diff --git a/doc/doc_features.md b/doc/doc_features.md index 367406b..347bfb8 100644 --- a/doc/doc_features.md +++ b/doc/doc_features.md @@ -1,6 +1,10 @@ ### **Features**: -- Windows binary containing pre-compiled dependencies, including CUDA libraries. +- works on AMD, NVIDIA, IntelHD graphics and all OpenCL1.2-compatible videocards with at least 512M video memory + +- CPU-only mode [`--cpu-mode`]. 8th gen Intel core CPU able to train H64 model in 2 days. + +- Windows build is standalone ready to work program and contains all dependencies (CUDA, OpenCL, ffmpeg, .bat script etc) to start working - New models expanding upon the original faceswap model. @@ -8,10 +12,6 @@ - Face metadata embedded into extracted JPG files. -- CPU-only mode [`--cpu-mode`]. 8th gen Intel core CPU able to train H64 model in 2 days. - -- Preview window - - Extractor and Converter run in parallel. - Debug mode option for all stages: [`--debug`] @@ -23,7 +23,6 @@ Predicts faces more uniformly than dlib, resulting in a less jittered aligned output. However, MTCNN extraction will produce more false positives. - Comparison dlib (at left) vs mtcnn on hard case: ![](https://i.imgur.com/5qLiiOV.gif) diff --git a/nnlib/device.py b/nnlib/device.py index fb25278..a8f6c72 100644 --- a/nnlib/device.py +++ b/nnlib/device.py @@ -270,6 +270,8 @@ try: ctx = plaidml.Context() for d in plaidml.devices(ctx, return_all=True)[0]: details = json.loads(d.details) + if details['type'] == 'CPU': #skipping opencl-CPU + continue if 'nvidia' in details['vendor'].lower(): has_nvidia_device = True plaidML_devices += [ {'id':d.id, diff --git a/requirements-gpu-opencl-cuda9-cudnn7.txt b/requirements-cuda9-cudnn7.txt similarity index 100% rename from requirements-gpu-opencl-cuda9-cudnn7.txt rename to requirements-cuda9-cudnn7.txt diff --git a/requirements-opencl.txt b/requirements-opencl.txt new file mode 100644 index 0000000..4429842 --- /dev/null +++ b/requirements-opencl.txt @@ -0,0 +1,11 @@ +numpy==1.16.1 +pathlib==1.0.1 +scandir==1.6 +h5py==2.7.1 +Keras==2.2.4 +opencv-python==4.0.0.21 +tensorflow==1.11.0 +plaidml-keras==0.5.0 +scikit-image +tqdm +git+https://www.github.com/keras-team/keras-contrib.git