Revert "Merge pull request #566 from pereiraroland26/main"

This reverts commit 5d450b4352.

.python-version

@@ -0,0 +1 @@
+3.10.14

README.md

@@ -24,7 +24,7 @@ Users of this software are expected to use this software responsibly while abidi
 #### 3. Download Models
 
  1. [GFPGANv1.4](https://huggingface.co/hacksider/deep-live-cam/resolve/main/GFPGANv1.4.pth)
- 2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx)
+ 2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx)
 
 Then put those 2 files on the "**models**" folder
 
@@ -142,30 +142,43 @@ Just follow the clicks on the screenshot
 Just use your favorite screencapture to stream like OBS
 > Note: In case you want to change your face, just select another picture, the preview mode will then restart (so just wait a bit).
 
+You can now use the virtual camera output (uses pyvirtualcam) by turning on the `Virtual Cam Output (OBS)` toggle which should output to the OBS Virtual Camera. Note: this may not work on macOS. You will get a preview as before, but now you will also have a virtual camera output which can be used in applications like Zoom.
 
 Additional command line arguments are given below. To learn out what they do, check [this guide](https://github.com/s0md3v/roop/wiki/Advanced-Options).
 
+
 ```
 options:
   -h, --help                                               show this help message and exit
   -s SOURCE_PATH, --source SOURCE_PATH                     select an source image
   -t TARGET_PATH, --target TARGET_PATH                     select an target image or video
   -o OUTPUT_PATH, --output OUTPUT_PATH                     select output file or directory
-  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, ...)
+  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, super_resolution...)
   --keep-fps                                               keep original fps
   --keep-audio                                             keep original audio
   --keep-frames                                            keep temporary frames
   --many-faces                                             process every face
   --video-encoder {libx264,libx265,libvpx-vp9}             adjust output video encoder
   --video-quality [0-51]                                   adjust output video quality
+  --live-mirror                                            the live camera display as you see it in the front-facing camera frame
+  --live-resizable                                         the live camera frame is resizable
   --max-memory MAX_MEMORY                                  maximum amount of RAM in GB
   --execution-provider {cpu} [{cpu} ...]                   available execution provider (choices: cpu, ...)
   --execution-threads EXECUTION_THREADS                    number of execution threads
+  --headless                                               run in headless mode
+  --enhancer-upscale-factor                                Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor
+  --source-image-scaling-factor                            Set the upscale factor for source images. Only applies if `face_swapper` is set as a frame-processor
+  -r SCALE, --super-resolution-scale-factor SCALE          Super resolution scale factor, choices are 2, 3, 4
   -v, --version                                            show program's version number and exit
 ```
 
 Looking for a CLI mode? Using the -s/--source argument will make the run program in cli mode.
 
+To improve the video quality, you can use the `super_resolution` frame processor after swapping the faces. It will enhance the video quality by 2x, 3x or 4x. You can set the upscale factor using the `-r` or `--super-resolution-scale-factor` argument. 
+Processing time will increase with the upscale factor, but it's quite quick.
+
+```
+
 ## Credits
 - [henryruhs](https://github.com/henryruhs): for being an irreplaceable contributor to the project
 - [ffmpeg](https://ffmpeg.org/): for making video related operations easy

modules/capturer.py

@@ -1,20 +1,38 @@
-from typing import Any
+from typing import Any, Optional
 import cv2
 
-
-def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
+def get_video_frame(video_path: str, frame_number: int = 0) -> Optional[Any]:
+    """Retrieve a specific frame from a video."""
     capture = cv2.VideoCapture(video_path)
-    frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
-    capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
+
+    if not capture.isOpened():
+        print(f"Error: Cannot open video file {video_path}")
+        return None
+
+    frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+
+    # Ensure frame_number is within the valid range
+    frame_number = max(0, min(frame_number, frame_total - 1))
+
+    capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
     has_frame, frame = capture.read()
     capture.release()
-    if has_frame:
-        return frame
-    return None
 
+    if not has_frame:
+        print(f"Error: Cannot read frame {frame_number} from {video_path}")
+        return None
+    
+    return frame
 
 def get_video_frame_total(video_path: str) -> int:
+    """Get the total number of frames in a video."""
     capture = cv2.VideoCapture(video_path)
-    video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+
+    if not capture.isOpened():
+        print(f"Error: Cannot open video file {video_path}")
+        return 0
+    
+    frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
     capture.release()
-    return video_frame_total
+
+    return frame_total

modules/core.py

@@ -1,16 +1,17 @@
 import os
 import sys
-# single thread doubles cuda performance - needs to be set before torch import
-if any(arg.startswith('--execution-provider') for arg in sys.argv):
-    os.environ['OMP_NUM_THREADS'] = '1'
-# reduce tensorflow log level
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 import warnings
-from typing import List
 import platform
 import signal
 import shutil
 import argparse
+from typing import List
+
+# Set environment variables for CUDA performance and TensorFlow logging
+if any(arg.startswith('--execution-provider') for arg in sys.argv):
+    os.environ['OMP_NUM_THREADS'] = '1'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
+
 import torch
 import onnxruntime
 import tensorflow
@@ -19,34 +20,73 @@ import modules.globals
 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
-
-if 'ROCMExecutionProvider' in modules.globals.execution_providers:
-    del torch
+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
+)
 
+# Filter warnings
 warnings.filterwarnings('ignore', category=FutureWarning, module='insightface')
 warnings.filterwarnings('ignore', category=UserWarning, module='torchvision')
 
+# Cross-platform resource management
+if platform.system() == 'Darwin' and 'ROCMExecutionProvider' in modules.globals.execution_providers:
+    del torch
+
 
 def parse_args() -> None:
     signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())
     program = argparse.ArgumentParser()
-    program.add_argument('-s', '--source', help='select an source image', dest='source_path')
-    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('--video-encoder', help='adjust output video encoder', dest='video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9'])
-    program.add_argument('--video-quality', help='adjust output video quality', dest='video_quality', type=int, default=18, choices=range(52), metavar='[0-51]')
-    program.add_argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory())
-    program.add_argument('--execution-provider', help='execution provider', dest='execution_provider', default=['cpu'], choices=suggest_execution_providers(), nargs='+')
-    program.add_argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=suggest_execution_threads())
-    program.add_argument('-v', '--version', action='version', version=f'{modules.metadata.name} {modules.metadata.version}')
+    program.add_argument('-s', '--source', help='Select a source image', dest='source_path')
+    program.add_argument('-t', '--target', help='Select a 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', 'super_resolution'],
+                         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('--video-encoder', help='Adjust output video encoder', dest='video_encoder', default='libx264',
+                         choices=['libx264', 'libx265', 'libvpx-vp9'])
+    program.add_argument('--video-quality', help='Adjust output video quality', dest='video_quality', type=int,
+                         default=18,
+                         choices=range(52), metavar='[0-51]')
+    program.add_argument('--live-mirror', help='The live camera display as you see it in the front-facing camera frame',
+                         dest='live_mirror', action='store_true', default=False)
+    program.add_argument('--live-resizable', help='The live camera frame is resizable',
+                         dest='live_resizable', action='store_true', default=False)
+    program.add_argument('--max-memory', help='Maximum amount of RAM in GB', dest='max_memory', type=int,
+                         default=suggest_max_memory())
+    program.add_argument('--execution-provider', help='Execution provider', dest='execution_provider', default=['cpu'],
+                         choices=suggest_execution_providers(), nargs='+')
+    program.add_argument('--execution-threads', help='Number of execution threads', dest='execution_threads', type=int,
+                         default=suggest_execution_threads())
+    program.add_argument('--headless', help='Run in headless mode', dest='headless', default=False, action='store_true')
+    program.add_argument('--enhancer-upscale-factor',
+                         help='Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor',
+                         dest='enhancer_upscale_factor', type=int, default=1)
+    program.add_argument('--source-image-scaling-factor', help='Set the upscale factor for source images',
+                         dest='source_image_scaling_factor', default=2, type=int)
+    program.add_argument('-r', '--super-resolution-scale-factor', dest='super_resolution_scale_factor',
+                         help='Set the upscale factor for super resolution', default=4, choices=[2, 3, 4], type=int)
+    program.add_argument('-v', '--version', action='version',
+                         version=f'{modules.metadata.name} {modules.metadata.version}')
 
-    # register deprecated args
+    # Register deprecated args
     program.add_argument('-f', '--face', help=argparse.SUPPRESS, dest='source_path_deprecated')
     program.add_argument('--cpu-cores', help=argparse.SUPPRESS, dest='cpu_cores_deprecated', type=int)
     program.add_argument('--gpu-vendor', help=argparse.SUPPRESS, dest='gpu_vendor_deprecated')
@@ -56,7 +96,8 @@ def parse_args() -> None:
 
     modules.globals.source_path = args.source_path
     modules.globals.target_path = args.target_path
-    modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path, args.output_path)
+    modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path,
+                                                        args.output_path)
     modules.globals.frame_processors = args.frame_processor
     modules.globals.headless = args.source_path or args.target_path or args.output_path
     modules.globals.keep_fps = args.keep_fps
@@ -65,23 +106,31 @@ def parse_args() -> None:
     modules.globals.many_faces = args.many_faces
     modules.globals.video_encoder = args.video_encoder
     modules.globals.video_quality = args.video_quality
+    modules.globals.live_mirror = args.live_mirror
+    modules.globals.live_resizable = args.live_resizable
     modules.globals.max_memory = args.max_memory
     modules.globals.execution_providers = decode_execution_providers(args.execution_provider)
     modules.globals.execution_threads = args.execution_threads
+    modules.globals.headless = args.headless
+    modules.globals.enhancer_upscale_factor = args.enhancer_upscale_factor
+    modules.globals.source_image_scaling_factor = args.source_image_scaling_factor
+    modules.globals.sr_scale_factor = args.super_resolution_scale_factor
+    # Handle face enhancer tumbler
+    modules.globals.fp_ui['face_enhancer'] = 'face_enhancer' in args.frame_processor
 
-    #for ENHANCER tumbler:
-    if 'face_enhancer' in args.frame_processor:
-        modules.globals.fp_ui['face_enhancer'] = True
-    else:
-        modules.globals.fp_ui['face_enhancer'] = False
-    
     modules.globals.nsfw = False
 
