update on requirements

some update on what is needed to be updated

README.md

@@ -30,13 +30,39 @@ By using this software, you agree to these terms and commit to using it in a man
 
 Users are expected to use this software responsibly and legally. If using a real person's face, obtain their consent and clearly label any output as a deepfake when sharing online. We are not responsible for end-user actions.
 
-## Exclusive v2.7 RC2 Quick Start - Pre-built (Windows/Mac Silicon/CPU)
+## Pre-built Quickstart
 
-  <a href="https://deeplivecam.net/index.php/quickstart"> <img src="media/Download.png" width="285" height="77" />
+<p align="center">
+  <a href="https://deeplivecam.net/index.php/quickstart">
+    <img src="https://github.com/user-attachments/assets/fa2cdf79-c933-4b93-844a-b087192261ed" width="100%" alt="Lite / Ultimate Download Banner">
+  </a>
+</p>
 
-##### This is the fastest build you can get if you have a discrete NVIDIA or AMD GPU, CPU or Mac Silicon, And you'll receive special priority support. 2.7 beta is the best you can have with 30+ extra features than the open source version.
- 
-###### These Pre-builts are perfect for non-technical users or those who don't have time to, or can't manually install all the requirements. Just a heads-up: this is an open-source project, so you can also install it manually. 
+<p align="center">
+  <img src="https://github.com/user-attachments/assets/56b61811-3a1e-4672-9b50-cf7f6e8e6852" width="40" alt="Windows">
+  &nbsp;&nbsp;&nbsp;
+  <img src="https://github.com/user-attachments/assets/6538e3a6-c957-431a-b586-2d6abcf534dc" width="34" alt="Mac Silicon">
+  &nbsp;&nbsp;&nbsp;
+  <img src="https://github.com/user-attachments/assets/ad45142e-426c-4364-a2a9-a512670cc62c" width="40" alt="CPU">
+</p>
+
+<p align="center">
+  <strong>Windows • Mac Silicon • CPU • NVIDIA • AMD</strong>
+</p>
+
+<p align="center">
+  Builds optimized for your hardware.
+</p>
+
+<p align="center">
+  <a href="https://deeplivecam.net/index.php/quickstart">
+    <img src="media/Download.png" width="280" alt="Download">
+  </a>
+</p>
+
+> **Ultimate** includes **30+ exclusive features**, performance optimizations, and **priority support**.
+
+Perfect if you want the fastest setup with **zero manual installation**, pre-configured dependencies, and optimized builds for every supported platform.
 
 ## TLDR; Live Deepfake in just 3 Clicks
 ![easysteps](https://github.com/user-attachments/assets/af825228-852c-411b-b787-ffd9aac72fc6)
@@ -109,7 +135,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
 
 **1. Set up Your Platform**
 
--   Python (3.11 recommended)
+-   Python (3.14 recommended; 3.11-3.14 supported)
 -   pip
 -   git
 -   [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) - ```iex (irm ffmpeg.tc.ht)```
@@ -118,7 +144,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
 **2. Clone the Repository**
 
 ```bash
-git clone https://github.com/hacksider/Deep-Live-Cam.git
+git clone --depth 1 https://github.com/hacksider/Deep-Live-Cam.git
 cd Deep-Live-Cam
 ```
 
@@ -142,7 +168,7 @@ pip install -r requirements.txt
 ```
 For Linux:
 ```bash
-# Ensure you use the installed Python 3.11
+# Ensure you use the installed Python 3.14
 python3 -m venv venv
 source venv/bin/activate
 pip install -r requirements.txt
@@ -150,17 +176,17 @@ pip install -r requirements.txt
 
