mirror of
https://github.com/hacksider/Deep-Live-Cam.git
synced 2025-03-17 13:21:46 +01:00
Revert "Merge pull request #566 from pereiraroland26/main"
This reverts commit 5d450b4352d9211198c5f940d1e503294cdc33ba.
This commit is contained in:
Kenneth Estanislao
parent
5d450b4352
commit
61dae91439
2
.gitignore
vendored
2
.gitignore
vendored
@ -20,5 +20,3 @@ models/inswapper_128.onnx
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models/GFPGANv1.4.pth
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*.onnx
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models/DMDNet.pth
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faceswap/
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.vscode/
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219
README.md
219
README.md
@ -1,4 +1,3 @@
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@ -7,7 +6,7 @@ This software is meant to be a productive contribution to the rapidly growing AI
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The developers of this software are aware of its possible unethical applications and are committed to take preventative measures against them. It has a built-in check which prevents the program from working on inappropriate media including but not limited to nudity, graphic content, sensitive material such as war footage etc. We will continue to develop this project in the positive direction while adhering to law and ethics. This project may be shut down or include watermarks on the output if requested by law.
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Users of this software are expected to use this software responsibly while abiding by local laws. If the face of a real person is being used, users are required to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers of this software will not be responsible for actions of end-users.
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Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers of this software will not be responsible for actions of end-users.
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## How do I install it?
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@ -25,7 +24,7 @@ Users of this software are expected to use this software responsibly while abidi
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#### 3. Download Models
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1. [GFPGANv1.4](https://huggingface.co/hacksider/deep-live-cam/resolve/main/GFPGANv1.4.pth)
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2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128_fp16.onnx) *(Note: Use this [replacement version](https://github.com/facefusion/facefusion-assets/releases/download/models/inswapper_128_fp16.onnx) if an issue occurs on your computer)*
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2. [inswapper_128_fp16.onnx](https://huggingface.co/hacksider/deep-live-cam/resolve/main/inswapper_128.onnx)
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Then put those 2 files on the "**models**" folder
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@ -34,29 +33,27 @@ We highly recommend to work with a `venv` to avoid issues.
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```
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pip install -r requirements.txt
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```
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For MAC OS, You have to install or upgrade python-tk package:
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```
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brew install python-tk@3.10
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```
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##### DONE!!! If you don't have any GPU, You should be able to run roop using `python run.py` command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.
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#### 5. Proceed if you want to use GPU acceleration (optional)
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<details>
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<summary>Click to see the details</summary>
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##### DONE!!! If you dont have any GPU, You should be able to run roop using `python run.py` command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.
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### *Proceed if you want to use GPU Acceleration
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### CUDA Execution Provider (Nvidia)*
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1. Install [CUDA Toolkit 11.8](https://developer.nvidia.com/cuda-11-8-0-download-archive)
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2. Install dependencies:
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```
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pip uninstall onnxruntime onnxruntime-gpu
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pip install onnxruntime-gpu==1.16.3
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```
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3. Usage in case the provider is available:
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```
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python run.py --execution-provider cuda
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```
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### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#coreml-execution-provider-apple-silicon)CoreML Execution Provider (Apple Silicon)
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@ -66,52 +63,65 @@ python run.py --execution-provider cuda
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```
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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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2. Usage in case the provider is available:
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```
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python run.py --execution-provider coreml
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```
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### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#coreml-execution-provider-apple-legacy)CoreML Execution Provider (Apple Legacy)
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1. Install dependencies:
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```
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pip uninstall onnxruntime onnxruntime-coreml
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pip install onnxruntime-coreml==1.13.1
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```
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2. Usage in case the provider is available:
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```
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python run.py --execution-provider coreml
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```
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### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#directml-execution-provider-windows)DirectML Execution Provider (Windows)
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1. Install dependencies:
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```
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pip uninstall onnxruntime onnxruntime-directml
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pip install onnxruntime-directml==1.15.1
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```
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2. Usage in case the provider is available:
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```
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python run.py --execution-provider directml
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```
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### [](https://github.com/s0md3v/roop/wiki/2.-Acceleration#openvino-execution-provider-intel)OpenVINO™ Execution Provider (Intel)
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1. Install dependencies:
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```
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pip uninstall onnxruntime onnxruntime-openvino
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pip install onnxruntime-openvino==1.15.0
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```
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2. Usage in case the provider is available:
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```
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python run.py --execution-provider openvino
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```
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</details>
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## How do I use it?
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> Note: When you run this program for the first time, it will download some models ~300MB in size.
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@ -125,29 +135,29 @@ Choose a face (image with desired face) and the target image/video (image/video
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Just follow the clicks on the screenshot
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1. Select a face
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2. Click live
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3. Wait for a few seconds (it takes a longer time, usually 10 to 30 seconds before the preview shows up)
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3. Wait for a few second (it takes a longer time, usually 10 to 30 seconds before the preview shows up)
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Just use your favorite screencapture to stream like OBS
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> Note: In case you want to change your face, just select another picture, the preview mode will then restart (so just wait a bit).
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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.
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Additional command line arguments are given below. To learn out what they do, check [this guide](https://github.com/s0md3v/roop/wiki/Advanced-Options).
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```
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options:
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-h, --help show this help message and exit
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-s SOURCE_PATH, --source SOURCE_PATH select a source image
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-t TARGET_PATH, --target TARGET_PATH select a target image or video
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-s SOURCE_PATH, --source SOURCE_PATH select an source image
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-t TARGET_PATH, --target TARGET_PATH select an target image or video
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-o OUTPUT_PATH, --output OUTPUT_PATH select output file or directory
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--frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...] frame processors (choices: face_swapper, face_enhancer, ...)
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--frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...] frame processors (choices: face_swapper, face_enhancer, super_resolution...)
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--keep-fps keep original fps
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--keep-audio keep original audio
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--keep-frames keep temporary frames
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--many-faces process every face
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--map-faces map source target faces
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--nsfw-filter filter the NSFW image or video
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--video-encoder {libx264,libx265,libvpx-vp9} adjust output video encoder
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--video-quality [0-51] adjust output video quality
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--live-mirror the live camera display as you see it in the front-facing camera frame
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@ -155,175 +165,24 @@ options:
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--max-memory MAX_MEMORY maximum amount of RAM in GB
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--execution-provider {cpu} [{cpu} ...] available execution provider (choices: cpu, ...)