-    # translate deprecated args
+    # Handle deprecated arguments
+    handle_deprecated_args(args)
+
+
+def handle_deprecated_args(args) -> None:
+    """Handle deprecated arguments by translating them to the new format."""
     if args.source_path_deprecated:
         print('\033[33mArgument -f and --face are deprecated. Use -s and --source instead.\033[0m')
         modules.globals.source_path = args.source_path_deprecated
-        modules.globals.output_path = normalize_output_path(args.source_path_deprecated, modules.globals.target_path, args.output_path)
+        modules.globals.output_path = normalize_output_path(args.source_path_deprecated, modules.globals.target_path,
+                                                            args.output_path)
     if args.cpu_cores_deprecated:
         print('\033[33mArgument --cpu-cores is deprecated. Use --execution-threads instead.\033[0m')
         modules.globals.execution_threads = args.cpu_cores_deprecated
@@ -92,7 +141,7 @@ def parse_args() -> None:
         print('\033[33mArgument --gpu-vendor nvidia is deprecated. Use --execution-provider cuda instead.\033[0m')
         modules.globals.execution_providers = decode_execution_providers(['cuda'])
     if args.gpu_vendor_deprecated == 'amd':
-        print('\033[33mArgument --gpu-vendor amd is deprecated. Use --execution-provider cuda instead.\033[0m')
+        print('\033[33mArgument --gpu-vendor amd is deprecated. Use --execution-provider rocm instead.\033[0m')
         modules.globals.execution_providers = decode_execution_providers(['rocm'])
     if args.gpu_threads_deprecated:
         print('\033[33mArgument --gpu-threads is deprecated. Use --execution-threads instead.\033[0m')
@@ -100,18 +149,22 @@ def parse_args() -> None:
 
 
 def encode_execution_providers(execution_providers: List[str]) -> List[str]:
-    return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers]
+    return [provider.replace('ExecutionProvider', '').lower() for provider in execution_providers]
 
 
 def decode_execution_providers(execution_providers: List[str]) -> List[str]:
-    return [provider for provider, encoded_execution_provider in zip(onnxruntime.get_available_providers(), encode_execution_providers(onnxruntime.get_available_providers()))
-            if any(execution_provider in encoded_execution_provider for execution_provider in execution_providers)]
+    available_providers = onnxruntime.get_available_providers()
+    encoded_providers = encode_execution_providers(available_providers)
+
+    selected_providers = [available_providers[encoded_providers.index(req)] for req in execution_providers
+                          if req in encoded_providers]
+
+    # Default to CPU if no suitable providers are found
+    return selected_providers if selected_providers else ['CPUExecutionProvider']
 
 
 def suggest_max_memory() -> int:
-    if platform.system().lower() == 'darwin':
-        return 4
-    return 16
+    return 4 if platform.system().lower() == 'darwin' else 16
 
 
 def suggest_execution_providers() -> List[str]:
@@ -119,34 +172,43 @@ def suggest_execution_providers() -> List[str]:
 
 
 def suggest_execution_threads() -> int:
-    if 'DmlExecutionProvider' in modules.globals.execution_providers:
+    if 'dml' in modules.globals.execution_providers:
         return 1
-    if 'ROCMExecutionProvider' in modules.globals.execution_providers:
+    if 'rocm' in modules.globals.execution_providers:
         return 1
     return 8
 
 
 def limit_resources() -> None:
-    # prevent tensorflow memory leak
+    # Prevent TensorFlow memory leak
     gpus = tensorflow.config.experimental.list_physical_devices('GPU')
     for gpu in gpus:
         tensorflow.config.experimental.set_memory_growth(gpu, True)
-    # limit memory usage
+
+    # Limit memory usage
     if modules.globals.max_memory:
         memory = modules.globals.max_memory * 1024 ** 3
         if platform.system().lower() == 'darwin':
-            memory = modules.globals.max_memory * 1024 ** 6
-        if platform.system().lower() == 'windows':
+            memory = modules.globals.max_memory * 1024 ** 3
+        elif platform.system().lower() == 'windows':
             import ctypes
             kernel32 = ctypes.windll.kernel32
             kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory))
         else:
             import resource
-            resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))
+            try:
+                soft, hard = resource.getrlimit(resource.RLIMIT_DATA)
+                if memory > hard:
+                    print(
+                        f"Warning: Requested memory limit {memory / (1024 ** 3)} GB exceeds system's hard limit. Setting to maximum allowed {hard / (1024 ** 3)} GB.")
+                    memory = hard
+                resource.setrlimit(resource.RLIMIT_DATA, (memory, memory))
+            except ValueError as e:
+                print(f"Warning: Could not set memory limit: {e}. Continuing with default limits.")
 
 
 def release_resources() -> None:
-    if 'CUDAExecutionProvider' in modules.globals.execution_providers:
+    if 'cuda' in modules.globals.execution_providers:
         torch.cuda.empty_cache()
 
 
@@ -157,12 +219,15 @@ def pre_check() -> bool:
     if not shutil.which('ffmpeg'):
         update_status('ffmpeg is not installed.')
         return False
+    if 'cuda' in modules.globals.execution_providers and not torch.cuda.is_available():
+        update_status('CUDA is not available. Please check your GPU or CUDA installation.')
+        return False
     return True
 
 
 def update_status(message: str, scope: str = 'DLC.CORE') -> None:
     print(f'[{scope}] {message}')
-    if not modules.globals.headless:
+    if not modules.globals.headless and ui.status_label:
         ui.update_status(message)
 
 
@@ -170,37 +235,70 @@ def start() -> None:
     for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
         if not frame_processor.pre_start():
             return
-    # process image to image
+
+    # Process image to image
     if has_image_extension(modules.globals.target_path):
-        if modules.globals.nsfw == False:
-            from modules.predicter import predict_image
-            if predict_image(modules.globals.target_path):
-                destroy()
-        shutil.copy2(modules.globals.target_path, modules.globals.output_path)
-        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-            update_status('Progressing...', frame_processor.NAME)
-            frame_processor.process_image(modules.globals.source_path, modules.globals.output_path, modules.globals.output_path)
-            release_resources()
-        if is_image(modules.globals.target_path):
-            update_status('Processing to image succeed!')
-        else:
-            update_status('Processing to image failed!')
+        process_image_to_image()
         return
-    # process image to videos
-    if modules.globals.nsfw == False:
+
+    # Process image to video
+    process_image_to_video()
+
+
+def process_image_to_image() -> None:
+    if modules.globals.nsfw:
+        from modules.predicter import predict_image
+        if predict_image(modules.globals.target_path):
+            destroy(to_quit=False)
+            update_status('Processing to image ignored!')
+            return
+
+    try:
+        shutil.copy2(modules.globals.target_path, modules.globals.output_path)
+    except Exception as e:
+        print("Error copying file:", str(e))
+
+    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
+        update_status('Processing...', frame_processor.NAME)
+        frame_processor.process_image(modules.globals.source_path, modules.globals.output_path,
+                                      modules.globals.output_path)
+        release_resources()
+
+    if is_image(modules.globals.target_path):
+        update_status('Processing to image succeeded!')
+    else:
+        update_status('Processing to image failed!')
+
+
+def process_image_to_video() -> None:
+    if modules.globals.nsfw:
         from modules.predicter import predict_video
         if predict_video(modules.globals.target_path):
-            destroy()
-    update_status('Creating temp resources...')
+            destroy(to_quit=False)
+            update_status('Processing to video ignored!')
+            return
+
+    update_status('Creating temporary resources...')
     create_temp(modules.globals.target_path)
     update_status('Extracting frames...')
     extract_frames(modules.globals.target_path)
     temp_frame_paths = get_temp_frame_paths(modules.globals.target_path)
     for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-        update_status('Progressing...', frame_processor.NAME)
+        update_status('Processing...', frame_processor.NAME)
         frame_processor.process_video(modules.globals.source_path, temp_frame_paths)
         release_resources()
-    # handles fps
+
+    handle_video_fps()
+    handle_video_audio()
+    clean_temp(modules.globals.target_path)
+
+    if is_video(modules.globals.target_path):
+        update_status('Processing to video succeeded!')
+    else:
+        update_status('Processing to video failed!')
+
+
+def handle_video_fps() -> None:
     if modules.globals.keep_fps:
         update_status('Detecting fps...')
         fps = detect_fps(modules.globals.target_path)
@@ -209,7 +307,9 @@ def start() -> None:
     else:
         update_status('Creating video with 30.0 fps...')
         create_video(modules.globals.target_path)
-    # handle audio
+
+
+def handle_video_audio() -> None:
     if modules.globals.keep_audio:
         if modules.globals.keep_fps:
             update_status('Restoring audio...')
@@ -218,30 +318,29 @@ def start() -> None:
         restore_audio(modules.globals.target_path, modules.globals.output_path)
     else:
         move_temp(modules.globals.target_path, modules.globals.output_path)
-    # clean and validate
-    clean_temp(modules.globals.target_path)
-    if is_video(modules.globals.target_path):
-        update_status('Processing to video succeed!')
-    else:
-        update_status('Processing to video failed!')
 
 
-def destroy() -> None:
+def destroy(to_quit=True) -> None:
     if modules.globals.target_path:
         clean_temp(modules.globals.target_path)
-    quit()
+    if to_quit: quit()
 
 
 def run() -> None:
-    parse_args()
-    if not pre_check():
-        return
-    for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
-        if not frame_processor.pre_check():
+    try:
+        parse_args()
+        if not pre_check():
             return
-    limit_resources()
-    if modules.globals.headless:
-        start()
-    else:
-        window = ui.init(start, destroy)
-        window.mainloop()
+        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
+            if not frame_processor.pre_check():
+                return
+        limit_resources()
+        if modules.globals.headless:
+            start()
+        else:
+            window = ui.init(start, destroy)
+            window.mainloop()
+    except Exception as e:
+        print(f"UI initialization failed: {str(e)}")
+        update_status(f"UI initialization failed: {str(e)}")
+        destroy()  # Ensure any resources are cleaned up on failure

modules/face_analyser.py

@@ -1,31 +1,27 @@
-from typing import Any
+from typing import Any, Optional
 import insightface
 
 import modules.globals
 from modules.typing import Frame
 
-FACE_ANALYSER = None
+FACE_ANALYSER: Optional[insightface.app.FaceAnalysis] = None
 
-
-def get_face_analyser() -> Any:
+def get_face_analyser() -> insightface.app.FaceAnalysis:
     global FACE_ANALYSER
 
     if FACE_ANALYSER is None:
-        FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=modules.globals.execution_providers)
+        FACE_ANALYSER = insightface.app.FaceAnalysis(
+            name='buffalo_l', 
+            providers=modules.globals.execution_providers
+        )
         FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
+    
     return FACE_ANALYSER
 
+def get_one_face(frame: Frame) -> Optional[Any]:
+    faces = get_face_analyser().get(frame)
+    return min(faces, key=lambda x: x.bbox[0], default=None)
 