 **For macOS:**
 
-Apple Silicon (M1/M2/M3) requires specific setup:
+Apple Silicon (M1 through M5) requires specific setup:
 
 ```bash
-# Install Python 3.11 (specific version is important)
-brew install python@3.11
+# Install Python 3.14
+brew install python@3.14
 
 # Install tkinter package (required for the GUI)
-brew install python-tk@3.11
+brew install python-tk@3.14
 
-# Create and activate virtual environment with Python 3.11
-python3.11 -m venv venv
+# Create and activate virtual environment with Python 3.14
+python3.14 -m venv venv
 source venv/bin/activate
 
 # Install dependencies
@@ -212,26 +238,29 @@ python run.py --execution-provider cuda
 
 **CoreML Execution Provider (Apple Silicon)**
 
-Apple Silicon (M1/M2/M3) specific installation:
+Apple Silicon (M1 through M5) specific installation:
 
-1. Make sure you've completed the macOS setup above using Python 3.11.
-2. Install dependencies:
+1. Make sure you've completed the macOS setup above using Python 3.14.
+2. No extra install step is needed — `requirements.txt` pulls the official
+   `onnxruntime` build, whose macOS wheels ship the CoreML execution provider.
+   If you previously installed the unmaintained `onnxruntime-silicon` fork,
+   remove it first, as it shadows the real package:
 
 ```bash
-pip uninstall onnxruntime onnxruntime-silicon
-pip install onnxruntime-silicon==1.13.1
+pip uninstall onnxruntime-silicon
+pip install -r requirements.txt
 ```
 
 3. Usage:
 
 ```bash
-python3.11 run.py --execution-provider coreml
+python3.14 run.py --execution-provider coreml
 ```
 
 **Important Notes for macOS:**
-- You **must** use Python 3.11, not newer versions like 3.13
-- Always run with `python3.11` command not just `python` if you have multiple Python versions installed
-- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.11`
+- Python 3.11 is the minimum (onnxruntime dropped 3.10); 3.14 is recommended
+- Always run with `python3.14` command not just `python` if you have multiple Python versions installed
+- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.14`
 - If you get model loading errors, check that your models are in the correct folder
 - If you encounter conflicts with other Python versions, consider uninstalling them:
   ```bash
@@ -239,9 +268,9 @@ python3.11 run.py --execution-provider coreml
   brew list | grep python
 
   # Uninstall conflicting versions if needed
-  brew uninstall --ignore-dependencies python@3.13
+  brew uninstall --ignore-dependencies python@3.11
 