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--execution-threads EXECUTION_THREADS number of execution threads
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--headless run in headless mode
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--enhancer-upscale-factor Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor
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--source-image-scaling-factor Set the upscale factor for source images. Only applies if `face_swapper` is set as a frame-processor
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-r SCALE, --super-resolution-scale-factor SCALE Super resolution scale factor, choices are 2, 3, 4
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-v, --version show program's version number and exit
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```
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Looking for a CLI mode? Using the -s/--source argument will make the run program in cli mode.
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### Webcam mode on Windows 11 using WSL2 Ubuntu (optional)
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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.
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Processing time will increase with the upscale factor, but it's quite quick.
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<details>
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<summary>Click to see the details</summary>
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If you want to use WSL2 on Windows 11 you will notice, that Ubuntu WSL2 doesn't come with USB-Webcam support in the Kernel. You need to do two things: Compile the Kernel with the right modules integrated and forward your USB Webcam from Windows to Ubuntu with the usbipd app. Here are detailed Steps:
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This tutorial will guide you through the process of setting up WSL2 Ubuntu with USB webcam support, rebuilding the kernel, and preparing the environment for the Deep-Live-Cam project.
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#### 1. Install WSL2 Ubuntu
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Install WSL2 Ubuntu from the Microsoft Store or using PowerShell:
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#### 2. Enable USB Support in WSL2
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1. Install the USB/IP tool for Windows:
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[https://learn.microsoft.com/en-us/windows/wsl/connect-usb](https://learn.microsoft.com/en-us/windows/wsl/connect-usb)
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2. In Windows PowerShell (as Administrator), connect your webcam to WSL:
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```powershell
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usbipd list
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usbipd bind --busid x-x # Replace x-x with your webcam's bus ID
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usbipd attach --wsl --busid x-x # Replace x-x with your webcam's bus ID
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```
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You need to redo the above every time you reboot wsl or re-connect your webcam/usb device.
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#### 3. Rebuild WSL2 Ubuntu Kernel with USB and Webcam Modules
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Follow these steps to rebuild the kernel:
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1. Start with this guide: [https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf](https://github.com/PINTO0309/wsl2_linux_kernel_usbcam_enable_conf)
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2. When you reach the `sudo wget [github.com](http://github.com/)...PINTO0309` step, which won't work for newer kernel versions, follow this video instead or alternatively follow the video tutorial from the beginning:
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[https://www.youtube.com/watch?v=t_YnACEPmrM](https://www.youtube.com/watch?v=t_YnACEPmrM)
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Additional info: [https://askubuntu.com/questions/1413377/camera-not-working-in-cheese-in-wsl2](https://askubuntu.com/questions/1413377/camera-not-working-in-cheese-in-wsl2)
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3. After rebuilding, restart WSL with the new kernel.
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#### 4. Set Up Deep-Live-Cam Project
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Within Ubuntu:
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1. Clone the repository:
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```bash
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git clone [https://github.com/hacksider/Deep-Live-Cam](https://github.com/hacksider/Deep-Live-Cam)
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```
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2. Follow the installation instructions in the repository, including cuda toolkit 11.8, make 100% sure it's not cuda toolkit 12.x.
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#### 5. Verify and Load Kernel Modules
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1. Check if USB and webcam modules are built into the kernel:
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```bash
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zcat /proc/config.gz | grep -i "CONFIG_USB_VIDEO_CLASS"
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```
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2. If modules are loadable (m), not built-in (y), check if the file exists:
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```bash
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ls /lib/modules/$(uname -r)/kernel/drivers/media/usb/uvc/
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```
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3. Load the module and check for errors (optional if built-in):
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```bash
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sudo modprobe uvcvideo
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dmesg | tail
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```
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4. Verify video devices:
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```bash
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sudo ls -al /dev/video*
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```
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#### 6. Set Up Permissions
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1. Add user to video group and set permissions:
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```bash
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sudo usermod -a -G video $USER
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sudo chgrp video /dev/video0 /dev/video1
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sudo chmod 660 /dev/video0 /dev/video1
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```
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2. Create a udev rule for permanent permissions:
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```bash
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sudo nano /etc/udev/rules.d/81-webcam.rules
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```
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Add this content:
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```
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KERNEL=="video[0-9]*", GROUP="video", MODE="0660"
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```
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3. Reload udev rules:
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```bash
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sudo udevadm control --reload-rules && sudo udevadm trigger
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```
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4. Log out and log back into your WSL session.
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5. Start Deep-Live-Cam with `python run.py --execution-provider cuda --max-memory 8` where 8 can be changed to the number of GB VRAM of your GPU has, minus 1-2GB. If you have a RTX3080 with 10GB I suggest adding 8GB. Leave some left for Windows.
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#### Final Notes
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- Steps 6 and 7 may be optional if the modules are built into the kernel and permissions are already set correctly.
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- Always ensure you're using compatible versions of CUDA, ONNX, and other dependencies.
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- If issues persist, consider checking the Deep-Live-Cam project's specific requirements and troubleshooting steps.
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By following these steps, you should have a WSL2 Ubuntu environment with USB webcam support ready for the Deep-Live-Cam project. If you encounter any issues, refer back to the specific error messages and troubleshooting steps provided.
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#### Troubleshooting CUDA Issues
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If you encounter this error:
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```
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[ONNXRuntimeError] : 1 : FAIL : Failed to load library [libonnxruntime_providers_cuda.so](http://libonnxruntime_providers_cuda.so/) with error: libcufft.so.10: cannot open shared object file: No such file or directory
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```
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Follow these steps:
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1. Install CUDA Toolkit 11.8 (ONNX 1.16.3 requires CUDA 11.x, not 12.x):
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[https://developer.nvidia.com/cuda-11-8-0-download-archive](https://developer.nvidia.com/cuda-11-8-0-download-archive)
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select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
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2. Check CUDA version:
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```bash
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/usr/local/cuda/bin/nvcc --version
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```
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3. If the wrong version is installed, remove it completely:
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[https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one](https://askubuntu.com/questions/530043/removing-nvidia-cuda-toolkit-and-installing-new-one)
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4. Install CUDA Toolkit 11.8 again [https://developer.nvidia.com/cuda-11-8-0-download-archive](https://developer.nvidia.com/cuda-11-8-0-download-archive), select: Linux, x86_64, WSL-Ubuntu, 2.0, deb (local)
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```bash
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sudo apt-get -y install cuda-toolkit-11-8
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```
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</details>
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## Want the Next Update Now?
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If you want the latest and greatest build, or want to see some new great features, go to our [experimental branch](https://github.com/hacksider/Deep-Live-Cam/tree/experimental) and experience what the contributors have given.
