pull/1172/merge
killerlux 2025-05-13 10:05:12 +02:00 committed by GitHub
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---
name: Feature Request
description: Suggest an idea for this project
labels: enhancement
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context or screenshots about the feature request here.

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---
name: Question
about: Ask a question or request support
labels: question
---
**Your question**
Please describe your question or what you need help with.
**Context**
Add any other context or details that might help us answer your question.

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# Pull Request Template
Thank you for your contribution!
Please fill out the following checklist and provide all relevant information to help us review your pull request.
## Description
Please include a summary of the change and which issue is fixed (if any). Also describe your motivation and context.
Fixes #(issue)
## Checklist
- [ ] My code follows the project style and guidelines
- [ ] I have performed a self-review of my code
- [ ] I have tested the changes and they work as expected
- [ ] I have added tests that prove my fix is effective or that my feature works (if applicable)
- [ ] I have added necessary documentation (if appropriate)
## Additional Information
Please add any other information or screenshots that may help the reviewers.

11
.github/SECURITY.md vendored 100644
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# Security Policy
## Reporting a Vulnerability
If you discover a security vulnerability, please report it by emailing the project maintainers at [your-email@example.com].
- Do **not** create a public issue for security vulnerabilities.
- Provide as much information as possible to help us understand and address the issue quickly.
- We will acknowledge your report within 3 business days and strive to resolve all security issues promptly.
Thank you for helping keep this project and its users safe!

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@ -148,6 +148,31 @@ source venv/bin/activate
pip install -r requirements.txt
```
**For Linux (Debian/Ubuntu based):**
```bash
# Install system dependencies (if needed)
sudo apt-get update
sudo apt-get install python3-venv python3-pip ffmpeg git
# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate
# Install Python dependencies
# (Important: Ensure you have CPU-only versions if not using GPU)
pip uninstall -y torch torchvision torchaudio onnxruntime*
pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu
# Install webcam utilities (optional but helpful for troubleshooting)
sudo apt-get install v4l-utils
# Ensure your user is in the 'video' group for webcam access
# (You might need to log out and log back in after adding)
sudo adduser $USER video
groups
```
**For macOS:**
Apple Silicon (M1/M2/M3) requires specific setup:
@ -181,7 +206,7 @@ source venv/bin/activate
pip install -r requirements.txt
```
**Run:** If you don't have a GPU, you can run Deep-Live-Cam using `python run.py`. Note that initial execution will download models (~300MB).
**Run:** If you don't have a GPU, you can run Deep-Live-Cam using `python run.py` or `python run.py --execution-provider cpu`. Note that initial execution will download models (~300MB). Performance will be very low (potentially < 1 FPS) without a compatible GPU.
### GPU Acceleration

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@ -4,7 +4,11 @@ import sys
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'
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
# disable GPU for tensorflow when using CPU provider
if '--execution-provider' in sys.argv and 'cpu' in sys.argv[sys.argv.index('--execution-provider') + 1]:
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
import warnings
from typing import List
import platform
@ -81,6 +85,13 @@ def parse_args() -> None:
modules.globals.execution_threads = args.execution_threads
modules.globals.lang = args.lang
# If using CPU provider, ensure we're not using any GPU features
if 'cpu' in args.execution_provider:
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
if torch.cuda.is_available():
torch.cuda.empty_cache()
torch.cuda.set_device('cpu')
#for ENHANCER tumbler:
if 'face_enhancer' in args.frame_processor:
modules.globals.fp_ui['face_enhancer'] = True

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@ -42,15 +42,31 @@ class VideoCapturer:
for dev_id, backend in capture_methods:
try:
print(f"Trying device {dev_id} with backend {backend}")
self.cap = cv2.VideoCapture(dev_id, backend)
if self.cap.isOpened():
print(f"Successfully opened device {dev_id} with backend {backend}")
break
self.cap.release()
except Exception:
except Exception as e:
print(f"Failed to open device {dev_id} with backend {backend}: {str(e)}")
continue
else:
# Unix-like systems (Linux/Mac) capture method
self.cap = cv2.VideoCapture(self.device_index)
# Try device 0 first, then the specified device index if different
capture_methods = [(0, cv2.CAP_V4L2), (self.device_index, cv2.CAP_V4L2)] if self.device_index != 0 else [(0, cv2.CAP_V4L2)]
for dev_id, backend in capture_methods:
try:
print(f"Trying device {dev_id} with backend {backend}")
self.cap = cv2.VideoCapture(dev_id, backend)
if self.cap.isOpened():
print(f"Successfully opened device {dev_id} with backend {backend}")
break
self.cap.release()
except Exception as e:
print(f"Failed to open device {dev_id} with backend {backend}: {str(e)}")
continue
if not self.cap or not self.cap.isOpened():
raise RuntimeError("Failed to open camera")
@ -60,6 +76,12 @@ class VideoCapturer:
self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
self.cap.set(cv2.CAP_PROP_FPS, fps)
# Print actual camera settings
actual_width = self.cap.get(cv2.CAP_PROP_FRAME_WIDTH)
actual_height = self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
actual_fps = self.cap.get(cv2.CAP_PROP_FPS)
print(f"Camera initialized with: {actual_width}x{actual_height} @ {actual_fps}fps")
self.is_running = True
return True