-def get_one_face(frame: Frame) -> Any:
-    face = get_face_analyser().get(frame)
-    try:
-        return min(face, key=lambda x: x.bbox[0])
-    except ValueError:
-        return None
-
-
-def get_many_faces(frame: Frame) -> Any:
-    try:
-        return get_face_analyser().get(frame)
-    except IndexError:
-        return None
+def get_many_faces(frame: Frame) -> Optional[Any]:
+    faces = get_face_analyser().get(frame)
+    return faces if faces else None

modules/globals.py

@@ -19,6 +19,8 @@ keep_frames = None
 many_faces = None
 video_encoder = None
 video_quality = None
+live_mirror = None
+live_resizable = None
 max_memory = None
 execution_providers: List[str] = []
 execution_threads = None
@@ -27,4 +29,7 @@ log_level = 'error'
 fp_ui: Dict[str, bool] = {}
 nsfw = None
 camera_input_combobox = None
-webcam_preview_running = False
+webcam_preview_running = False
+enhancer_upscale_factor = 1
+source_image_scaling_factor = 2
+sr_scale_factor = 4

modules/predicter.py

@@ -1,24 +1,25 @@
-import numpy
+import numpy as np
 import opennsfw2
 from PIL import Image
-
 from modules.typing import Frame
 
 MAX_PROBABILITY = 0.85
 
+# Preload the model once for efficiency
+model = None
 
 def predict_frame(target_frame: Frame) -> bool:
+    global model
+    if model is None: model = opennsfw2.make_open_nsfw_model()
     image = Image.fromarray(target_frame)
     image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
-    model = opennsfw2.make_open_nsfw_model()
-    views = numpy.expand_dims(image, axis=0)
+    views = np.expand_dims(image, axis=0)
     _, probability = model.predict(views)[0]
     return probability > MAX_PROBABILITY
 
-
 def predict_image(target_path: str) -> bool:
-    return opennsfw2.predict_image(target_path) > MAX_PROBABILITY
-
+    probability = opennsfw2.predict_image(target_path)
+    return probability > MAX_PROBABILITY
 
 def predict_video(target_path: str) -> bool:
     _, probabilities = opennsfw2.predict_video_frames(video_path=target_path, frame_interval=100)

modules/processors/frame/core.py

@@ -17,57 +17,56 @@ FRAME_PROCESSORS_INTERFACE = [
     'process_video'
 ]
 
-
-def load_frame_processor_module(frame_processor: str) -> Any:
+def load_frame_processor_module(frame_processor: str) -> ModuleType:
     try:
         frame_processor_module = importlib.import_module(f'modules.processors.frame.{frame_processor}')
+        # Ensure all required methods are present
         for method_name in FRAME_PROCESSORS_INTERFACE:
             if not hasattr(frame_processor_module, method_name):
-                sys.exit()
+                raise AttributeError(f"Missing required method {method_name} in {frame_processor} module.")
     except ImportError:
-        print(f"Frame processor {frame_processor} not found")
-        sys.exit()
+        print(f"Error: Frame processor '{frame_processor}' not found.")
+        sys.exit(1)
+    except AttributeError as e:
+        print(e)
+        sys.exit(1)
+    
     return frame_processor_module
 
-
 def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType]:
     global FRAME_PROCESSORS_MODULES
 
     if not FRAME_PROCESSORS_MODULES:
-        for frame_processor in frame_processors:
-            frame_processor_module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+        FRAME_PROCESSORS_MODULES = [load_frame_processor_module(fp) for fp in frame_processors]
+    
     set_frame_processors_modules_from_ui(frame_processors)
     return FRAME_PROCESSORS_MODULES
 
 def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
     global FRAME_PROCESSORS_MODULES
     for frame_processor, state in modules.globals.fp_ui.items():
-        if state == True and frame_processor not in frame_processors:
-            frame_processor_module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
+        if state and frame_processor not in frame_processors:
+            module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.append(module)
             modules.globals.frame_processors.append(frame_processor)
-        if state == False:
-            try:
-                frame_processor_module = load_frame_processor_module(frame_processor)
-                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
-                modules.globals.frame_processors.remove(frame_processor)
-            except:
-                pass
+        elif not state and frame_processor in frame_processors:
+            module = load_frame_processor_module(frame_processor)
+            FRAME_PROCESSORS_MODULES.remove(module)
+            modules.globals.frame_processors.remove(frame_processor)
 
 def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
     with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
-        futures = []
-        for path in temp_frame_paths:
-            future = executor.submit(process_frames, source_path, [path], progress)
-            futures.append(future)
+        futures = [executor.submit(process_frames, source_path, [path], progress) for path in temp_frame_paths]
         for future in futures:
             future.result()
 
-
-def process_video(source_path: str, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
+def process_video(source_path: str, frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
     progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
     total = len(frame_paths)
     with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
-        progress.set_postfix({'execution_providers': modules.globals.execution_providers, 'execution_threads': modules.globals.execution_threads, 'max_memory': modules.globals.max_memory})
+        progress.set_postfix({
+            'execution_providers': modules.globals.execution_providers, 
+            'execution_threads': modules.globals.execution_threads, 
+            'max_memory': modules.globals.max_memory
+        })
         multi_process_frame(source_path, frame_paths, process_frames, progress)

modules/processors/frame/face_enhancer.py

@@ -8,7 +8,7 @@ import modules.globals
 import modules.processors.frame.core
 from modules.core import update_status
 from modules.face_analyser import get_one_face
-from modules.typing import Frame, Face
+from modules.typing import Frame, Face  # Ensure these are imported
 from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
 
 FACE_ENHANCER = None
@@ -16,34 +16,29 @@ THREAD_SEMAPHORE = threading.Semaphore()
 THREAD_LOCK = threading.Lock()
 NAME = 'DLC.FACE-ENHANCER'
 
-
 def pre_check() -> bool:
     download_directory_path = resolve_relative_path('..\models')
     conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
     return True
 
-
 def pre_start() -> bool:
     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
 
-
 def get_face_enhancer() -> Any:
     global FACE_ENHANCER
 
     with THREAD_LOCK:
         if FACE_ENHANCER is None:
-            if os.name == 'nt':
-                model_path = resolve_relative_path('..\models\GFPGANv1.4.pth')
-                # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
-            else:
-                model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
-            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1) # type: ignore[attr-defined]
+            model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
+            FACE_ENHANCER = gfpgan.GFPGANer(
+                model_path=model_path,
+                upscale=modules.globals.enhancer_upscale_factor
+            )  # type: ignore[attr-defined]
     return FACE_ENHANCER
 
-
 def enhance_face(temp_frame: Frame) -> Frame:
     with THREAD_SEMAPHORE:
         _, _, temp_frame = get_face_enhancer().enhance(
@@ -52,14 +47,12 @@ def enhance_face(temp_frame: Frame) -> Frame:
         )
     return temp_frame
 
-
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
     target_face = get_one_face(temp_frame)
     if target_face:
         temp_frame = enhance_face(temp_frame)
     return temp_frame
 
-
 def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
     for temp_frame_path in temp_frame_paths:
         temp_frame = cv2.imread(temp_frame_path)
@@ -68,12 +61,10 @@ def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any
         if progress:
             progress.update(1)
 
-
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
     target_frame = cv2.imread(target_path)
     result = process_frame(None, target_frame)
     cv2.imwrite(output_path, result)
 
-
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
     modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

modules/processors/frame/face_swapper.py

@@ -2,6 +2,7 @@ from typing import Any, List
 import cv2
 import insightface
 import threading
+import os
 
 import modules.globals
 import modules.processors.frame.core
@@ -9,45 +10,59 @@ from modules.core import update_status
 from modules.face_analyser import get_one_face, get_many_faces
 from modules.typing import Face, Frame
 from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import numpy as np
 
 FACE_SWAPPER = None
 THREAD_LOCK = threading.Lock()
 NAME = 'DLC.FACE-SWAPPER'
 
-
 def pre_check() -> bool:
     download_directory_path = resolve_relative_path('../models')
-    conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx'])
+    conditional_download(download_directory_path, [
+        'https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128.onnx'
+    ])
     return True
 
-
 def pre_start() -> bool:
     if not is_image(modules.globals.source_path):
         update_status('Select an image for source path.', NAME)
         return False
     elif not get_one_face(cv2.imread(modules.globals.source_path)):
-        update_status('No face in source path detected.', NAME)
+        update_status('No face detected in the source path.', 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)
         return False
     return True
 
-
 def get_face_swapper() -> Any:
     global FACE_SWAPPER
 
     with THREAD_LOCK:
         if FACE_SWAPPER is None:
-            model_path = resolve_relative_path('../models/inswapper_128_fp16.onnx')
+            model_path = resolve_relative_path('../models/inswapper_128.onnx')
             FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers)
     return FACE_SWAPPER
 
+def upscale_image(image: np.ndarray, scaling_factor: int = modules.globals.source_image_scaling_factor) -> np.ndarray:
+    """
+    Upscales the given image by the specified scaling factor.
+
+    Args:
+        image (np.ndarray): The input image to upscale.
+        scaling_factor (int): The factor by which to upscale the image.
+
+    Returns:
+        np.ndarray: The upscaled image.
+    """
+    height, width = image.shape[:2]
+    new_size = (width * scaling_factor, height * scaling_factor)
+    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
+    return upscaled_image
 
 def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
     return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
 
-
 def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
     if modules.globals.many_faces:
         many_faces = get_many_faces(temp_frame)
@@ -60,27 +75,30 @@ def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
             temp_frame = swap_face(source_face, target_face, temp_frame)
     return temp_frame
 
-
 def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
-    source_face = get_one_face(cv2.imread(source_path))
+    source_image = cv2.imread(source_path)
+    if source_image is None:
+        print(f"Failed to load source image from {source_path}")
+        return
+    # Upscale the source image for better quality
+    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
+    source_face = get_one_face(source_image_upscaled)
+
     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
+            print(f"Error processing frame {temp_frame_path}: {exception}")
         if progress:
             progress.update(1)
 
-
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
     source_face = get_one_face(cv2.imread(source_path))
     target_frame = cv2.imread(target_path)
     result = process_frame(source_face, target_frame)
     cv2.imwrite(output_path, result)
 