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## TODO
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- [ ] Support multiple faces feature
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- [ ] Develop a version for web app/service
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- [ ] UI/UX enhancements for desktop app
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- [ ] Speed up model loading
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- [ ] Speed up real-time face swapping
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*Note: This is an open-source project, and we’re working on it in our free time. Therefore, features, replies, bug fixes, etc., might be delayed. We hope you understand. Thanks.*
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## Credits
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- [henryruhs](https://github.com/henryruhs): for being an irreplaceable contributor to the project
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- [ffmpeg](https://ffmpeg.org/): for making video related operations easy
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- [deepinsight](https://github.com/deepinsight): for their [insightface](https://github.com/deepinsight/insightface) project which provided a well-made library and models. Please be reminded that the [use of the model is for non-commercial research purposes only](https://github.com/deepinsight/insightface?tab=readme-ov-file#license).
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- [deepinsight](https://github.com/deepinsight): for their [insightface](https://github.com/deepinsight/insightface) project which provided a well-made library and models.
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- [havok2-htwo](https://github.com/havok2-htwo) : for sharing the code for webcam
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- [GosuDRM](https://github.com/GosuDRM/nsfw-roop) : for uncensoring roop
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- [vic4key](https://github.com/vic4key) : For supporting/contributing on this project
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- and [all developers](https://github.com/hacksider/Deep-Live-Cam/graphs/contributors) behind libraries used in this project.
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- Foot Note: [This is originally roop-cam, see the full history of the code here.](https://github.com/hacksider/roop-cam) Please be informed that the base author of the code is [s0md3v](https://github.com/s0md3v/roop)
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- and all developers behind libraries used in this project.
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@ -1,32 +0,0 @@
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import numpy as np
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from sklearn.cluster import KMeans
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from sklearn.metrics import silhouette_score
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from typing import Any
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def find_cluster_centroids(embeddings, max_k=10) -> Any:
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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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for k in K:
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kmeans = KMeans(n_clusters=k, random_state=0)
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kmeans.fit(embeddings)
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inertia.append(kmeans.inertia_)
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cluster_centroids.append({"k": k, "centroids": kmeans.cluster_centers_})
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diffs = [inertia[i] - inertia[i+1] for i in range(len(inertia)-1)]
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optimal_centroids = cluster_centroids[diffs.index(max(diffs)) + 1]['centroids']
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return optimal_centroids
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def find_closest_centroid(centroids: list, normed_face_embedding) -> list:
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try:
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centroids = np.array(centroids)
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normed_face_embedding = np.array(normed_face_embedding)
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similarities = np.dot(centroids, normed_face_embedding)
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closest_centroid_index = np.argmax(similarities)
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return closest_centroid_index, centroids[closest_centroid_index]
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except ValueError:
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return None
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289
modules/core.py
289
modules/core.py
@ -1,16 +1,17 @@
|
||||
import os
|
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import sys
|
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# single thread doubles cuda performance - needs to be set before torch import
|
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if any(arg.startswith('--execution-provider') for arg in sys.argv):
|
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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
|
||||
@ -19,38 +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('--nsfw-filter', help='filter the NSFW image or video', dest='nsfw_filter', action='store_true', default=False)
|
||||
program.add_argument('--map-faces', help='map source target faces', dest='map_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('-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')
|
||||
@ -60,15 +96,14 @@ 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
|
||||
modules.globals.keep_audio = args.keep_audio
|
||||
modules.globals.keep_frames = args.keep_frames
|
||||
modules.globals.many_faces = args.many_faces
|
||||
modules.globals.nsfw_filter = args.nsfw_filter
|
||||
modules.globals.map_faces = args.map_faces
|
||||
modules.globals.video_encoder = args.video_encoder
|
||||
modules.globals.video_quality = args.video_quality
|
||||
modules.globals.live_mirror = args.live_mirror
|
||||
@ -76,18 +111,26 @@ def parse_args() -> None:
|
||||
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
|
||||
@ -98,7 +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')
|
||||
@ -106,18 +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]:
|
||||
@ -125,34 +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()
|
||||
|
||||
|
||||
@ -163,52 +219,86 @@ 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)
|
||||
|
||||
|
||||
def start() -> None:
|
||||
for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
|
||||
if not frame_processor.pre_start():
|
||||
return
|
||||
update_status('Processing...')
|
||||
# process image to image
|
||||
|
||||
# Process image to image
|
||||
if has_image_extension(modules.globals.target_path):
|
||||
if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
|
||||
process_image_to_image()
|
||||
return
|
||||
|
||||
# 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('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!')
|
||||
return
|
||||
# process image to videos
|
||||
if modules.globals.nsfw_filter and ui.check_and_ignore_nsfw(modules.globals.target_path, destroy):
|
||||
return
|
||||
|
||||
if not modules.globals.map_faces:
|
||||
update_status('Creating temp resources...')
|
||||
create_temp(modules.globals.target_path)
|
||||
update_status('Extracting frames...')
|
||||
extract_frames(modules.globals.target_path)
|
||||
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(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)
|
||||
@ -217,7 +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...')
|
||||
@ -226,12 +318,6 @@ 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(to_quit=True) -> None:
|
||||
@ -241,15 +327,20 @@ def destroy(to_quit=True) -> None:
|
||||
|
||||
|
||||
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
|
||||
|
||||
@ -1,189 +1,27 @@
|
||||
import os
|
||||
import shutil
|
||||
from typing import Any
|
||||
from typing import Any, Optional
|
||||
import insightface
|
||||
|
||||
import cv2
|
||||
import numpy as np
|
||||
import modules.globals
|
||||
from tqdm import tqdm
|
||||
from modules.typing import Frame
|
||||
from modules.cluster_analysis import find_cluster_centroids, find_closest_centroid
|
||||
from modules.utilities import get_temp_directory_path, create_temp, extract_frames, clean_temp, get_temp_frame_paths
|
||||
from pathlib import Path
|
||||
|
||||
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 has_valid_map() -> bool:
|
||||
for map in modules.globals.souce_target_map:
|
||||
if "source" in map and "target" in map:
|
||||
return True
|
||||
return False
|
||||
|
||||
def default_source_face() -> Any:
|
||||
for map in modules.globals.souce_target_map:
|
||||
if "source" in map:
|
||||
return map['source']['face']
|
||||
return None
|
||||
|
||||
def simplify_maps() -> Any:
|
||||
centroids = []
|
||||
faces = []
|
||||
for map in modules.globals.souce_target_map:
|
||||
if "source" in map and "target" in map:
|
||||
centroids.append(map['target']['face'].normed_embedding)
|
||||
faces.append(map['source']['face'])
|
||||
|
||||
modules.globals.simple_map = {'source_faces': faces, 'target_embeddings': centroids}
|
||||
return None
|
||||
|
||||
def add_blank_map() -> Any:
|
||||
try:
|
||||
max_id = -1
|
||||
if len(modules.globals.souce_target_map) > 0:
|
||||
max_id = max(modules.globals.souce_target_map, key=lambda x: x['id'])['id']
|
||||
|
||||
modules.globals.souce_target_map.append({
|
||||
'id' : max_id + 1
|
||||
})
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
def get_unique_faces_from_target_image() -> Any:
|
||||
try:
|
||||
modules.globals.souce_target_map = []
|
||||
target_frame = cv2.imread(modules.globals.target_path)
|
||||
many_faces = get_many_faces(target_frame)
|
||||
i = 0
|
||||
|
||||
for face in many_faces:
|
||||
x_min, y_min, x_max, y_max = face['bbox']
|
||||
modules.globals.souce_target_map.append({
|
||||
'id' : i,
|
||||
'target' : {
|
||||
'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
|
||||
'face' : face
|
||||
}
|
||||
})
|
||||
i = i + 1
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
|
||||
def get_unique_faces_from_target_video() -> Any:
|
||||
try:
|
||||
modules.globals.souce_target_map = []
|
||||
frame_face_embeddings = []
|
||||
face_embeddings = []
|
||||
|
||||
print('Creating temp resources...')
