mirror of
https://github.com/hacksider/Deep-Live-Cam.git
synced 2026-09-09 17:18:58 +02:00
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1
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Kenneth EstanislaoandClaude Opus 4.8
|
c54c8f3105 |
@@ -30,39 +30,13 @@ By using this software, you agree to these terms and commit to using it in a man
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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.
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## Pre-built Quickstart
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## Exclusive v2.7 RC2 Quick Start - Pre-built (Windows/Mac Silicon/CPU)
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<p align="center">
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<a href="https://deeplivecam.net/index.php/quickstart">
|
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<img src="https://github.com/user-attachments/assets/fa2cdf79-c933-4b93-844a-b087192261ed" width="100%" alt="Lite / Ultimate Download Banner">
|
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</a>
|
||||
</p>
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||||
<a href="https://deeplivecam.net/index.php/quickstart"> <img src="media/Download.png" width="285" height="77" />
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<p align="center">
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<img src="https://github.com/user-attachments/assets/56b61811-3a1e-4672-9b50-cf7f6e8e6852" width="40" alt="Windows">
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||||
|
||||
<img src="https://github.com/user-attachments/assets/6538e3a6-c957-431a-b586-2d6abcf534dc" width="34" alt="Mac Silicon">
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|
||||
<img src="https://github.com/user-attachments/assets/ad45142e-426c-4364-a2a9-a512670cc62c" width="40" alt="CPU">
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</p>
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<p align="center">
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<strong>Windows • Mac Silicon • CPU • NVIDIA • AMD</strong>
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</p>
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<p align="center">
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Builds optimized for your hardware.
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</p>
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<p align="center">
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<a href="https://deeplivecam.net/index.php/quickstart">
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<img src="media/Download.png" width="280" alt="Download">
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</a>
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</p>
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> **Ultimate** includes **30+ exclusive features**, performance optimizations, and **priority support**.
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Perfect if you want the fastest setup with **zero manual installation**, pre-configured dependencies, and optimized builds for every supported platform.
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##### 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.
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###### 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.
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## TLDR; Live Deepfake in just 3 Clicks
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@@ -135,7 +109,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
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**1. Set up Your Platform**
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- Python (3.14 recommended; 3.11-3.14 supported)
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- Python (3.11 recommended)
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- pip
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- git
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- [ffmpeg](https://www.youtube.com/watch?v=OlNWCpFdVMA) - ```iex (irm ffmpeg.tc.ht)```
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@@ -144,7 +118,7 @@ This is more likely to work on your computer but will be slower as it utilizes t
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**2. Clone the Repository**
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```bash
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git clone --depth 1 https://github.com/hacksider/Deep-Live-Cam.git
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git clone https://github.com/hacksider/Deep-Live-Cam.git
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cd Deep-Live-Cam
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```
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@@ -168,7 +142,7 @@ pip install -r requirements.txt
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```
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For Linux:
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```bash
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# Ensure you use the installed Python 3.14
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# Ensure you use the installed Python 3.11
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python3 -m venv venv
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source venv/bin/activate
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pip install -r requirements.txt
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@@ -176,17 +150,17 @@ pip install -r requirements.txt
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**For macOS:**
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Apple Silicon (M1 through M5) requires specific setup:
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Apple Silicon (M1/M2/M3) requires specific setup:
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```bash
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# Install Python 3.14
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brew install python@3.14
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# Install Python 3.11 (specific version is important)
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brew install python@3.11
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# Install tkinter package (required for the GUI)
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brew install python-tk@3.14
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brew install python-tk@3.11
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# Create and activate virtual environment with Python 3.14
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python3.14 -m venv venv
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# Create and activate virtual environment with Python 3.11
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python3.11 -m venv venv
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source venv/bin/activate
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# Install dependencies
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@@ -238,29 +212,26 @@ python run.py --execution-provider cuda
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**CoreML Execution Provider (Apple Silicon)**
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Apple Silicon (M1 through M5) specific installation:
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Apple Silicon (M1/M2/M3) specific installation:
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1. Make sure you've completed the macOS setup above using Python 3.14.
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2. No extra install step is needed — `requirements.txt` pulls the official
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`onnxruntime` build, whose macOS wheels ship the CoreML execution provider.
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If you previously installed the unmaintained `onnxruntime-silicon` fork,
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remove it first, as it shadows the real package:
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1. Make sure you've completed the macOS setup above using Python 3.11.