-
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
     modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)

modules/processors/frame/super_resolution.py

@@ -0,0 +1,197 @@
+import threading
+import traceback
+from typing import Any, List
+import cv2
+
+import os
+
+import modules.globals
+import modules.processors.frame.core
+from modules.core import update_status
+from modules.face_analyser import get_one_face
+from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video
+import numpy as np
+
+NAME = 'DLC.SUPER-RESOLUTION'
+THREAD_SEMAPHORE = threading.Semaphore()
+
+# Singleton class for Super-Resolution
+class SuperResolutionModel:
+    _instance = None
+    _lock = threading.Lock()
+
+    def __init__(self, sr_model_path: str = f'ESPCN_x{modules.globals.sr_scale_factor}.pb'):
+        if SuperResolutionModel._instance is not None:
+            raise Exception("This class is a singleton!")
+        self.sr = cv2.dnn_superres.DnnSuperResImpl_create()
+        self.model_path = os.path.join(resolve_relative_path('../models'), sr_model_path)
+        if not os.path.exists(self.model_path):
+            raise FileNotFoundError(f"Super-resolution model not found at {self.model_path}")
+        try:
+            self.sr.readModel(self.model_path)
+            self.sr.setModel("espcn", modules.globals.sr_scale_factor)  # Using ESPCN with 2,3 or 4x upscaling
+        except Exception as e:
+            print(f"Error during super-resolution model initialization: {e}")
+            raise e
+
+    @classmethod
+    def get_instance(cls, sr_model_path: str = f'ESPCN_x{modules.globals.sr_scale_factor}.pb'):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:
+                    try:
+                        cls._instance = cls(sr_model_path)
+                    except Exception as e:
+                        raise RuntimeError(f"Failed to initialize SuperResolution: {str(e)}")
+        return cls._instance
+
+
+def pre_check() -> bool:
+    """
+    Checks and downloads necessary models before starting the face swapper.
+    """
+    download_directory_path = resolve_relative_path('../models')
+    # Download the super-resolution model as well
+    conditional_download(download_directory_path, [
+        f'https://huggingface.co/spaces/PabloGabrielSch/AI_Resolution_Upscaler_And_Resizer/resolve/bcd13b766a9499196e8becbe453c4a848673b3b6/models/ESPCN_x{modules.globals.sr_scale_factor}.pb'
+    ])
+    return True
+
+def pre_start() -> bool:
+    if not is_image(modules.globals.source_path):
+        update_status('Select an image for source path.', NAME)
+        return False
+    elif not get_one_face(cv2.imread(modules.globals.source_path)):
+        update_status('No face detected in the source path.', 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)
+        return False
+    return True
+
+
+def apply_super_resolution(image: np.ndarray) -> np.ndarray:
+    """
+    Applies super-resolution to the given image using the provided super-resolver.
+
+    Args:
+        image (np.ndarray): The input image to enhance.
+        sr_model_path (str): ESPCN model path for super-resolution.
+
+    Returns:
+        np.ndarray: The super-resolved image.
+    """
+    with THREAD_SEMAPHORE:
+        sr_model = SuperResolutionModel.get_instance()
+
+        if sr_model is None:
+            print("Super-resolution model is not initialized.")
+            return image
+        try:
+            upscaled_image = sr_model.sr.upsample(image)
+            return upscaled_image
+        except Exception as e:
+            print(f"Error during super-resolution: {e}")
+            return image
+
+
+def process_frame(frame: np.ndarray) -> np.ndarray:
+    """
+    Processes a single frame by swapping the source face into detected target faces.
+
+    Args:
+
+        frame (np.ndarray): The target frame image.
+
+    Returns:
+        np.ndarray: The processed frame with swapped faces.
+    """
+
+    # Apply super-resolution to the entire frame
+    frame = apply_super_resolution(frame)
+
+    return frame
+
+def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
+    """
+    Processes multiple frames by swapping the source face into each target frame.
+
+    Args:
+        source_path (str): Path to the source image.
+        temp_frame_paths (List[str]): List of paths to target frame images.
+        progress (Any, optional): Progress tracker. Defaults to None.
+    """
+    for idx, temp_frame_path in enumerate(temp_frame_paths):
+        frame = cv2.imread(temp_frame_path)
+        if frame is None:
+            print(f"Failed to load frame from {temp_frame_path}")
+            continue
+        try:
+            result = process_frame(frame)
+            cv2.imwrite(temp_frame_path, result)
+        except Exception as exception:
+            traceback.print_exc()
+            print(f"Error processing frame {temp_frame_path}: {exception}")
+        if progress:
+            progress.update(1)
+
+def upscale_image(image: np.ndarray, scaling_factor: int = 2) -> np.ndarray:
+    """
+    Upscales the given image by the specified scaling factor.
+
+    Args:
+        image (np.ndarray): The input image to upscale.
+        scaling_factor (int): The factor by which to upscale the image.
+
+    Returns:
+        np.ndarray: The upscaled image.
+    """
+    height, width = image.shape[:2]
+    new_size = (width * scaling_factor, height * scaling_factor)
+    upscaled_image = cv2.resize(image, new_size, interpolation=cv2.INTER_CUBIC)
+    return upscaled_image
+
+def process_image(source_path: str, target_path: str, output_path: str) -> None:
+    """
+    Processes a single image by swapping the source face into the target image.
+
+    Args:
+        source_path (str): Path to the source image.
+        target_path (str): Path to the target image.
+        output_path (str): Path to save the output image.
+    """
+    source_image = cv2.imread(source_path)
+    if source_image is None:
+        print(f"Failed to load source image from {source_path}")
+        return
+
+    # Upscale the source image for better quality before face detection
+    source_image_upscaled = upscale_image(source_image, scaling_factor=2)
+
+    # Detect source face from the upscaled image
+    source_face = get_one_face(source_image_upscaled)
+    if source_face is None:
+        print("No source face detected.")
+        return
+
+    target_frame = cv2.imread(target_path)
+    if target_frame is None:
+        print(f"Failed to load target image from {target_path}")
+        return
+
+    # Process the frame
+    result = process_frame(target_frame)
+
+    # Save the processed frame
+    cv2.imwrite(output_path, result)
+
+
+def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
+    """
+    Processes a video by swapping the source face into each frame.
+
+    Args:
+        source_path (str): Path to the source image.
+        temp_frame_paths (List[str]): List of paths to video frame images.
+    """
+    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

modules/ui.json

@@ -1,76 +1,57 @@
 {
   "CTk": {
-    "fg_color": ["gray95", "gray10"]
+    "fg_color": ["#FFFFFF", "#2D2D2D"]
   },
   "CTkToplevel": {
-    "fg_color": ["gray95", "gray10"]
+    "fg_color": ["#FFFFFF", "#2D2D2D"]
   },
   "CTkFrame": {
     "corner_radius": 0,
     "border_width": 0,
-    "fg_color": ["gray90", "gray13"],
-    "top_fg_color": ["gray85", "gray16"],
-    "border_color": ["gray65", "gray28"]
+    "fg_color": ["#F0F0F0", "#3C3C3C"],
+    "top_fg_color": ["#E0E0E0", "#4B4B4B"],
+    "border_color": ["#B0B0B0", "#5A5A5A"]
   },
   "CTkButton": {
     "corner_radius": 0,
     "border_width": 0,
-    "fg_color": ["#2aa666", "#1f538d"],
-    "hover_color": ["#3cb666", "#14375e"],
-    "border_color": ["#3e4a40", "#949A9F"],
-    "text_color": ["#f3faf6", "#f3faf6"],
+    "fg_color": ["#007ACC", "#007ACC"],
+    "hover_color": ["#005EA3", "#005EA3"],
+    "border_color": ["#004C8A", "#004C8A"],
+    "text_color": ["#FFFFFF", "#FFFFFF"],
     "text_color_disabled": ["gray74", "gray60"]
   },
   "CTkLabel": {
     "corner_radius": 0,
     "fg_color": "transparent",
-    "text_color": ["gray14", "gray84"]
+    "text_color": ["#000000", "#FFFFFF"]
   },
   "CTkEntry": {
     "corner_radius": 0,
     "border_width": 2,
-    "fg_color": ["#F9F9FA", "#343638"],
-    "border_color": ["#979DA2", "#565B5E"],
-    "text_color": ["gray14", "gray84"],
+    "fg_color": ["#FFFFFF", "#333333"],
+    "border_color": ["#A0A0A0", "#5A5A5A"],
+    "text_color": ["#000000", "#FFFFFF"],
     "placeholder_text_color": ["gray52", "gray62"]
   },
-  "CTkCheckbox": {
-    "corner_radius": 0,
-    "border_width": 3,
-    "fg_color": ["#2aa666", "#1f538d"],
-    "border_color": ["#3e4a40", "#949A9F"],
-    "hover_color": ["#3cb666", "#14375e"],
-    "checkmark_color": ["#f3faf6", "gray90"],
-    "text_color": ["gray14", "gray84"],
-    "text_color_disabled": ["gray60", "gray45"]
-  },
   "CTkSwitch": {
     "corner_radius": 1000,
     "border_width": 3,
     "button_length": 0,
     "fg_color": ["#939BA2", "#4A4D50"],
     "progress_color": ["#2aa666", "#1f538d"],
-    "button_color": ["gray36", "#D5D9DE"],
-    "button_hover_color": ["gray20", "gray100"],
-    "text_color": ["gray14", "gray84"],
+    "button_color": ["#444444", "#D5D9DE"],
+    "button_hover_color": ["#333333", "#FFFFFF"],
+    "text_color": ["#000000", "#FFFFFF"],
     "text_color_disabled": ["gray60", "gray45"]
   },
-  "CTkRadiobutton": {
-    "corner_radius": 1000,
-    "border_width_checked": 6,
-    "border_width_unchecked": 3,
+  "CTkOptionMenu": {
+    "corner_radius": 0,
     "fg_color": ["#2aa666", "#1f538d"],
-    "border_color": ["#3e4a40", "#949A9F"],
-    "hover_color": ["#3cb666", "#14375e"],
-    "text_color": ["gray14", "gray84"],
-    "text_color_disabled": ["gray60", "gray45"]
-  },
-  "CTkProgressBar": {
-    "corner_radius": 1000,
-    "border_width": 0,
-    "fg_color": ["#939BA2", "#4A4D50"],
-    "progress_color": ["#2aa666", "#1f538d"],
-    "border_color": ["gray", "gray"]
+    "button_color": ["#3cb666", "#14375e"],
+    "button_hover_color": ["#234567", "#1e2c40"],
+    "text_color": ["#FFFFFF", "#FFFFFF"],
+    "text_color_disabled": ["gray74", "gray60"]
   },
   "CTkSlider": {
     "corner_radius": 1000,
@@ -82,59 +63,6 @@
     "button_color": ["#2aa666", "#1f538d"],
     "button_hover_color": ["#3cb666", "#14375e"]
   },
-  "CTkOptionMenu": {
-    "corner_radius": 0,
-    "fg_color": ["#2aa666", "#1f538d"],
-    "button_color": ["#3cb666", "#14375e"],
-    "button_hover_color": ["#234567", "#1e2c40"],
-    "text_color": ["#f3faf6", "#f3faf6"],
-    "text_color_disabled": ["gray74", "gray60"]
-  },
-  "CTkComboBox": {
-    "corner_radius": 0,
-    "border_width": 2,
-    "fg_color": ["#F9F9FA", "#343638"],
-    "border_color": ["#979DA2", "#565B5E"],
-    "button_color": ["#979DA2", "#565B5E"],
-    "button_hover_color": ["#6E7174", "#7A848D"],
-    "text_color": ["gray14", "gray84"],
-    "text_color_disabled": ["gray50", "gray45"]
-  },
-  "CTkScrollbar": {
-    "corner_radius": 1000,
-    "border_spacing": 4,
-    "fg_color": "transparent",
-    "button_color": ["gray55", "gray41"],
-    "button_hover_color": ["gray40", "gray53"]
-  },
-  "CTkSegmentedButton": {
-    "corner_radius": 0,
-    "border_width": 2,
-    "fg_color": ["#979DA2", "gray29"],
-    "selected_color": ["#2aa666", "#1f538d"],
-    "selected_hover_color": ["#3cb666", "#14375e"],
-    "unselected_color": ["#979DA2", "gray29"],
-    "unselected_hover_color": ["gray70", "gray41"],
-    "text_color": ["#f3faf6", "#f3faf6"],
-    "text_color_disabled": ["gray74", "gray60"]
-  },
-  "CTkTextbox": {
-    "corner_radius": 0,
-    "border_width": 0,
-    "fg_color": ["gray100", "gray20"],
-    "border_color": ["#979DA2", "#565B5E"],
-    "text_color": ["gray14", "gray84"],
-    "scrollbar_button_color": ["gray55", "gray41"],
-    "scrollbar_button_hover_color": ["gray40", "gray53"]
-  },
-  "CTkScrollableFrame": {
-    "label_fg_color": ["gray80", "gray21"]
-  },
-  "DropdownMenu": {
-    "fg_color": ["gray90", "gray20"],
-    "hover_color": ["gray75", "gray28"],
-    "text_color": ["gray14", "gray84"]
-  },
   "CTkFont": {
     "macOS": {
       "family": "Avenir",
@@ -152,7 +80,12 @@
       "weight": "normal"
     }
   },
+  "DropdownMenu": {
+    "fg_color": ["#FFFFFF", "#2D2D2D"],
+    "hover_color": ["#E0E0E0", "#4B4B4B"],
+    "text_color": ["#000000", "#FFFFFF"]
+  },
   "URL": {
-    "text_color": ["gray74", "gray60"]
+    "text_color": ["#007ACC", "#1E90FF"]
   }
 }