|
||||
clean_temp(modules.globals.target_path)
|
||||
create_temp(modules.globals.target_path)
|
||||
print('Extracting frames...')
|
||||
extract_frames(modules.globals.target_path)
|
||||
|
||||
temp_frame_paths = get_temp_frame_paths(modules.globals.target_path)
|
||||
|
||||
i = 0
|
||||
for temp_frame_path in tqdm(temp_frame_paths, desc="Extracting face embeddings from frames"):
|
||||
temp_frame = cv2.imread(temp_frame_path)
|
||||
many_faces = get_many_faces(temp_frame)
|
||||
|
||||
for face in many_faces:
|
||||
face_embeddings.append(face.normed_embedding)
|
||||
|
||||
frame_face_embeddings.append({'frame': i, 'faces': many_faces, 'location': temp_frame_path})
|
||||
i += 1
|
||||
|
||||
centroids = find_cluster_centroids(face_embeddings)
|
||||
|
||||
for frame in frame_face_embeddings:
|
||||
for face in frame['faces']:
|
||||
closest_centroid_index, _ = find_closest_centroid(centroids, face.normed_embedding)
|
||||
face['target_centroid'] = closest_centroid_index
|
||||
|
||||
for i in range(len(centroids)):
|
||||
modules.globals.souce_target_map.append({
|
||||
'id' : i
|
||||
})
|
||||
|
||||
temp = []
|
||||
for frame in tqdm(frame_face_embeddings, desc=f"Mapping frame embeddings to centroids-{i}"):
|
||||
temp.append({'frame': frame['frame'], 'faces': [face for face in frame['faces'] if face['target_centroid'] == i], 'location': frame['location']})
|
||||
|
||||
modules.globals.souce_target_map[i]['target_faces_in_frame'] = temp
|
||||
|
||||
# dump_faces(centroids, frame_face_embeddings)
|
||||
default_target_face()
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
|
||||
def default_target_face():
|
||||
for map in modules.globals.souce_target_map:
|
||||
best_face = None
|
||||
best_frame = None
|
||||
for frame in map['target_faces_in_frame']:
|
||||
if len(frame['faces']) > 0:
|
||||
best_face = frame['faces'][0]
|
||||
best_frame = frame
|
||||
break
|
||||
|
||||
for frame in map['target_faces_in_frame']:
|
||||
for face in frame['faces']:
|
||||
if face['det_score'] > best_face['det_score']:
|
||||
best_face = face
|
||||
best_frame = frame
|
||||
|
||||
x_min, y_min, x_max, y_max = best_face['bbox']
|
||||
|
||||
target_frame = cv2.imread(best_frame['location'])
|
||||
map['target'] = {
|
||||
'cv2' : target_frame[int(y_min):int(y_max), int(x_min):int(x_max)],
|
||||
'face' : best_face
|
||||
}
|
||||
|
||||
|
||||
def dump_faces(centroids: Any, frame_face_embeddings: list):
|
||||
temp_directory_path = get_temp_directory_path(modules.globals.target_path)
|
||||
|
||||
for i in range(len(centroids)):
|
||||
if os.path.exists(temp_directory_path + f"/{i}") and os.path.isdir(temp_directory_path + f"/{i}"):
|
||||
shutil.rmtree(temp_directory_path + f"/{i}")
|
||||
Path(temp_directory_path + f"/{i}").mkdir(parents=True, exist_ok=True)
|
||||
|
||||
for frame in tqdm(frame_face_embeddings, desc=f"Copying faces to temp/./{i}"):
|
||||
temp_frame = cv2.imread(frame['location'])
|
||||
|
||||
j = 0
|
||||
for face in frame['faces']:
|
||||
if face['target_centroid'] == i:
|
||||
x_min, y_min, x_max, y_max = face['bbox']
|
||||
|
||||
if temp_frame[int(y_min):int(y_max), int(x_min):int(x_max)].size > 0:
|
||||
cv2.imwrite(temp_directory_path + f"/{i}/{frame['frame']}_{j}.png", temp_frame[int(y_min):int(y_max), int(x_min):int(x_max)])
|
||||
j += 1
|
||||
def get_many_faces(frame: Frame) -> Optional[Any]:
|
||||
faces = get_face_analyser().get(frame)
|
||||
return faces if faces else None
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
import os
|
||||
from typing import List, Dict, Any
|
||||
from typing import List, Dict
|
||||
|
||||
ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
WORKFLOW_DIR = os.path.join(ROOT_DIR, 'workflow')
|
||||
@ -9,9 +9,6 @@ file_types = [
|
||||
('Video', ('*.mp4','*.mkv'))
|
||||
]
|
||||
|
||||
souce_target_map = []
|
||||
simple_map = {}
|
||||
|
||||
source_path = None
|
||||
target_path = None
|
||||
output_path = None
|
||||
@ -20,9 +17,6 @@ keep_fps = None
|
||||
keep_audio = None
|
||||
keep_frames = None
|
||||
many_faces = None
|
||||
map_faces = None
|
||||
color_correction = None # New global variable for color correction toggle
|
||||
nsfw_filter = None
|
||||
video_encoder = None
|
||||
video_quality = None
|
||||
live_mirror = None
|
||||
@ -33,5 +27,9 @@ execution_threads = None
|
||||
headless = None
|
||||
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
|
||||
@ -2,58 +2,68 @@ from typing import Any, List
|
||||
import cv2
|
||||
import insightface
|
||||
import threading
|
||||
import os
|
||||
|
||||
import modules.globals
|
||||
import modules.processors.frame.core
|
||||
from modules.core import update_status
|
||||
from modules.face_analyser import get_one_face, get_many_faces, default_source_face
|
||||
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
|
||||
from modules.cluster_analysis import find_closest_centroid
|
||||
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 modules.globals.map_faces and not is_image(modules.globals.source_path):
|
||||
if not is_image(modules.globals.source_path):
|
||||
update_status('Select an image for source path.', NAME)
|
||||
return False
|
||||
elif not modules.globals.map_faces and not get_one_face(cv2.imread(modules.globals.source_path)):
|
||||
update_status('No face in source path detected.', NAME)
|
||||
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 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:
|
||||
# Ensure the frame is in RGB format if color correction is enabled
|
||||
if modules.globals.color_correction:
|
||||
temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)
|
||||
|
||||
if modules.globals.many_faces:
|
||||
many_faces = get_many_faces(temp_frame)
|
||||
if many_faces:
|
||||
@ -65,99 +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_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame:
|
||||
if is_image(modules.globals.target_path):
|
||||
if modules.globals.many_faces:
|
||||
source_face = default_source_face()
|
||||
for map in modules.globals.souce_target_map:
|
||||
target_face = map['target']['face']
|
||||
temp_frame = swap_face(source_face, target_face, temp_frame)
|
||||
|
||||
elif not modules.globals.many_faces:
|
||||
for map in modules.globals.souce_target_map:
|
||||
if "source" in map:
|
||||
source_face = map['source']['face']
|
||||
target_face = map['target']['face']
|
||||
temp_frame = swap_face(source_face, target_face, temp_frame)
|
||||
|
||||
elif is_video(modules.globals.target_path):
|
||||
if modules.globals.many_faces:
|
||||
source_face = default_source_face()
|
||||
for map in modules.globals.souce_target_map:
|
||||
target_frame = [f for f in map['target_faces_in_frame'] if f['location'] == temp_frame_path]
|
||||
|
||||
for frame in target_frame:
|
||||
for target_face in frame['faces']:
|
||||
temp_frame = swap_face(source_face, target_face, temp_frame)
|
||||
|
||||
elif not modules.globals.many_faces:
|
||||
for map in modules.globals.souce_target_map:
|
||||
if "source" in map:
|
||||
target_frame = [f for f in map['target_faces_in_frame'] if f['location'] == temp_frame_path]
|
||||
source_face = map['source']['face']
|
||||
|
||||
for frame in target_frame:
|
||||
for target_face in frame['faces']:
|
||||
temp_frame = swap_face(source_face, target_face, temp_frame)
|
||||
else:
|
||||
many_faces = get_many_faces(temp_frame)
|
||||
if modules.globals.many_faces:
|
||||
source_face = default_source_face()
|
||||
if many_faces:
|
||||
for target_face in many_faces:
|
||||
temp_frame = swap_face(source_face, target_face, temp_frame)
|
||||
|
||||
elif not modules.globals.many_faces:
|
||||
if many_faces:
|
||||
for target_face in many_faces:
|
||||
closest_centroid_index, _ = find_closest_centroid(modules.globals.simple_map['target_embeddings'], target_face.normed_embedding)
|
||||
|
||||
temp_frame = swap_face(modules.globals.simple_map['source_faces'][closest_centroid_index], target_face, temp_frame)
|
||||
return temp_frame
|
||||
|
||||
|
||||
def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
|
||||
if not modules.globals.map_faces:
|
||||
source_face = get_one_face(cv2.imread(source_path))
|
||||
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
|
||||
if progress:
|
||||
progress.update(1)
|
||||
else:
|
||||
for temp_frame_path in temp_frame_paths:
|
||||
temp_frame = cv2.imread(temp_frame_path)
|
||||
try:
|
||||
result = process_frame_v2(temp_frame, temp_frame_path)
|
||||
cv2.imwrite(temp_frame_path, result)
|
||||
except Exception as exception:
|
||||
print(exception)
|
||||
pass
|
||||
if progress:
|
||||
progress.update(1)
|
||||
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(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:
|
||||
if not modules.globals.map_faces:
|
||||
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)
|
||||
else:
|
||||
if modules.globals.many_faces:
|
||||
update_status('Many faces enabled. Using first source image. Progressing...', NAME)
|
||||
target_frame = cv2.imread(output_path)
|
||||
result = process_frame_v2(target_frame)
|
||||
cv2.imwrite(output_path, result)
|
||||
|
||||
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:
|
||||
if modules.globals.map_faces and modules.globals.many_faces:
|
||||
update_status('Many faces enabled. Using first source image. Progressing...', NAME)
|
||||
modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)
|
||||
|
||||
401
modules/ui.py
401
modules/ui.py
@ -19,7 +19,7 @@ if platform.system() == 'Windows' or platform.system() == 'Linux': # Windows or
|
||||
|
||||
import modules.globals
|
||||
import modules.metadata
|
||||
from modules.face_analyser import get_one_face, get_unique_faces_from_target_image, get_unique_faces_from_target_video, add_blank_map, has_valid_map, simplify_maps
|
||||
from modules.face_analyser import get_one_face
|
||||
from modules.capturer import get_video_frame, get_video_frame_total
|
||||
from modules.processors.frame.core import get_frame_processors_modules
|
||||
from modules.utilities import is_image, is_video, resolve_relative_path
|
||||
@ -34,22 +34,6 @@ PREVIEW_MAX_WIDTH = 1200
|
||||
PREVIEW_DEFAULT_WIDTH = 960
|
||||
PREVIEW_DEFAULT_HEIGHT = 540
|
||||
|
||||
POPUP_WIDTH = 750
|
||||
POPUP_HEIGHT = 810
|
||||
POPUP_SCROLL_WIDTH = 740,
|
||||
POPUP_SCROLL_HEIGHT = 700
|
||||
|
||||
POPUP_LIVE_WIDTH = 900
|
||||
POPUP_LIVE_HEIGHT = 820
|
||||
POPUP_LIVE_SCROLL_WIDTH = 890,
|
||||
POPUP_LIVE_SCROLL_HEIGHT = 700
|
||||
|
||||
MAPPER_PREVIEW_MAX_HEIGHT = 100
|
||||
MAPPER_PREVIEW_MAX_WIDTH = 100
|
||||
|
||||
DEFAULT_BUTTON_WIDTH = 200
|
||||
DEFAULT_BUTTON_HEIGHT = 40
|
||||
|
||||
RECENT_DIRECTORY_SOURCE = None
|
||||
RECENT_DIRECTORY_TARGET = None
|
||||
RECENT_DIRECTORY_OUTPUT = None
|
||||
@ -59,11 +43,6 @@ preview_slider = None
|
||||
source_label = None
|
||||
target_label = None
|
||||
status_label = None
|
||||
popup_status_label = None
|
||||
popup_status_label_live = None
|
||||
source_label_dict = {}
|
||||
source_label_dict_live = {}
|
||||
target_label_dict_live = {}
|
||||
|
||||
img_ft, vid_ft = modules.globals.file_types
|
||||
|
||||
@ -169,12 +148,8 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
|
||||
