.75)
 
-    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,
@@ -277,9 +282,8 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             save_switch_states(),
         ),
     )
-    show_fps_switch.place(relx=0.1, rely=0.75)
+    show_fps_switch.place(relx=0.6, 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,
@@ -288,117 +292,38 @@ 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=0.6, rely=0.50)
+    mouth_mask_switch.place(relx=0.1, rely=0.55)
 
-    # 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 Box"),
+        text=_("Show Mouth Mask 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=0.65)
+    show_mouth_mask_box_switch.place(relx=0.6, rely=0.55)
 
-    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)
 
-    preview_button = ctk.CTkButton(
-        root, text=_("Preview"), cursor="hand2", command=lambda: toggle_preview()
-    )
-    preview_button.place(relx=0.4, 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=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+    stop_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)
 
-    # Camera Section (Bottom)
+    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)
+
+    # --- Camera Selection ---
     camera_label = ctk.CTkLabel(root, text=_("Select Camera:"))
-    camera_label.place(relx=0.1, rely=0.87, relwidth=0.2, relheight=0.05)
+    camera_label.place(relx=0.1, rely=0.86, relwidth=0.2, relheight=0.05)
 
     available_cameras = get_available_cameras()
     camera_indices, camera_names = available_cameras
@@ -417,7 +342,7 @@ 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=0.87, relwidth=0.25, relheight=0.05)
+    camera_optionmenu.place(relx=0.35, rely=0.86, relwidth=0.25, relheight=0.05)
 
     live_button = ctk.CTkButton(
         root,
@@ -437,16 +362,16 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
             else "disabled"
         ),
     )
-    live_button.place(relx=0.65, rely=0.87, relwidth=0.2, relheight=0.05)
+    live_button.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
+    # --- End Camera Selection ---
 
-    # Status and Links (Bottom)
     status_label = ctk.CTkLabel(root, text=None, justify="center")
-    status_label.place(relx=0.1, rely=0.92, relwidth=0.8)
+    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)
 
     donate_label = ctk.CTkLabel(
         root, text="Deep Live Cam", justify="center", cursor="hand2"
     )
-    donate_label.place(relx=0.1, rely=0.94, relwidth=0.8)
+    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
     donate_label.configure(
         text_color=ctk.ThemeManager.theme.get("URL").get("text_color")
     )
@@ -472,7 +397,7 @@ def analyze_target(start: Callable[[], None], root: ctk.CTk):
         return
 
     if modules.globals.map_faces:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
 
         if is_image(modules.globals.target_path):
             update_status("Getting unique faces")
@@ -481,8 +406,8 @@ def analyze_target(start: Callable[[], None], root: ctk.CTk):
             update_status("Getting unique faces")
             get_unique_faces_from_target_video()
 
-        if len(modules.globals.souce_target_map) > 0:
-            create_source_target_popup(start, root, modules.globals.souce_target_map)
+        if len(modules.globals.source_target_map) > 0:
+            create_source_target_popup(start, root, modules.globals.source_target_map)
         else:
             update_status("No faces found in target")
     else:
@@ -619,11 +544,6 @@ def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
     preview.configure()
     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)
@@ -660,7 +580,7 @@ def update_tumbler(var: str, value: bool) -> None:
 
 
 def select_source_path() -> None:
-    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft, fake_face_switch, fake_face_value
+    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft
 
     PREVIEW.withdraw()
     source_path = ctk.filedialog.askopenfilename(
@@ -669,10 +589,6 @@ 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))
@@ -780,17 +696,21 @@ def check_and_ignore_nsfw(target, destroy: Callable = None) -> bool:
 
 
 def fit_image_to_size(image, width: int, height: int):
-    if width is None and height is None:
+    if width is None or height is None or width <= 0 or height <= 0:
         return image
     h, w, _ = image.shape
     ratio_h = 0.0
     ratio_w = 0.0
-    if width > height:
-        ratio_h = height / h
-    else:
-        ratio_w = width / w
-    ratio = max(ratio_w, ratio_h)
-    new_size = (int(ratio * w), int(ratio * h))
+    ratio_w = width / w
+    ratio_h = height / h
+    # Use the smaller ratio to ensure the image fits within the given dimensions
+    ratio = min(ratio_w, ratio_h)
+    
+    # Compute new dimensions, ensuring they're at least 1 pixel
+    new_width = max(1, int(ratio * w))
+    new_height = max(1, int(ratio * h))
+    new_size = (new_width, new_height)
+
     return cv2.resize(image, dsize=new_size)
 
 
@@ -845,7 +765,8 @@ 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
@@ -870,9 +791,9 @@ def webcam_preview(root: ctk.CTk, camera_index: int):
             return
         create_webcam_preview(camera_index)
     else:
-        modules.globals.souce_target_map = []
+        modules.globals.source_target_map = []
         create_source_target_popup_for_webcam(
-            root, modules.globals.souce_target_map, camera_index
+            root, modules.globals.source_target_map, camera_index
         )
 
 
@@ -1283,42 +1204,3 @@ 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

@@ -1,21 +1,20 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-
 numpy>=1.23.5,<2
-opencv-python==4.10.0.84
-cv2_enumerate_cameras==1.1.15
-onnx==1.16.0
+typing-extensions>=4.8.0
+opencv-python==4.11.0.86
+onnx==1.17.0
+cv2_enumerate_cameras==1.1.18.3
 insightface==0.7.3
 psutil==5.9.8
 tk==0.1.0
 customtkinter==5.2.2
 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'
-torchvision==0.15.2; sys_platform == 'darwin'
+torch; sys_platform != 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torch; sys_platform == 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torchvision; sys_platform != 'darwin' --index-url https://download.pytorch.org/whl/cu126
+torchvision; sys_platform == 'darwin' --index-url https://download.pytorch.org/whl/cu126
 onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.16.3; sys_platform != 'darwin'
-tensorflow==2.12.1; sys_platform != 'darwin'
+onnxruntime-gpu==1.21; sys_platform != 'darwin'
+tensorflow; sys_platform != 'darwin'
 opennsfw2==0.10.2
 protobuf==4.23.2
 tqdm==4.66.4