modules/ui.py

@@ -1,9 +1,21 @@
 import os
+import platform
 import webbrowser
 import customtkinter as ctk
-from typing import Callable, Tuple
+from typing import Callable, Tuple, List, Any
+from types import ModuleType
 import cv2
 from PIL import Image, ImageOps
+import pyvirtualcam
+
+# Import OS-specific modules only when necessary
+if platform.system() == 'Darwin':  # macOS
+    import AVFoundation
+
+# Import Windows specific modules only when on windows platform
+if platform.system() == 'Windows' or platform.system() == 'Linux':  # Windows or Linux
+    from pygrabber.dshow_graph import FilterGraph
+
 
 import modules.globals
 import modules.metadata
@@ -13,12 +25,14 @@ from modules.processors.frame.core import get_frame_processors_modules
 from modules.utilities import is_image, is_video, resolve_relative_path
 
 ROOT = None
-ROOT_HEIGHT = 700
+ROOT_HEIGHT = 800
 ROOT_WIDTH = 600
 
 PREVIEW = None
 PREVIEW_MAX_HEIGHT = 700
-PREVIEW_MAX_WIDTH = 1200
+PREVIEW_MAX_WIDTH  = 1200
+PREVIEW_DEFAULT_WIDTH  = 960
+PREVIEW_DEFAULT_HEIGHT = 540
 
 RECENT_DIRECTORY_SOURCE = None
 RECENT_DIRECTORY_TARGET = None
@@ -32,10 +46,49 @@ status_label = None
 
 img_ft, vid_ft = modules.globals.file_types
 
+camera = None
+
+def check_camera_permissions():
+    """Check and request camera access permission on macOS."""
+    if platform.system() == 'Darwin':  # macOS-specific
+        auth_status = AVFoundation.AVCaptureDevice.authorizationStatusForMediaType_(AVFoundation.AVMediaTypeVideo)
+
+        if auth_status == AVFoundation.AVAuthorizationStatusNotDetermined:
+            # Request access to the camera
+            def completion_handler(granted):
+                if granted:
+                    print("Access granted to the camera.")
+                else:
+                    print("Access denied to the camera.")
+            
+            AVFoundation.AVCaptureDevice.requestAccessForMediaType_completionHandler_(AVFoundation.AVMediaTypeVideo, completion_handler)
+        elif auth_status == AVFoundation.AVAuthorizationStatusAuthorized:
+            print("Camera access already authorized.")
+        elif auth_status == AVFoundation.AVAuthorizationStatusDenied:
+            print("Camera access denied. Please enable it in System Preferences.")
+        elif auth_status == AVFoundation.AVAuthorizationStatusRestricted:
+            print("Camera access restricted. The app is not allowed to use the camera.")
+
+
+def select_camera(camera_name: str):
+    """Select the appropriate camera based on its name (cross-platform)."""
+    if platform.system() == 'Darwin':  # macOS-specific
+        devices = AVFoundation.AVCaptureDevice.devicesWithMediaType_(AVFoundation.AVMediaTypeVideo)
+        for device in devices:
+            if device.localizedName() == camera_name:
+                return device
+    elif platform.system() == 'Windows' or platform.system() == 'Linux':
+        # On Windows/Linux, simply return the camera name as OpenCV can handle it by index
+        return camera_name
+    return None
+
 
 def init(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
     global ROOT, PREVIEW
 
+    if platform.system() == 'Darwin':  # macOS-specific
+        check_camera_permissions()  # Check camera permissions before initializing the UI
+    
     ROOT = create_root(start, destroy)
     PREVIEW = create_preview(ROOT)
 
@@ -49,101 +102,102 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
     ctk.set_appearance_mode('system')
     ctk.set_default_color_theme(resolve_relative_path('ui.json'))
 
+    print("Creating root window...")
+    
     root = ctk.CTk()
     root.minsize(ROOT_WIDTH, ROOT_HEIGHT)
     root.title(f'{modules.metadata.name} {modules.metadata.version} {modules.metadata.edition}')
-    root.configure()
     root.protocol('WM_DELETE_WINDOW', lambda: destroy())
 
     source_label = ctk.CTkLabel(root, text=None)
-    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)
+    source_label.place(relx=0.1, rely=0.0875, relwidth=0.3, relheight=0.25)
 
     target_label = ctk.CTkLabel(root, text=None)
-    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)
+    target_label.place(relx=0.6, rely=0.0875, relwidth=0.3, relheight=0.25)
 
-    source_button = ctk.CTkButton(root, text='Select a face', cursor='hand2', command=lambda: select_source_path())
-    source_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)
+    source_button = ctk.CTkButton(root, text='Select a face', cursor='hand2', command=select_source_path)
+    source_button.place(relx=0.1, rely=0.35, relwidth=0.3, relheight=0.1)
 
-    target_button = ctk.CTkButton(root, text='Select a target', cursor='hand2', command=lambda: select_target_path())
-    target_button.place(relx=0.6, 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=0.4, relwidth=0.1, relheight=0.1)
+
+    target_button = ctk.CTkButton(root, text='Select a target', cursor='hand2', command=select_target_path)
+    target_button.place(relx=0.6, rely=0.35, relwidth=0.3, relheight=0.1)
 
     keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
     keep_fps_checkbox = ctk.CTkSwitch(root, text='Keep fps', variable=keep_fps_value, cursor='hand2', command=lambda: setattr(modules.globals, 'keep_fps', not modules.globals.keep_fps))
-    keep_fps_checkbox.place(relx=0.1, rely=0.6)
+    keep_fps_checkbox.place(relx=0.1, rely=0.525)
 
     keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
     keep_frames_switch = ctk.CTkSwitch(root, text='Keep frames', variable=keep_frames_value, cursor='hand2', command=lambda: setattr(modules.globals, 'keep_frames', keep_frames_value.get()))
-    keep_frames_switch.place(relx=0.1, rely=0.65)
+    keep_frames_switch.place(relx=0.1, rely=0.56875)
 
-    # for FRAME PROCESSOR ENHANCER tumbler:
     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()))
-    enhancer_switch.place(relx=0.1, rely=0.7)
+    enhancer_switch = ctk.CTkSwitch(root, text='Face Enhancer', variable=enhancer_value, cursor='hand2', command=lambda: update_tumbler('face_enhancer', enhancer_value.get()))
+    enhancer_switch.place(relx=0.1, rely=0.6125)
 
     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()))
-    keep_audio_switch.place(relx=0.6, rely=0.6)
+    keep_audio_switch.place(relx=0.6, rely=0.525)
 
     many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
     many_faces_switch = ctk.CTkSwitch(root, text='Many faces', variable=many_faces_value, cursor='hand2', command=lambda: setattr(modules.globals, 'many_faces', many_faces_value.get()))
-    many_faces_switch.place(relx=0.6, rely=0.65)
+    many_faces_switch.place(relx=0.6, rely=0.56875)
 
     nsfw_value = ctk.BooleanVar(value=modules.globals.nsfw)
     nsfw_switch = ctk.CTkSwitch(root, text='NSFW', variable=nsfw_value, cursor='hand2', command=lambda: setattr(modules.globals, 'nsfw', nsfw_value.get()))
-    nsfw_switch.place(relx=0.6, rely=0.7)
+    nsfw_switch.place(relx=0.6, rely=0.6125)
 
     start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: select_output_path(start))
-    start_button.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)
+    start_button.place(relx=0.15, rely=0.7, relwidth=0.2, relheight=0.05)
 
-    stop_button = ctk.CTkButton(root, text='Destroy', cursor='hand2', command=lambda: destroy())
-    stop_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)
+    stop_button = ctk.CTkButton(root, text='Destroy', cursor='hand2', command=destroy)
+    stop_button.place(relx=0.4, rely=0.7, relwidth=0.2, relheight=0.05)
 