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=0.6125)
|
||||
|
||||
map_faces = ctk.BooleanVar(value=modules.globals.map_faces)
|
||||
map_faces_switch = ctk.CTkSwitch(root, text='Map faces', variable=map_faces, cursor='hand2', command=lambda: setattr(modules.globals, 'map_faces', map_faces.get()))
|
||||
map_faces_switch.place(relx=0.1, rely=0.75)
|
||||
|
||||
start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: analyze_target(start, root))
|
||||
start_button.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)
|
||||
start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: select_output_path(start))
|
||||
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=destroy)
|
||||
stop_button.place(relx=0.4, rely=0.7, relwidth=0.2, relheight=0.05)
|
||||
@ -182,8 +157,22 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
|
||||
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)
|
||||
|
||||
live_button = ctk.CTkButton(root, text='Live', cursor='hand2', command=lambda: webcam_preview(root))
|
||||
live_button.place(relx=0.40, rely=0.86, relwidth=0.2, relheight=0.05)
|
||||
camera_label = ctk.CTkLabel(root, text="Select Camera:")
|
||||
camera_label.place(relx=0.4, rely=0.7525, relwidth=0.2, relheight=0.05)
|
||||
|
||||
available_cameras = get_available_cameras()
|
||||
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=0.7525, relwidth=0.2, relheight=0.05)
|
||||
|
||||
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, relwidth=0.8, rely=0.875)
|
||||
@ -195,109 +184,6 @@ def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.C
|
||||
|
||||
return root
|
||||
|
||||
def analyze_target(start: Callable[[], None], root: ctk.CTk):
|
||||
if POPUP != None and POPUP.winfo_exists():
|
||||
update_status("Please complete pop-up or close it.")
|
||||
return
|
||||
|
||||
if modules.globals.map_faces:
|
||||
modules.globals.souce_target_map = []
|
||||
|
||||
if is_image(modules.globals.target_path):
|
||||
update_status('Getting unique faces')
|
||||
get_unique_faces_from_target_image()
|
||||
elif is_video(modules.globals.target_path):
|
||||
update_status('Getting unique faces')
|
||||
get_unique_faces_from_target_video()
|
||||
|
||||
if len(modules.globals.souce_target_map) > 0:
|
||||
create_source_target_popup(start, root, modules.globals.souce_target_map)
|
||||
else:
|
||||
update_status("No faces found in target")
|
||||
else:
|
||||
select_output_path(start)
|
||||
|
||||
def create_source_target_popup(start: Callable[[], None], root: ctk.CTk, map: list) -> None:
|
||||
global POPUP, popup_status_label
|
||||
|
||||
POPUP = ctk.CTkToplevel(root)
|
||||
POPUP.title("Source x Target Mapper")
|
||||
POPUP.geometry(f"{POPUP_WIDTH}x{POPUP_HEIGHT}")
|
||||
POPUP.focus()
|
||||
|
||||
def on_submit_click(start):
|
||||
if has_valid_map():
|
||||
POPUP.destroy()
|
||||
select_output_path(start)
|
||||
else:
|
||||
update_pop_status("Atleast 1 source with target is required!")
|
||||
|
||||
scrollable_frame = ctk.CTkScrollableFrame(POPUP, width=POPUP_SCROLL_WIDTH, height=POPUP_SCROLL_HEIGHT)
|
||||
scrollable_frame.grid(row=0, column=0, padx=0, pady=0, sticky='nsew')
|
||||
|
||||
def on_button_click(map, button_num):
|
||||
map = update_popup_source(scrollable_frame, map, button_num)
|
||||
|
||||
for item in map:
|
||||
id = item['id']
|
||||
|
||||
button = ctk.CTkButton(scrollable_frame, text="Select source image", command=lambda id=id: on_button_click(map, id), width=DEFAULT_BUTTON_WIDTH, height=DEFAULT_BUTTON_HEIGHT)
|
||||
button.grid(row=id, column=0, padx=50, pady=10)
|
||||
|
||||
x_label = ctk.CTkLabel(scrollable_frame, text=f"X", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
x_label.grid(row=id, column=2, padx=10, pady=10)
|
||||
|
||||
image = Image.fromarray(cv2.cvtColor(item['target']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
target_image = ctk.CTkLabel(scrollable_frame, text=f"T-{id}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
target_image.grid(row=id, column=3, padx=10, pady=10)
|
||||
target_image.configure(image=tk_image)
|
||||
|
||||
popup_status_label = ctk.CTkLabel(POPUP, text=None, justify='center')
|
||||
popup_status_label.grid(row=1, column=0, pady=15)
|
||||
|
||||
close_button = ctk.CTkButton(POPUP, text="Submit", command=lambda: on_submit_click(start))
|
||||
close_button.grid(row=2, column=0, pady=10)
|
||||
|
||||
|
||||
def update_popup_source(scrollable_frame: ctk.CTkScrollableFrame, map: list, button_num: int) -> list:
|
||||
global source_label_dict
|
||||
|
||||
source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
|
||||
|
||||
if "source" in map[button_num]:
|
||||
map[button_num].pop("source")
|
||||
source_label_dict[button_num].destroy()
|
||||
del source_label_dict[button_num]
|
||||
|
||||
if source_path == "":
|
||||
return map
|
||||
else:
|
||||
cv2_img = cv2.imread(source_path)
|
||||
face = get_one_face(cv2_img)
|
||||
|
||||
if face:
|
||||
x_min, y_min, x_max, y_max = face['bbox']
|
||||
|
||||
map[button_num]['source'] = {
|
||||
'cv2' : cv2_img[int(y_min):int(y_max), int(x_min):int(x_max)],
|
||||
'face' : face
|
||||
}
|
||||
|
||||
image = Image.fromarray(cv2.cvtColor(map[button_num]['source']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
source_image = ctk.CTkLabel(scrollable_frame, text=f"S-{button_num}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
source_image.grid(row=button_num, column=1, padx=10, pady=10)
|
||||
source_image.configure(image=tk_image)
|
||||
source_label_dict[button_num] = source_image
|
||||
else:
|
||||
update_pop_status("Face could not be detected in last upload!")