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2. Install dependencies:
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```bash
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pip uninstall onnxruntime-silicon
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pip install -r requirements.txt
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pip uninstall onnxruntime onnxruntime-silicon
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pip install onnxruntime-silicon==1.13.1
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```
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3. Usage:
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```bash
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python3.14 run.py --execution-provider coreml
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python3.11 run.py --execution-provider coreml
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```
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**Important Notes for macOS:**
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- Python 3.11 is the minimum (onnxruntime dropped 3.10); 3.14 is recommended
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- Always run with `python3.14` command not just `python` if you have multiple Python versions installed
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- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.14`
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- You **must** use Python 3.11, not newer versions like 3.13
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- Always run with `python3.11` command not just `python` if you have multiple Python versions installed
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- If you get error about `_tkinter` missing, reinstall the tkinter package: `brew reinstall python-tk@3.11`
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- If you get model loading errors, check that your models are in the correct folder
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- If you encounter conflicts with other Python versions, consider uninstalling them:
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```bash
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@@ -268,9 +239,9 @@ python3.14 run.py --execution-provider coreml
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brew list | grep python
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# Uninstall conflicting versions if needed
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brew uninstall --ignore-dependencies python@3.11
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brew uninstall --ignore-dependencies python@3.13
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# Keep only Python 3.14
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# Keep only Python 3.11
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brew cleanup
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```
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+2
-7
@@ -14,13 +14,8 @@ def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
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if modules.globals.color_correction:
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capture.set(cv2.CAP_PROP_CONVERT_RGB, 1)
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frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
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if frame_total <= 0:
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capture.release()
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return None
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target_index = 0 if frame_number <= 1 else min(frame_total - 1, frame_number - 1)
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capture.set(cv2.CAP_PROP_POS_FRAMES, target_index)
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frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
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capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
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has_frame, frame = capture.read()
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if has_frame and modules.globals.color_correction:
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@@ -4,18 +4,6 @@ from typing import Any
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def find_cluster_centroids(embeddings, max_k=10) -> Any:
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n_samples = len(embeddings)
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if n_samples == 0:
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raise ValueError("embeddings must not be empty")
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if max_k < 1:
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raise ValueError("max_k must be at least 1")
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max_k = min(max_k, n_samples)
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if max_k == 1:
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kmeans = KMeans(n_clusters=1, random_state=0)
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kmeans.fit(embeddings)
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return kmeans.cluster_centers_
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inertia = []
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cluster_centroids = []
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K = range(1, max_k+1)
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+3
-11
@@ -58,7 +58,7 @@ def parse_args() -> None:
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program.add_argument('--live-resizable', help='The live camera frame is resizable', dest='live_resizable', action='store_true', default=False)
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program.add_argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory())
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program.add_argument('--execution-provider', help='execution provider', dest='execution_provider', default=[suggest_default_execution_provider()], choices=suggest_execution_providers(), nargs='+')
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program.add_argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=None)
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program.add_argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=suggest_execution_threads())
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program.add_argument('-v', '--version', action='version', version=f'{modules.metadata.name} {modules.metadata.version}')
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# register deprecated args
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@@ -90,12 +90,6 @@ def parse_args() -> None:
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modules.globals.execution_threads = args.execution_threads
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modules.globals.lang = args.lang
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# The argparse default (None) avoids evaluating suggest_execution_threads()
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# before providers are decoded, and deprecated-arg overrides above may
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# have already set execution_threads.
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if modules.globals.execution_threads is None:
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modules.globals.execution_threads = suggest_execution_threads()
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#for ENHANCER tumblers:
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for enhancer_key in ('face_enhancer', 'face_enhancer_gpen256', 'face_enhancer_gpen512'):
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modules.globals.fp_ui[enhancer_key] = enhancer_key in args.frame_processor
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@@ -138,9 +132,9 @@ def suggest_max_memory() -> int:
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def suggest_default_execution_provider() -> str:
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"""Pick the best available provider: cuda > rocm > coreml > openvino > dml > cpu."""
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"""Pick the best available provider: cuda > rocm > coreml > dml > cpu."""