-    preview_button = ctk.CTkButton(root, text='Preview', cursor='hand2', command=lambda: toggle_preview())
-    preview_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)
+    preview_button = ctk.CTkButton(root, text='Preview', cursor='hand2', command=toggle_preview)
+    preview_button.place(relx=0.65, rely=0.7, relwidth=0.2, relheight=0.05)
 
-    # --- Camera Selection ---
     camera_label = ctk.CTkLabel(root, text="Select Camera:")
-    camera_label.place(relx=0.4, rely=0.86, relwidth=0.2, relheight=0.05)
+    camera_label.place(relx=0.4, rely=0.7525, relwidth=0.2, relheight=0.05)
 
     available_cameras = get_available_cameras()
-
-    # Convert camera indices to strings for CTkOptionMenu
     available_camera_strings = [str(cam) for cam in available_cameras]
 
     camera_variable = ctk.StringVar(value=available_camera_strings[0] if available_camera_strings else "No cameras found")
-    camera_optionmenu = ctk.CTkOptionMenu(root, variable=camera_variable, 
-                                         values=available_camera_strings)
-    camera_optionmenu.place(relx=0.65, rely=0.86, relwidth=0.2, relheight=0.05)
+    camera_optionmenu = ctk.CTkOptionMenu(root, variable=camera_variable, values=available_camera_strings)
+    camera_optionmenu.place(relx=0.65, rely=0.7525, relwidth=0.2, relheight=0.05)
 
-    live_button = ctk.CTkButton(root, text='Live', cursor='hand2', command=lambda: webcam_preview(int(camera_variable.get())))
-    live_button.place(relx=0.15, rely=0.86, relwidth=0.2, relheight=0.05)
-    # --- End Camera Selection ---
+    virtual_cam_out_value = ctk.BooleanVar(value=False)
+    virtual_cam_out_switch = ctk.CTkSwitch(root, text='Virtual Cam Output (OBS)', variable=virtual_cam_out_value, cursor='hand2')
+    virtual_cam_out_switch.place(relx=0.4, rely=0.805)
+
+    live_button = ctk.CTkButton(root, text='Live', cursor='hand2', command=lambda: webcam_preview(camera_variable.get(), virtual_cam_out_value.get()))
+    live_button.place(relx=0.15, rely=0.7525, relwidth=0.2, relheight=0.05)
 
     status_label = ctk.CTkLabel(root, text=None, justify='center')
-    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)
+    status_label.place(relx=0.1, relwidth=0.8, rely=0.875)
 
     donate_label = ctk.CTkLabel(root, text='Deep Live Cam', justify='center', cursor='hand2')
     donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
     donate_label.configure(text_color=ctk.ThemeManager.theme.get('URL').get('text_color'))
-    donate_label.bind('<Button>', lambda event: webbrowser.open('https://paypal.me/hacksider'))
+    donate_label.bind('<Button-1>', lambda event: webbrowser.open('https://paypal.me/hacksider'))
 
     return root
 
 
-def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
+def create_preview(parent: ctk.CTk) -> ctk.CTkToplevel:
     global preview_label, preview_slider
 
     preview = ctk.CTkToplevel(parent)
     preview.withdraw()
     preview.title('Preview')
-    preview.configure()
-    preview.protocol('WM_DELETE_WINDOW', lambda: toggle_preview())
-    preview.resizable(width=False, height=False)
+    preview.protocol('WM_DELETE_WINDOW', toggle_preview)
+    preview.resizable(width=True, height=True)
 
     preview_label = ctk.CTkLabel(preview, text=None)
     preview_label.pack(fill='both', expand=True)
 
-    preview_slider = ctk.CTkSlider(preview, from_=0, to=0, command=lambda frame_value: update_preview(frame_value))
+    preview_slider = ctk.CTkSlider(preview, from_=0, to=0, command=update_preview)
 
     return preview
 
@@ -158,10 +212,10 @@ def update_tumbler(var: str, value: bool) -> None:
 
 
 def select_source_path() -> None:
-    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft
+    global RECENT_DIRECTORY_SOURCE
 
     PREVIEW.withdraw()
-    source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
+    source_path = ctk.filedialog.askopenfilename(title='Select a source image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
     if is_image(source_path):
         modules.globals.source_path = source_path
         RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
@@ -172,11 +226,35 @@ def select_source_path() -> None:
         source_label.configure(image=None)
 
 
-def select_target_path() -> None:
-    global RECENT_DIRECTORY_TARGET, img_ft, vid_ft
+def swap_faces_paths() -> None:
+    global RECENT_DIRECTORY_SOURCE, RECENT_DIRECTORY_TARGET
+
+    source_path = modules.globals.source_path
+    target_path = modules.globals.target_path
+
+    if not is_image(source_path) or not is_image(target_path):
+        return
+
+    modules.globals.source_path = target_path
+    modules.globals.target_path = source_path
+
+    RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
+    RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
 
     PREVIEW.withdraw()
-    target_path = ctk.filedialog.askopenfilename(title='select an target image or video', initialdir=RECENT_DIRECTORY_TARGET, filetypes=[img_ft, vid_ft])
+
+    source_image = render_image_preview(modules.globals.source_path, (200, 200))
+    source_label.configure(image=source_image)
+
+    target_image = render_image_preview(modules.globals.target_path, (200, 200))
+    target_label.configure(image=target_image)
+
+
+def select_target_path() -> None:
+    global RECENT_DIRECTORY_TARGET
+
+    PREVIEW.withdraw()
+    target_path = ctk.filedialog.askopenfilename(title='Select a target image or video', initialdir=RECENT_DIRECTORY_TARGET, filetypes=[img_ft, vid_ft])
     if is_image(target_path):
         modules.globals.target_path = target_path
         RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
@@ -193,12 +271,12 @@ def select_target_path() -> None:
 
 
 def select_output_path(start: Callable[[], None]) -> None:
-    global RECENT_DIRECTORY_OUTPUT, img_ft, vid_ft
+    global RECENT_DIRECTORY_OUTPUT
 
     if is_image(modules.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save image output file', filetypes=[img_ft], defaultextension='.png', initialfile='output.png', initialdir=RECENT_DIRECTORY_OUTPUT)
+        output_path = ctk.filedialog.asksaveasfilename(title='Save image output file', filetypes=[img_ft], defaultextension='.png', initialfile='output.png', initialdir=RECENT_DIRECTORY_OUTPUT)
     elif is_video(modules.globals.target_path):
-        output_path = ctk.filedialog.asksaveasfilename(title='save video output file', filetypes=[vid_ft], defaultextension='.mp4', initialfile='output.mp4', initialdir=RECENT_DIRECTORY_OUTPUT)
+        output_path = ctk.filedialog.asksaveasfilename(title='Save video output file', filetypes=[vid_ft], defaultextension='.mp4', initialfile='output.mp4', initialdir=RECENT_DIRECTORY_OUTPUT)
     else:
         output_path = None
     if output_path:
@@ -219,13 +297,13 @@ def render_video_preview(video_path: str, size: Tuple[int, int], frame_number: i
     if frame_number:
         capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
     has_frame, frame = capture.read()
+    capture.release()
     if has_frame:
         image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
         if size:
             image = ImageOps.fit(image, size, Image.LANCZOS)
         return ctk.CTkImage(image, size=image.size)
-    capture.release()
-    cv2.destroyAllWindows()
+    return None
 
 
 def toggle_preview() -> None:
@@ -235,12 +313,17 @@ def toggle_preview() -> None:
         init_preview()
         update_preview()
         PREVIEW.deiconify()
+    global camera
+    if PREVIEW.state() == 'withdrawn':
+        if camera and camera.isOpened():
+            camera.release()
+            camera = None
 
 
 def init_preview() -> None:
     if is_image(modules.globals.target_path):
         preview_slider.pack_forget()
-    if is_video(modules.globals.target_path):
+    elif is_video(modules.globals.target_path):
         video_frame_total = get_video_frame_total(modules.globals.target_path)
         preview_slider.configure(to=video_frame_total)
         preview_slider.pack(fill='x')
@@ -250,7 +333,7 @@ def init_preview() -> None:
 def update_preview(frame_number: int = 0) -> None:
     if modules.globals.source_path and modules.globals.target_path:
         temp_frame = get_video_frame(modules.globals.target_path, frame_number)
-        if modules.globals.nsfw == False:
+        if not modules.globals.nsfw:
             from modules.predicter import predict_frame
             if predict_frame(temp_frame):
                 quit()
@@ -264,62 +347,148 @@ def update_preview(frame_number: int = 0) -> None:
         image = ctk.CTkImage(image, size=image.size)
         preview_label.configure(image=image)
 
-def webcam_preview(camera_index: int):
+def webcam_preview_loop(camera: cv2.VideoCapture, source_image: Any, frame_processors: List[ModuleType], virtual_cam: pyvirtualcam.Camera = None) -> bool:
+    global preview_label, PREVIEW
+
+    ret, frame = camera.read()
+    if not ret:
+        update_status(f"Error: Frame not received from camera.")
+        return False
+
+    temp_frame = frame.copy()
+
+    if modules.globals.live_mirror:
+        temp_frame = cv2.flip(temp_frame, 1) # horizontal flipping
+
+    if modules.globals.live_resizable:
+        temp_frame = fit_image_to_size(temp_frame, PREVIEW.winfo_width(), PREVIEW.winfo_height())
+
+    for frame_processor in frame_processors:
+        temp_frame = frame_processor.process_frame(source_image, temp_frame)
+
+    image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
+    image = ImageOps.contain(image, (temp_frame.shape[1], temp_frame.shape[0]), Image.LANCZOS)
+    image = ctk.CTkImage(image, size=image.size)
+    preview_label.configure(image=image)
+    if virtual_cam:
+        virtual_cam.send(temp_frame)
+        virtual_cam.sleep_until_next_frame()
+    ROOT.update()
+
+    if PREVIEW.state() == 'withdrawn':
+        return False
+    
+    return True
+
+def fit_image_to_size(image, width: int, height: int):
+    if width is None and height is None:
+      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))
+    return cv2.resize(image, dsize=new_size)
+
+def webcam_preview(camera_name: str, virtual_cam_output: bool):
     if modules.globals.source_path is None:
-        # No image selected
         return
 
     global preview_label, PREVIEW
 
-    cap = cv2.VideoCapture(camera_index)
-    if not cap.isOpened():
-        update_status(f"Error: Could not open camera with index {camera_index}")
+    WIDTH = 960
+    HEIGHT = 540
+    FPS = 60
+
+    # Select the camera by its name
+    selected_camera = select_camera(camera_name)
+    if selected_camera is None:
+        update_status(f"No suitable camera found.")
         return
 
