- Add fan-amd details to Cli
- Update Extract Parallel Processing rules for plaidML
- Handle missing plaidML lib on amd flag
- Pass through correct loglevel from GPUStats to plaidml_tools
Remove FFMPEG from Conda Requirements
Fix Tensorboard logging for Tensorflow 1.13.1
Bump default Conda Tensorflow to 1.13.1
Update max python version to 3.7
Bugfix: Fully disable keypress monitor for GUI
Bugfix: Preview - Handle missing alignments file
Config changes:
- Separate plugin defaults into their own files
- Move mask_type to global training config
- Add ability to pass in custom config files
* Color Augmentation: Implement testing code
* Tweak Contrast and Lighting augmentation amounts
* Prevent color augmentation from entering timelapse
* Remove all augmentations from preview images
Convert - Force prediction batchsize to 1 when converting on CPU
Training: Move snapshot saving to outside of the save threads to avoid race condition
GUI Summary stats. Show iteration count for current training session (fixed to last save amount).
sysinfo,py: CUDNN Check fix for unsupported OSes
cli.py: More useful information
scripts/convert.py: Set processes to 1 if no images are passed in
cv2_dnn aligner: Fix bounding box for negative values
scripts/convert.py: Fix for incorrect frame ranges passed in
* Sort to vgg_face. Remove Face Recognition requirements
* Remove dlib components from setup.py
* Remove dlib from Windows Installer script
* Remove dlib and cmake from requirements.txt
* Update INSTALL.md to remove all dlib requirements
* Remove dlib and cmake from dockerfiles
* Windows installer. Output cli to details Window. Setup.py bugfix
* Skip FaceFilter if invalid paths passed in
* Implement extraction pipeline
* Face filter to vgg_face. Resume partial model downloads
* On-the-fly conversion to extraction pipeline
* Move git model ids from get_model to model definition
Remove Dlib Aligner
Add CV2-DNN Aligner replacement for dlib
Remove aligner models from repo
Add download function to pull models from remote location
Minor FAN fixups
* Separate predict and implement pool
* Add check and raise error to multithreading
Box functions to config. Add crop box option.
* All masks to mask module. Refactor convert masks
Predicted mask passed from model. Cli update
* Intesect box with mask and fixes
* Use raw NN output for convert
Use raw mask for face adjustments. Split adjustments to pre and post warp
* Separate out adjustments. Add unmask sharpen
* Set sensible defaults. Pre PR Testing
* Fix queue sizes. Move masked.py to lib
* Fix Skip Frames. Fix GUI Config popup
* Sensible queue limits. Add a less resource intensive single processing mode
* Fix predicted mask. Amend smooth box defaults
* Deterministic ordering for video output
* Video to Video convert implemented
* Fixups
- Remove defaults from folders across all stages
- Move match-hist and aca into color adjustments selectable
- Handle crashes properly for pooled processes
- Fix output directory does not exist error when creating a new output folder
- Force output to frames if input is not a video
* Add Color Transfer adjustment method
Wrap info text in GUI plugin configure popup
* Refactor image adjustments. Easier to create plugins
Start implementing config options for video encoding
* Add video encoding config options
Allow video encoding for frames input (must pass in a reference video)
Move video and image output writers to plugins
* Image writers config options
Move scaling to cli
Move draw_transparent to images config
Add config options for cv2 writer
Add Pillow image writer
* Add gif filetype to Pillow. Fix draw transparent for Pillow
* Add Animated GIF writer
standardize opencv/pillow defaults
* [speedup] Pre-encode supported writers in the convert pool (opencv, pillow)
Move scaling to convert pool
Remove dfaker mask
* Fix default writer
* Bugfixes
* Better custom argparse formatting
* added new RealFace training model (codenamed: Pegasus)
* minor re-factoring (doesn't break compatibility)
* fixed tf error for input/output sizes with ratios other than 1:2
* linting
* Minor formatting/grammar ammends
* Make loss a fixed config item. Make learning rate an unfixed item
* Check input and output sizes
* Mask optimizations
- Remove repetitive np.array() of items that are already np.arrays
- Remove repetitive reshaping
- Perform dilation on single channel only
- Clarify dfl_full mask parts
- Simplify with for loop
- Add more complex mask based on facial components
- Prep for convert masks
* Line width clarity
Line width clarity
* docstring
* style consistency
* flake8 fixes
* Update _config.py
descritions
torzdf