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available = encode_execution_providers(onnxruntime.get_available_providers())
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for pref in ('cuda', 'rocm', 'coreml', 'openvino', 'dml'):
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for pref in ('cuda', 'rocm', 'coreml', 'dml'):
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if pref in available:
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return pref
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return 'cpu'
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@@ -163,8 +157,6 @@ def suggest_execution_threads() -> int:
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return 1
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if 'CUDAExecutionProvider' in modules.globals.execution_providers:
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return 2
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if 'OpenVINOExecutionProvider' in modules.globals.execution_providers:
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return 1
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# For CPU execution, use most cores but leave some for system
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return max(4, min(cpu_count - 2, 16))
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@@ -335,9 +335,6 @@ def default_target_face():
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best_frame = frame
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break
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if best_face is None:
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continue # No faces detected in this cluster — skip
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for frame in map['target_faces_in_frame']:
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for face in frame['faces']:
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if face['det_score'] > best_face['det_score']:
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@@ -40,15 +40,6 @@ ONNX_PROVIDERS: List[str] = _detect_onnx_providers()
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HAS_CUDA_PROVIDER: bool = "CUDAExecutionProvider" in ONNX_PROVIDERS
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HAS_COREML_PROVIDER: bool = "CoreMLExecutionProvider" in ONNX_PROVIDERS
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HAS_DML_PROVIDER: bool = "DmlExecutionProvider" in ONNX_PROVIDERS
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HAS_OPENVINO_PROVIDER: bool = "OpenVINOExecutionProvider" in ONNX_PROVIDERS
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# OpenVINO execution-provider config shared by every ONNX session builder.
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# AUTO:GPU,NPU,CPU lets OpenVINO pick the best available device in priority
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# order (Intel GPU → NPU → CPU).
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OPENVINO_PROVIDER_CONFIG = (
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"OpenVINOExecutionProvider",
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{"device_type": "AUTO:GPU,NPU,CPU"},
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)
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def camera_backends() -> List[Tuple[int, int]]:
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@@ -74,8 +65,6 @@ def accelerator_label() -> str:
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return "CoreML (Apple Neural Engine)"
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if HAS_COREML_PROVIDER:
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return "CoreML"
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if HAS_OPENVINO_PROVIDER:
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return "OpenVINO (Intel)"
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if HAS_DML_PROVIDER:
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return "DirectML"
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return "CPU"
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@@ -1,17 +1,4 @@
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import importlib.util
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import os
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import numpy
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# Keras 3 defaults to the TensorFlow backend, which has no Python 3.14 wheels.
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# opennsfw2 only runs inference, so any installed backend works; pick one that
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# is actually present before opennsfw2 imports keras.
|
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if "KERAS_BACKEND" not in os.environ:
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||||
for _backend in ("torch", "tensorflow", "jax"):
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||||
if importlib.util.find_spec(_backend) is not None:
|
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os.environ["KERAS_BACKEND"] = _backend
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break
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import opennsfw2
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from PIL import Image
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import cv2 # Add OpenCV import
|
||||
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@@ -14,7 +14,6 @@ import numpy as np
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import onnxruntime
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import modules.globals
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from modules.platform_info import OPENVINO_PROVIDER_CONFIG
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IS_APPLE_SILICON = platform.system() == "Darwin" and platform.machine() == "arm64"
|
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||||
@@ -51,9 +50,6 @@ def build_provider_config(providers=None):
|
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"AllowLowPrecisionAccumulationOnGPU": 1,
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},
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))
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elif p == "OpenVINOExecutionProvider":
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# AUTO lets OpenVINO select the best device
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config.append(OPENVINO_PROVIDER_CONFIG)
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else:
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config.append(p)
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return config
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||||
|
||||
@@ -18,7 +18,6 @@ from modules.utilities import (
|
||||
)
|
||||
from modules.cluster_analysis import find_closest_centroid
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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
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from collections import deque
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import time
|
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@@ -271,8 +270,6 @@ def get_face_swapper() -> Any:
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# Use bare provider — ONNX Runtime defaults are
|
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# fastest on modern GPUs (Blackwell/sm_120).
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providers_config.append(p)
|
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elif p == "OpenVINOExecutionProvider":
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providers_config.append(OPENVINO_PROVIDER_CONFIG)
|
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else:
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providers_config.append(p)
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FACE_SWAPPER = insightface.model_zoo.get_model(
|
||||
|
||||
+14
-15
@@ -1,18 +1,17 @@
|
||||
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
|
||||
numpy>=1.23.5,<2
|
||||
typing-extensions>=4.8.0
|
||||
opencv-python==4.10.0.84
|
||||
cv2_enumerate_cameras==1.1.15
|
||||
onnx==1.21.0
|
||||
insightface==0.7.3
|
||||
psutil==7.2.2
|
||||
psutil==5.9.8
|
||||
PySide6>=6.7,<7
|
||||
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
|
||||
pillow==12.2.0
|
||||
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==5.29.6
|
||||
pygrabber; sys_platform == 'win32'
|
||||
|
||||
@@ -31,30 +31,6 @@ 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
|
||||
|
||||
Reference in New Issue
Block a user