-    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 960)  # Set the width of the resolution
-    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 540)  # Set the height of the resolution
-    cap.set(cv2.CAP_PROP_FPS, 60)  # Set the frame rate of the webcam
-    PREVIEW_MAX_WIDTH = 960
-    PREVIEW_MAX_HEIGHT = 540
+    # Use OpenCV's camera index for cross-platform compatibility
+    camera_index = get_camera_index_by_name(camera_name)
 
-    preview_label.configure(image=None)  # Reset the preview image before startup
+    global camera
+    camera = cv2.VideoCapture(camera_index)
 
-    PREVIEW.deiconify()  # Open preview window
+    if not camera.isOpened():
+        update_status(f"Error: Could not open camera {camera_name}")
+        return
+
+    camera.set(cv2.CAP_PROP_FRAME_WIDTH, WIDTH)
+    camera.set(cv2.CAP_PROP_FRAME_HEIGHT, HEIGHT)
+    camera.set(cv2.CAP_PROP_FPS, FPS)
+
+    PREVIEW_MAX_WIDTH = WIDTH
+    PREVIEW_MAX_HEIGHT = HEIGHT
+
+    preview_label.configure(width=PREVIEW_DEFAULT_WIDTH, height=PREVIEW_DEFAULT_HEIGHT)
+    PREVIEW.deiconify()
 
     frame_processors = get_frame_processors_modules(modules.globals.frame_processors)
+    source_image = get_one_face(cv2.imread(modules.globals.source_path))
 
-    source_image = None  # Initialize variable for the selected face image
+    preview_running = True
 
-    while True:
-        ret, frame = cap.read()
-        if not ret:
-            break
+    if virtual_cam_output:
+        with pyvirtualcam.Camera(width=WIDTH, height=HEIGHT, fps=FPS, fmt=pyvirtualcam.PixelFormat.BGR) as virtual_cam:
+            while preview_running:
+                preview_running = webcam_preview_loop(camera, source_image, frame_processors, virtual_cam)
 
-        # Select and save face image only once
-        if source_image is None and modules.globals.source_path:
-            source_image = get_one_face(cv2.imread(modules.globals.source_path))
+    while preview_running:
+        preview_running = webcam_preview_loop(camera, source_image, frame_processors)
 
-        temp_frame = frame.copy()  #Create a copy of the frame
+    if camera: camera.release()
+    PREVIEW.withdraw()
 
-        for frame_processor in frame_processors:
-            temp_frame = frame_processor.process_frame(source_image, temp_frame)
 
-        image = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)  # Convert the image to RGB format to display it with Tkinter
-        image = Image.fromarray(image)
-        image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
-        image = ctk.CTkImage(image, size=image.size)
-        preview_label.configure(image=image)
-        ROOT.update()
+def get_camera_index_by_name(camera_name: str) -> int:
+    """Map camera name to index for OpenCV."""
+    if platform.system() == 'Darwin':  # macOS-specific
+        if "FaceTime" in camera_name:
+            return 0  # Assuming FaceTime is at index 0
+        elif "iPhone" in camera_name:
+            return 1  # Assuming iPhone camera is at index 1
+    elif platform.system() == 'Windows' or platform.system() == 'Linux':
+        # Map camera name to index dynamically (OpenCV on these platforms usually starts with 0)
+        return get_available_cameras().index(camera_name)
+    return -1
 
-    cap.release()
-    PREVIEW.withdraw()  # Close preview window when loop is finished
 
 def get_available_cameras():
-    """Returns a list of available camera indices."""
+    """Get available camera names (cross-platform)."""
     available_cameras = []
-    for index in range(10):  # Check for cameras with index 0 to 9
-        cap = cv2.VideoCapture(index)
-        if cap.isOpened():
-            available_cameras.append(index)
-            cap.release()
-    return available_cameras
+    if platform.system() == 'Darwin':  # macOS-specific
+        devices = AVFoundation.AVCaptureDevice.devicesWithMediaType_(AVFoundation.AVMediaTypeVideo)
+        
+        for device in devices:
+            if device.deviceType() == AVFoundation.AVCaptureDeviceTypeBuiltInWideAngleCamera:
+                print(f"Found Built-In Camera: {device.localizedName()}")
+                available_cameras.append(device.localizedName())
+            elif device.deviceType() == "AVCaptureDeviceTypeExternal":
+                print(f"Found External Camera: {device.localizedName()}")
+                available_cameras.append(device.localizedName())
+            elif device.deviceType() == "AVCaptureDeviceTypeContinuityCamera":
+                print(f"Skipping Continuity Camera: {device.localizedName()}")
+    elif platform.system() == 'Windows' or platform.system() == 'Linux':
+        try:  
+            devices = FilterGraph().get_input_devices()  
+        except Exception as e:  
+            # Use OpenCV to detect camera indexes
+            index = 0
+            devices = [] 
+            while True:
+                cap = cv2.VideoCapture(index)
+                if not cap.isOpened():
+                    break
+                devices.append(f"Camera {index}")
+                cap.release()
+                index += 1
+
+        available_cameras = devices
+    return available_cameras

modules/utilities.py

@@ -5,7 +5,7 @@ import platform
 import shutil
 import ssl
 import subprocess
-import urllib
+import urllib.request
 from pathlib import Path
 from typing import List, Any
 from tqdm import tqdm
@@ -15,127 +15,123 @@ import modules.globals
 TEMP_FILE = 'temp.mp4'
 TEMP_DIRECTORY = 'temp'
 
-# monkey patch ssl for mac
+# Monkey patch SSL for macOS to handle issues with some HTTPS requests
 if platform.system().lower() == 'darwin':
     ssl._create_default_https_context = ssl._create_unverified_context
 
-
 def run_ffmpeg(args: List[str]) -> bool:
     commands = ['ffmpeg', '-hide_banner', '-hwaccel', 'auto', '-loglevel', modules.globals.log_level]
     commands.extend(args)
     try:
         subprocess.check_output(commands, stderr=subprocess.STDOUT)
         return True
-    except Exception:
-        pass
+    except subprocess.CalledProcessError as e:
+        print(f"FFmpeg error: {e.output.decode()}")
     return False
 
-
 def detect_fps(target_path: str) -> float:
-    command = ['ffprobe', '-v', 'error', '-select_streams', 'v:0', '-show_entries', 'stream=r_frame_rate', '-of', 'default=noprint_wrappers=1:nokey=1', target_path]
-    output = subprocess.check_output(command).decode().strip().split('/')
+    command = [
+        'ffprobe', '-v', 'error', '-select_streams', 'v:0', 
+        '-show_entries', 'stream=r_frame_rate', 
+        '-of', 'default=noprint_wrappers=1:nokey=1', target_path
+    ]
     try:
+        output = subprocess.check_output(command).decode().strip().split('/')
         numerator, denominator = map(int, output)
         return numerator / denominator
-    except Exception:
-        pass
+    except (subprocess.CalledProcessError, ValueError):
+        print("Failed to detect FPS, defaulting to 30.0 FPS.")
     return 30.0
 
-
 def extract_frames(target_path: str) -> None:
     temp_directory_path = get_temp_directory_path(target_path)
+    create_temp(target_path)
     run_ffmpeg(['-i', target_path, '-pix_fmt', 'rgb24', os.path.join(temp_directory_path, '%04d.png')])
 
-
 def create_video(target_path: str, fps: float = 30.0) -> None:
     temp_output_path = get_temp_output_path(target_path)
     temp_directory_path = get_temp_directory_path(target_path)
-    run_ffmpeg(['-r', str(fps), '-i', os.path.join(temp_directory_path, '%04d.png'), '-c:v', modules.globals.video_encoder, '-crf', str(modules.globals.video_quality), '-pix_fmt', 'yuv420p', '-vf', 'colorspace=bt709:iall=bt601-6-625:fast=1', '-y', temp_output_path])
-
+    run_ffmpeg([
+        '-r', str(fps), '-i', os.path.join(temp_directory_path, '%04d.png'), 
+        '-c:v', modules.globals.video_encoder, 
+        '-crf', str(modules.globals.video_quality), 
+        '-pix_fmt', 'yuv420p', 
+        '-vf', 'colorspace=bt709:iall=bt601-6-625:fast=1', 
+        '-y', temp_output_path
+    ])
 
 def restore_audio(target_path: str, output_path: str) -> None:
     temp_output_path = get_temp_output_path(target_path)
-    done = run_ffmpeg(['-i', temp_output_path, '-i', target_path, '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', '-y', output_path])
+    done = run_ffmpeg([
+        '-i', temp_output_path, '-i', target_path, 
+        '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', '-y', output_path
+    ])
     if not done:
         move_temp(target_path, output_path)
 
-
 def get_temp_frame_paths(target_path: str) -> List[str]:
     temp_directory_path = get_temp_directory_path(target_path)
-    return glob.glob((os.path.join(glob.escape(temp_directory_path), '*.png')))
-
+    return glob.glob(os.path.join(glob.escape(temp_directory_path), '*.png'))
 
 def get_temp_directory_path(target_path: str) -> str:
-    target_name, _ = os.path.splitext(os.path.basename(target_path))
-    target_directory_path = os.path.dirname(target_path)
-    return os.path.join(target_directory_path, TEMP_DIRECTORY, target_name)
-
+    target_name = Path(target_path).stem
+    target_directory_path = Path(target_path).parent
+    return str(target_directory_path / TEMP_DIRECTORY / target_name)
 
 def get_temp_output_path(target_path: str) -> str:
     temp_directory_path = get_temp_directory_path(target_path)
-    return os.path.join(temp_directory_path, TEMP_FILE)
+    return str(Path(temp_directory_path) / TEMP_FILE)
 
-
-def normalize_output_path(source_path: str, target_path: str, output_path: str) -> Any:
-    if source_path and target_path:
-        source_name, _ = os.path.splitext(os.path.basename(source_path))
-        target_name, target_extension = os.path.splitext(os.path.basename(target_path))
-        if os.path.isdir(output_path):
-            return os.path.join(output_path, source_name + '-' + target_name + target_extension)
+def normalize_output_path(source_path: str, target_path: str, output_path: str) -> str:
+    if source_path and target_path and os.path.isdir(output_path):
+        source_name = Path(source_path).stem
+        target_name = Path(target_path).stem
+        target_extension = Path(target_path).suffix
+        return str(Path(output_path) / f"{source_name}-{target_name}{target_extension}")
     return output_path
 
-
 def create_temp(target_path: str) -> None:
     temp_directory_path = get_temp_directory_path(target_path)
     Path(temp_directory_path).mkdir(parents=True, exist_ok=True)
 