|
||||
return map
|
||||
|
||||
|
||||
def create_preview(parent: ctk.CTk) -> ctk.CTkToplevel:
|
||||
global preview_label, preview_slider
|
||||
@ -320,11 +206,6 @@ def update_status(text: str) -> None:
|
||||
status_label.configure(text=text)
|
||||
ROOT.update()
|
||||
|
||||
def update_pop_status(text: str) -> None:
|
||||
popup_status_label.configure(text=text)
|
||||
|
||||
def update_pop_live_status(text: str) -> None:
|
||||
popup_status_label_live.configure(text=text)
|
||||
|
||||
def update_tumbler(var: str, value: bool) -> None:
|
||||
modules.globals.fp_ui[var] = value
|
||||
@ -513,75 +394,10 @@ def fit_image_to_size(image, width: int, height: int):
|
||||
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:
|
||||
return
|
||||
|
||||
def render_image_preview(image_path: str, size: Tuple[int, int]) -> ctk.CTkImage:
|
||||
image = Image.open(image_path)
|
||||
if size:
|
||||
image = ImageOps.fit(image, size, Image.LANCZOS)
|
||||
return ctk.CTkImage(image, size=image.size)
|
||||
|
||||
|
||||
def render_video_preview(video_path: str, size: Tuple[int, int], frame_number: int = 0) -> ctk.CTkImage:
|
||||
capture = cv2.VideoCapture(video_path)
|
||||
if frame_number:
|
||||
capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
|
||||
has_frame, frame = capture.read()
|
||||
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()
|
||||
|
||||
|
||||
def toggle_preview() -> None:
|
||||
if PREVIEW.state() == 'normal':
|
||||
PREVIEW.withdraw()
|
||||
elif modules.globals.source_path and modules.globals.target_path:
|
||||
init_preview()
|
||||
update_preview()
|
||||
|
||||
|
||||
def init_preview() -> None:
|
||||
if is_image(modules.globals.target_path):
|
||||
preview_slider.pack_forget()
|
||||
if 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')
|
||||
preview_slider.set(0)
|
||||
|
||||
|
||||
def update_preview(frame_number: int = 0) -> None:
|
||||
if modules.globals.source_path and modules.globals.target_path:
|
||||
update_status('Processing...')
|
||||
temp_frame = get_video_frame(modules.globals.target_path, frame_number)
|
||||
if modules.globals.nsfw_filter and check_and_ignore_nsfw(temp_frame):
|
||||
return
|
||||
for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
|
||||
temp_frame = frame_processor.process_frame(
|
||||
get_one_face(cv2.imread(modules.globals.source_path)),
|
||||
temp_frame
|
||||
)
|
||||
image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
|
||||
image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
image = ctk.CTkImage(image, size=image.size)
|
||||
preview_label.configure(image=image)
|
||||
update_status('Processing succeed!')
|
||||
PREVIEW.deiconify()
|
||||
|
||||
def webcam_preview(root: ctk.CTk):
|
||||
if not modules.globals.map_faces:
|
||||
if modules.globals.source_path is None:
|
||||
# No image selected
|
||||
return
|
||||
create_webcam_preview()
|
||||
else:
|
||||
modules.globals.souce_target_map = []
|
||||
create_source_target_popup_for_webcam(root, modules.globals.souce_target_map)
|
||||
|
||||
def create_webcam_preview():
|
||||
global preview_label, PREVIEW
|
||||
|
||||
WIDTH = 960
|
||||
@ -624,7 +440,11 @@ def create_webcam_preview():
|
||||
while preview_running:
|
||||
preview_running = webcam_preview_loop(camera, source_image, frame_processors, virtual_cam)
|
||||
|
||||
temp_frame = frame.copy() #Create a copy of the frame
|
||||
while preview_running:
|
||||
preview_running = webcam_preview_loop(camera, source_image, frame_processors)
|
||||
|
||||
if camera: camera.release()
|
||||
PREVIEW.withdraw()
|
||||
|
||||
|
||||
def get_camera_index_by_name(camera_name: str) -> int:
|
||||
@ -639,18 +459,6 @@ def get_camera_index_by_name(camera_name: str) -> int:
|
||||
return get_available_cameras().index(camera_name)
|
||||
return -1
|
||||
|
||||
if not modules.globals.map_faces:
|
||||
# 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))
|
||||
|
||||
for frame_processor in frame_processors:
|
||||
temp_frame = frame_processor.process_frame(source_image, temp_frame)
|
||||
else:
|
||||
modules.globals.target_path = None
|
||||
|
||||
for frame_processor in frame_processors:
|
||||
temp_frame = frame_processor.process_frame_v2(temp_frame)
|
||||
|
||||
def get_available_cameras():
|
||||
"""Get available camera names (cross-platform)."""
|
||||
@ -682,156 +490,5 @@ def get_available_cameras():
|
||||
cap.release()
|
||||
index += 1
|
||||
|
||||
if PREVIEW.state() == 'withdrawn':
|
||||
break
|
||||
|
||||
camera.release()
|
||||
PREVIEW.withdraw() # Close preview window when loop is finished
|
||||
|
||||
|
||||
def create_source_target_popup_for_webcam(root: ctk.CTk, map: list) -> None:
|
||||
global POPUP_LIVE, popup_status_label_live
|
||||
|
||||
POPUP_LIVE = ctk.CTkToplevel(root)
|
||||
POPUP_LIVE.title("Source x Target Mapper")
|
||||
POPUP_LIVE.geometry(f"{POPUP_LIVE_WIDTH}x{POPUP_LIVE_HEIGHT}")
|
||||
POPUP_LIVE.focus()
|
||||
|
||||
def on_submit_click():
|
||||
if has_valid_map():
|
||||
POPUP_LIVE.destroy()
|
||||
simplify_maps()
|
||||
create_webcam_preview()
|
||||
else:
|
||||
update_pop_live_status("Atleast 1 source with target is required!")
