Fix: Improve Linux CPU execution and webcam handling. Update README.

README.md

@@ -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
 

modules/core.py

@@ -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

modules/video_capture.py

@@ -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