-
 def move_temp(target_path: str, output_path: str) -> None:
     temp_output_path = get_temp_output_path(target_path)
     if os.path.isfile(temp_output_path):
-        if os.path.isfile(output_path):
-            os.remove(output_path)
         shutil.move(temp_output_path, output_path)
 
-
 def clean_temp(target_path: str) -> None:
     temp_directory_path = get_temp_directory_path(target_path)
-    parent_directory_path = os.path.dirname(temp_directory_path)
+    parent_directory_path = Path(temp_directory_path).parent
     if not modules.globals.keep_frames and os.path.isdir(temp_directory_path):
         shutil.rmtree(temp_directory_path)
-    if os.path.exists(parent_directory_path) and not os.listdir(parent_directory_path):
-        os.rmdir(parent_directory_path)
-
+    if parent_directory_path.exists() and not list(parent_directory_path.iterdir()):
+        parent_directory_path.rmdir()
 
 def has_image_extension(image_path: str) -> bool:
     return image_path.lower().endswith(('png', 'jpg', 'jpeg'))
 
-
 def is_image(image_path: str) -> bool:
     if image_path and os.path.isfile(image_path):
         mimetype, _ = mimetypes.guess_type(image_path)
-        return bool(mimetype and mimetype.startswith('image/'))
+        return mimetype and mimetype.startswith('image/')
     return False
 
-
 def is_video(video_path: str) -> bool:
     if video_path and os.path.isfile(video_path):
         mimetype, _ = mimetypes.guess_type(video_path)
-        return bool(mimetype and mimetype.startswith('video/'))
+        return mimetype and mimetype.startswith('video/')
     return False
 
-
 def conditional_download(download_directory_path: str, urls: List[str]) -> None:
-    if not os.path.exists(download_directory_path):
-        os.makedirs(download_directory_path)
+    download_directory = Path(download_directory_path)
+    download_directory.mkdir(parents=True, exist_ok=True)
     for url in urls:
-        download_file_path = os.path.join(download_directory_path, os.path.basename(url))
-        if not os.path.exists(download_file_path):
-            request = urllib.request.urlopen(url) # type: ignore[attr-defined]
-            total = int(request.headers.get('Content-Length', 0))
-            with tqdm(total=total, desc='Downloading', unit='B', unit_scale=True, unit_divisor=1024) as progress:
-                urllib.request.urlretrieve(url, download_file_path, reporthook=lambda count, block_size, total_size: progress.update(block_size)) # type: ignore[attr-defined]
-
+        download_file_path = download_directory / Path(url).name
+        if not download_file_path.exists():
+            with urllib.request.urlopen(url) as request:
+                total = int(request.headers.get('Content-Length', 0))
+                with tqdm(total=total, desc='Downloading', unit='B', unit_scale=True, unit_divisor=1024) as progress:
+                    urllib.request.urlretrieve(url, download_file_path, reporthook=lambda count, block_size, total_size: progress.update(block_size))
 
 def resolve_relative_path(path: str) -> str:
-    return os.path.abspath(os.path.join(os.path.dirname(__file__), path))
+    return str(Path(__file__).parent / path)

requirements.txt

@@ -1,7 +1,7 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
 
 numpy==1.23.5
-opencv-python==4.8.1.78
+opencv-contrib-python==4.10.0.84
 onnx==1.16.0
 insightface==0.7.3
 psutil==5.9.8
@@ -21,3 +21,7 @@ opennsfw2==0.10.2
 protobuf==4.23.2
 tqdm==4.66.4
 gfpgan==1.3.8
+pyobjc==9.1; sys_platform == 'darwin'
+pygrabber==0.2
+pyvirtualcam==0.12.0
+pyobjc-framework-AVFoundation==10.3.1; sys_platform == 'darwin'

setup_deep_live_cam.bat

@@ -3,73 +3,35 @@ setlocal EnableDelayedExpansion
 
 :: 1. Setup your platform
 echo Setting up your platform...
-
-:: Python
-where python >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo Python is not installed. Please install Python 3.10 or later.
-    pause
-    exit /b
-)
-
-:: Pip
-where pip >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo Pip is not installed. Please install Pip.
-    pause
-    exit /b
-)
-
-:: Git
-where git >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo Git is not installed. Installing Git...
-    winget install --id Git.Git -e --source winget
-)
-
-:: FFMPEG
-where ffmpeg >nul 2>&1
-if %ERRORLEVEL% neq 0 (
-    echo FFMPEG is not installed. Installing FFMPEG...
-    winget install --id Gyan.FFmpeg -e --source winget
-)
+call :check_installation python "Python 3.10 or later"
+call :check_installation pip "Pip"
+call :install_if_missing git "Git" "winget install --id Git.Git -e --source winget"
+call :install_if_missing ffmpeg "FFMPEG" "winget install --id Gyan.FFmpeg -e --source winget"
 
 :: Visual Studio 2022 Runtimes
 echo Installing Visual Studio 2022 Runtimes...
 winget install --id Microsoft.VC++2015-2022Redist-x64 -e --source winget
 
 :: 2. Clone Repository
-if exist Deep-Live-Cam (
-    echo Deep-Live-Cam directory already exists.
-    set /p overwrite="Do you want to overwrite? (Y/N): "
-    if /i "%overwrite%"=="Y" (
-        rmdir /s /q Deep-Live-Cam
-        git clone https://github.com/hacksider/Deep-Live-Cam.git
-    ) else (
-        echo Skipping clone, using existing directory.
-    )
-) else (
-    git clone https://github.com/hacksider/Deep-Live-Cam.git
-)
-cd Deep-Live-Cam
+call :clone_repository "https://github.com/iVideoGameBoss/iRoopDeepFaceCam.git" "iRoopDeepFaceCam"
 
 :: 3. Download Models
 echo Downloading models...
-mkdir models
-curl -L -o models/GFPGANv1.4.pth https://path.to.model/GFPGANv1.4.pth
-curl -L -o models/inswapper_128_fp16.onnx https://path.to.model/inswapper_128_fp16.onnx
+if not exist models mkdir models
+curl -L -o models\GFPGANv1.4.pth https://huggingface.co/ivideogameboss/iroopdeepfacecam/resolve/main/GFPGANv1.4.pth
+curl -L -o models\inswapper_128_fp16.onnx https://huggingface.co/ivideogameboss/iroopdeepfacecam/resolve/main/inswapper_128_fp16.onnx
 
 :: 4. Install dependencies
 echo Creating a virtual environment...
 python -m venv venv
-call venv\Scripts\activate
+call venv\Scripts\activate.bat
 
 echo Installing required Python packages...
 pip install --upgrade pip
 pip install -r requirements.txt
-
 echo Setup complete. You can now run the application.
 
+:menu
 :: GPU Acceleration Options
 echo.
 echo Choose the GPU Acceleration Option if applicable:
@@ -81,42 +43,83 @@ echo 5. OpenVINO (Intel)
 echo 6. None
 set /p choice="Enter your choice (1-6): "
 
-if "%choice%"=="1" (
-    echo Installing CUDA dependencies...
-    pip uninstall -y onnxruntime onnxruntime-gpu
-    pip install onnxruntime-gpu==1.16.3
-    set exec_provider="cuda"
-) else if "%choice%"=="2" (
-    echo Installing CoreML (Apple Silicon) dependencies...
-    pip uninstall -y onnxruntime onnxruntime-silicon
-    pip install onnxruntime-silicon==1.13.1
-    set exec_provider="coreml"
-) else if "%choice%"=="3" (
-    echo Installing CoreML (Apple Legacy) dependencies...
-    pip uninstall -y onnxruntime onnxruntime-coreml
-    pip install onnxruntime-coreml==1.13.1
-    set exec_provider="coreml"
-) else if "%choice%"=="4" (
-    echo Installing DirectML dependencies...
-    pip uninstall -y onnxruntime onnxruntime-directml
-    pip install onnxruntime-directml==1.15.1
-    set exec_provider="directml"
-) else if "%choice%"=="5" (
-    echo Installing OpenVINO dependencies...
-    pip uninstall -y onnxruntime onnxruntime-openvino
-    pip install onnxruntime-openvino==1.15.0
-    set exec_provider="openvino"
-) else (
-    echo Skipping GPU acceleration setup.
-)
+set "exec_provider="
+call :set_execution_provider %choice%
+
+:end_choice
+echo.
+echo GPU Acceleration setup complete.
+echo Selected provider: !exec_provider!
+echo.
 
 :: Run the application
 if defined exec_provider (
-    echo Running the application with %exec_provider% execution provider...
-    python run.py --execution-provider %exec_provider%
+    echo Running the application with !exec_provider! execution provider...
+    python run.py --execution-provider !exec_provider!
 ) else (
     echo Running the application...
     python run.py
 )
 
+:: Deactivate the virtual environment
+call venv\Scripts\deactivate.bat
+
+echo.
+echo Script execution completed.
 pause
+exit /b
+
+:check_installation
+where %1 >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo %2 is not installed. Please install %2.
+    pause
+    exit /b
+)
+
+:install_if_missing
+where %1 >nul 2>&1
+if %ERRORLEVEL% neq 0 (
+    echo %2 is not installed. Installing %2...
+    %3
+)
+
+:clone_repository
+if exist %2 (
+    echo %2 directory already exists.
+    set /p overwrite="Do you want to overwrite? (Y/N): "
+    if /i "%overwrite%"=="Y" (
+        rmdir /s /q %2
+        git clone %1
+    ) else (
+        echo Skipping clone, using existing directory.
+    )
+) else (
+    git clone %1
+)
+
+:set_execution_provider
+if "%1"=="1" (
+    call :install_onnxruntime "onnxruntime-gpu" "1.16.3" "cuda"
+) else if "%1"=="2" (
+    call :install_onnxruntime "onnxruntime-silicon" "1.13.1" "coreml"
+) else if "%1"=="3" (
+    call :install_onnxruntime "onnxruntime-coreml" "1.13.1" "coreml"
+) else if "%1"=="4" (
+    call :install_onnxruntime "onnxruntime-directml" "1.15.1" "directml"
+) else if "%1"=="5" (
+    call :install_onnxruntime "onnxruntime-openvino" "1.15.0" "openvino"
+) else if "%1"=="6" (
+    echo Skipping GPU acceleration setup.
+    set "exec_provider=none"
+) else (
+    echo Invalid choice. Please try again.
+    goto menu
+)
+
+:install_onnxruntime
+echo Installing %1 dependencies...
+pip uninstall -y onnxruntime %1
+pip install %1==%2
+set "exec_provider=%3"
+goto end_choice