|
||||
|
||||
def on_add_click():
|
||||
add_blank_map()
|
||||
refresh_data(map)
|
||||
update_pop_live_status("Please provide mapping!")
|
||||
|
||||
popup_status_label_live = ctk.CTkLabel(POPUP_LIVE, text=None, justify='center')
|
||||
popup_status_label_live.grid(row=1, column=0, pady=15)
|
||||
|
||||
add_button = ctk.CTkButton(POPUP_LIVE, text="Add", command=lambda: on_add_click())
|
||||
add_button.place(relx=0.2, rely=0.92, relwidth=0.2, relheight=0.05)
|
||||
|
||||
close_button = ctk.CTkButton(POPUP_LIVE, text="Submit", command=lambda: on_submit_click())
|
||||
close_button.place(relx=0.6, rely=0.92, relwidth=0.2, relheight=0.05)
|
||||
|
||||
|
||||
def refresh_data(map: list):
|
||||
global POPUP_LIVE
|
||||
|
||||
scrollable_frame = ctk.CTkScrollableFrame(POPUP_LIVE, width=POPUP_LIVE_SCROLL_WIDTH, height=POPUP_LIVE_SCROLL_HEIGHT)
|
||||
scrollable_frame.grid(row=0, column=0, padx=0, pady=0, sticky='nsew')
|
||||
|
||||
def on_sbutton_click(map, button_num):
|
||||
map = update_webcam_source(scrollable_frame, map, button_num)
|
||||
|
||||
def on_tbutton_click(map, button_num):
|
||||
map = update_webcam_target(scrollable_frame, map, button_num)
|
||||
|
||||
for item in map:
|
||||
id = item['id']
|
||||
|
||||
button = ctk.CTkButton(scrollable_frame, text="Select source image", command=lambda id=id: on_sbutton_click(map, id), width=DEFAULT_BUTTON_WIDTH, height=DEFAULT_BUTTON_HEIGHT)
|
||||
button.grid(row=id, column=0, padx=30, pady=10)
|
||||
|
||||
x_label = ctk.CTkLabel(scrollable_frame, text=f"X", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
x_label.grid(row=id, column=2, padx=10, pady=10)
|
||||
|
||||
button = ctk.CTkButton(scrollable_frame, text="Select target image", command=lambda id=id: on_tbutton_click(map, id), width=DEFAULT_BUTTON_WIDTH, height=DEFAULT_BUTTON_HEIGHT)
|
||||
button.grid(row=id, column=3, padx=20, pady=10)
|
||||
|
||||
if "source" in item:
|
||||
image = Image.fromarray(cv2.cvtColor(item['source']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
source_image = ctk.CTkLabel(scrollable_frame, text=f"S-{id}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
source_image.grid(row=id, column=1, padx=10, pady=10)
|
||||
source_image.configure(image=tk_image)
|
||||
|
||||
if "target" in item:
|
||||
image = Image.fromarray(cv2.cvtColor(item['target']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
target_image = ctk.CTkLabel(scrollable_frame, text=f"T-{id}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
target_image.grid(row=id, column=4, padx=20, pady=10)
|
||||
target_image.configure(image=tk_image)
|
||||
|
||||
|
||||
def update_webcam_source(scrollable_frame: ctk.CTkScrollableFrame, map: list, button_num: int) -> list:
|
||||
global source_label_dict_live
|
||||
|
||||
source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
|
||||
|
||||
if "source" in map[button_num]:
|
||||
map[button_num].pop("source")
|
||||
source_label_dict_live[button_num].destroy()
|
||||
del source_label_dict_live[button_num]
|
||||
|
||||
if source_path == "":
|
||||
return map
|
||||
else:
|
||||
cv2_img = cv2.imread(source_path)
|
||||
face = get_one_face(cv2_img)
|
||||
|
||||
if face:
|
||||
x_min, y_min, x_max, y_max = face['bbox']
|
||||
|
||||
map[button_num]['source'] = {
|
||||
'cv2' : cv2_img[int(y_min):int(y_max), int(x_min):int(x_max)],
|
||||
'face' : face
|
||||
}
|
||||
|
||||
image = Image.fromarray(cv2.cvtColor(map[button_num]['source']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
source_image = ctk.CTkLabel(scrollable_frame, text=f"S-{button_num}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
source_image.grid(row=button_num, column=1, padx=10, pady=10)
|
||||
source_image.configure(image=tk_image)
|
||||
source_label_dict_live[button_num] = source_image
|
||||
else:
|
||||
update_pop_live_status("Face could not be detected in last upload!")
|
||||
return map
|
||||
|
||||
def update_webcam_target(scrollable_frame: ctk.CTkScrollableFrame, map: list, button_num: int) -> list:
|
||||
global target_label_dict_live
|
||||
|
||||
target_path = ctk.filedialog.askopenfilename(title='select an target image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
|
||||
|
||||
if "target" in map[button_num]:
|
||||
map[button_num].pop("target")
|
||||
target_label_dict_live[button_num].destroy()
|
||||
del target_label_dict_live[button_num]
|
||||
|
||||
if target_path == "":
|
||||
return map
|
||||
else:
|
||||
cv2_img = cv2.imread(target_path)
|
||||
face = get_one_face(cv2_img)
|
||||
|
||||
if face:
|
||||
x_min, y_min, x_max, y_max = face['bbox']
|
||||
|
||||
map[button_num]['target'] = {
|
||||
'cv2' : cv2_img[int(y_min):int(y_max), int(x_min):int(x_max)],
|
||||
'face' : face
|
||||
}
|
||||
|
||||
image = Image.fromarray(cv2.cvtColor(map[button_num]['target']['cv2'], cv2.COLOR_BGR2RGB))
|
||||
image = image.resize((MAPPER_PREVIEW_MAX_WIDTH, MAPPER_PREVIEW_MAX_HEIGHT), Image.LANCZOS)
|
||||
tk_image = ctk.CTkImage(image, size=image.size)
|
||||
|
||||
target_image = ctk.CTkLabel(scrollable_frame, text=f"T-{button_num}", width=MAPPER_PREVIEW_MAX_WIDTH, height=MAPPER_PREVIEW_MAX_HEIGHT)
|
||||
target_image.grid(row=button_num, column=4, padx=20, pady=10)
|
||||
target_image.configure(image=tk_image)
|
||||
target_label_dict_live[button_num] = target_image
|
||||
else:
|
||||
update_pop_live_status("Face could not be detected in last upload!")
|
||||
return map
|
||||
|
||||
available_cameras = devices
|
||||
return available_cameras
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user