-  # Keep only Python 3.11
+  # Keep only Python 3.14
   brew cleanup
   ```
 

modules/capturer.py

@@ -14,8 +14,13 @@ def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
     if modules.globals.color_correction:
         capture.set(cv2.CAP_PROP_CONVERT_RGB, 1)
     
-    frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
-    capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
+    frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+    if frame_total <= 0:
+        capture.release()
+        return None
+
+    target_index = 0 if frame_number <= 1 else min(frame_total - 1, frame_number - 1)
+    capture.set(cv2.CAP_PROP_POS_FRAMES, target_index)
     has_frame, frame = capture.read()
 
     if has_frame and modules.globals.color_correction:

modules/cluster_analysis.py

@@ -4,6 +4,18 @@ from typing import Any
 
 
 def find_cluster_centroids(embeddings, max_k=10) -> Any:
+    n_samples = len(embeddings)
+    if n_samples == 0:
+        raise ValueError("embeddings must not be empty")
+    if max_k < 1:
+        raise ValueError("max_k must be at least 1")
+
+    max_k = min(max_k, n_samples)
+    if max_k == 1:
+        kmeans = KMeans(n_clusters=1, random_state=0)
+        kmeans.fit(embeddings)
+        return kmeans.cluster_centers_
+
     inertia = []
     cluster_centroids = []
     K = range(1, max_k+1)

modules/core.py

@@ -58,7 +58,7 @@ def parse_args() -> None:
     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=[suggest_default_execution_provider()], 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('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=None)
     program.add_argument('-v', '--version', action='version', version=f'{modules.metadata.name} {modules.metadata.version}')
 
     # register deprecated args
@@ -90,6 +90,12 @@ def parse_args() -> None:
     modules.globals.execution_threads = args.execution_threads
     modules.globals.lang = args.lang
 
+    # The argparse default (None) avoids evaluating suggest_execution_threads()
+    # before providers are decoded, and deprecated-arg overrides above may
+    # have already set execution_threads.
+    if modules.globals.execution_threads is None:
+        modules.globals.execution_threads = suggest_execution_threads()
+
     #for ENHANCER tumblers:
     for enhancer_key in ('face_enhancer', 'face_enhancer_gpen256', 'face_enhancer_gpen512'):
         modules.globals.fp_ui[enhancer_key] = enhancer_key in args.frame_processor
@@ -132,9 +138,9 @@ def suggest_max_memory() -> int:
 
 
 def suggest_default_execution_provider() -> str:
-    """Pick the best available provider: cuda > rocm > coreml > dml > cpu."""
+    """Pick the best available provider: cuda > rocm > coreml > openvino > dml > cpu."""
     available = encode_execution_providers(onnxruntime.get_available_providers())
-    for pref in ('cuda', 'rocm', 'coreml', 'dml'):
+    for pref in ('cuda', 'rocm', 'coreml', 'openvino', 'dml'):
         if pref in available:
             return pref
     return 'cpu'
@@ -157,6 +163,8 @@ def suggest_execution_threads() -> int:
         return 1
     if 'CUDAExecutionProvider' in modules.globals.execution_providers:
         return 2
+    if 'OpenVINOExecutionProvider' in modules.globals.execution_providers:
+        return 1
     
     # For CPU execution, use most cores but leave some for system
     return max(4, min(cpu_count - 2, 16))

modules/face_analyser.py

@@ -335,6 +335,9 @@ def default_target_face():
                 best_frame = frame
                 break
 
+        if best_face is None:
+            continue  # No faces detected in this cluster — skip
+
         for frame in map['target_faces_in_frame']:
             for face in frame['faces']:
                 if face['det_score'] > best_face['det_score']:

modules/platform_info.py

@@ -40,6 +40,15 @@ ONNX_PROVIDERS: List[str] = _detect_onnx_providers()
 HAS_CUDA_PROVIDER: bool = "CUDAExecutionProvider" in ONNX_PROVIDERS
 HAS_COREML_PROVIDER: bool = "CoreMLExecutionProvider" in ONNX_PROVIDERS
 HAS_DML_PROVIDER: bool = "DmlExecutionProvider" in ONNX_PROVIDERS
+HAS_OPENVINO_PROVIDER: bool = "OpenVINOExecutionProvider" in ONNX_PROVIDERS
+
+# OpenVINO execution-provider config shared by every ONNX session builder.
+# AUTO:GPU,NPU,CPU lets OpenVINO pick the best available device in priority
+# order (Intel GPU → NPU → CPU).
+OPENVINO_PROVIDER_CONFIG = (
+    "OpenVINOExecutionProvider",
+    {"device_type": "AUTO:GPU,NPU,CPU"},
+)
 
 
 def camera_backends() -> List[Tuple[int, int]]:
@@ -65,6 +74,8 @@ def accelerator_label() -> str:
         return "CoreML (Apple Neural Engine)"
     if HAS_COREML_PROVIDER:
         return "CoreML"
+    if HAS_OPENVINO_PROVIDER:
+        return "OpenVINO (Intel)"
     if HAS_DML_PROVIDER:
         return "DirectML"
     return "CPU"

modules/predicter.py

@@ -1,4 +1,17 @@
+import importlib.util
+import os
+
 import numpy
+
+# Keras 3 defaults to the TensorFlow backend, which has no Python 3.14 wheels.
+# opennsfw2 only runs inference, so any installed backend works; pick one that
+# is actually present before opennsfw2 imports keras.
+if "KERAS_BACKEND" not in os.environ:
+    for _backend in ("torch", "tensorflow", "jax"):
+        if importlib.util.find_spec(_backend) is not None:
+            os.environ["KERAS_BACKEND"] = _backend
+            break
+
 import opennsfw2
 from PIL import Image
 import cv2  # Add OpenCV import

modules/processors/frame/_onnx_enhancer.py

@@ -14,6 +14,7 @@ import numpy as np
 import onnxruntime
 
 import modules.globals
+from modules.platform_info import OPENVINO_PROVIDER_CONFIG
 
 IS_APPLE_SILICON = platform.system() == "Darwin" and platform.machine() == "arm64"
 
@@ -50,6 +51,9 @@ def build_provider_config(providers=None):
                     "AllowLowPrecisionAccumulationOnGPU": 1,
                 },
             ))
+        elif p == "OpenVINOExecutionProvider":
+            # AUTO lets OpenVINO select the best device
+            config.append(OPENVINO_PROVIDER_CONFIG)
         else:
             config.append(p)
     return config

modules/processors/frame/face_swapper.py

@@ -18,6 +18,7 @@ from modules.utilities import (
 )
 from modules.cluster_analysis import find_closest_centroid
 from modules.gpu_processing import gpu_gaussian_blur, gpu_sharpen, gpu_add_weighted, gpu_resize
+from modules.platform_info import OPENVINO_PROVIDER_CONFIG
 import os
 from collections import deque
 import time
@@ -270,6 +271,8 @@ def get_face_swapper() -> Any:
                         # Use bare provider — ONNX Runtime defaults are
                         # fastest on modern GPUs (Blackwell/sm_120).
                         providers_config.append(p)
+                    elif p == "OpenVINOExecutionProvider":
+                        providers_config.append(OPENVINO_PROVIDER_CONFIG)
                     else:
                         providers_config.append(p)
                 FACE_SWAPPER = insightface.model_zoo.get_model(

requirements.txt

@@ -1,17 +1,18 @@
-numpy>=1.23.5,<2
-typing-extensions>=4.8.0
-opencv-python==4.10.0.84
-cv2_enumerate_cameras==1.1.15
-onnx==1.18.0
+numpy>=2.0,<3
+typing-extensions>=4.15.0
+opencv-python==4.14.0.94
+opencv-python-headless==4.14.0.94
+cv2_enumerate_cameras==1.3.3
+onnx==1.22.0
 insightface==0.7.3
-psutil==5.9.8
+psutil==7.2.2
 PySide6>=6.7,<7
-pillow==12.1.1
-tqdm>=4.65.0
-onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64'
-onnxruntime-gpu==1.23.2; sys_platform != 'darwin'
-tensorflow>=2.15.0; sys_platform != 'darwin'
-tensorflow>=2.15.0; sys_platform == 'darwin' and python_version < '3.13'
-opennsfw2==0.10.2
-protobuf==4.25.1
+pillow==12.3.0
+tqdm>=4.66.3
+onnxruntime==1.28.0; sys_platform == 'darwin' and platform_machine == 'arm64'
+onnxruntime==1.23.0; sys_platform == 'darwin' and platform_machine != 'arm64'
+onnxruntime-gpu==1.26.0; sys_platform != 'darwin'
+opennsfw2==0.18.0
+keras>=3.0.0
+protobuf>=6.33.5,<8
 pygrabber; sys_platform == 'win32'

run.py

@@ -31,6 +31,30 @@ if sys.platform == "win32":
             except (OSError, AttributeError):
                 pass
 
+    # On Windows, register OpenVINO DLL directories so onnxruntime's
+    # OpenVINOExecutionProvider can find openvino.dll.  This must happen
+    # before any ONNX InferenceSession is created.  Failure is non-fatal:
+    # OpenVINO simply isn't installed, and onnxruntime will fall back to CPU.
+    try:
+        from onnxruntime.tools.add_openvino_win_libs import (  # type: ignore[import-untyped]  # noqa: E501
+            add_openvino_libs_to_path,
+        )
+        add_openvino_libs_to_path()
+    except ImportError:
+        # onnxruntime build without the OpenVINO tooling module — no-op.
+        pass
+    except FileNotFoundError:
+        # OpenVINO site-packages dir absent — no-op.
+        pass
+    except SystemExit as exc:
+        # add_openvino_libs_to_path() calls sys.exit() when OpenVINO libs
+        # can't be located (e.g. OPENVINO_LIB_PATHS unset).  Log the message
+        # it raised with so the failure is visible, but keep startup alive.
+        print(
+            f"[startup] OpenVINO DLL registration skipped: {exc}",
+            flush=True,
+        )
+
 # On Linux, pre-load NVIDIA shared libraries (cuDNN, cuBLAS, nvrtc...) shipped
 # inside the venv via pip wheels (nvidia-cudnn-cu12, etc.). LD_LIBRARY_PATH
 # cannot be set after Python starts, so we use ctypes.CDLL with RTLD_GLOBAL