* Core Updates
- Remove lib.utils.keras_backend_quiet and replace with get_backend() where relevant
- Document lib.gpu_stats and lib.sys_info
- Remove call to GPUStats.is_plaidml from convert and replace with get_backend()
- lib.gui.menu - typofix
* Update Dependencies
Bump Tensorflow Version Check
* Port extraction to tf2
* Add custom import finder for loading Keras or tf.keras depending on backend
* Add `tensorflow` to KerasFinder search path
* Basic TF2 training running
* model.initializers - docstring fix
* Fix and pass tests for tf2
* Replace Keras backend tests with faceswap backend tests
* Initial optimizers update
* Monkey patch tf.keras optimizer
* Remove custom Adam Optimizers and Memory Saving Gradients
* Remove multi-gpu option. Add Distribution to cli
* plugins.train.model._base: Add Mirror, Central and Default distribution strategies
* Update tensorboard kwargs for tf2
* Penalized Loss - Fix for TF2 and AMD
* Fix syntax for tf2.1
* requirements typo fix
* Explicit None for clipnorm if using a distribution strategy
* Fix penalized loss for distribution strategies
* Update Dlight
* typo fix
* Pin to TF2.2
* setup.py - Install tensorflow from pip if not available in Conda
* Add reduction options and set default for mirrored distribution strategy
* Explicitly use default strategy rather than nullcontext
* lib.model.backup_restore documentation
* Remove mirrored strategy reduction method and default based on OS
* Initial restructure - training
* Remove PingPong
Start model.base refactor
* Model saving and resuming enabled
* More tidying up of model.base
* Enable backup and snapshotting
* Re-enable state file
Remove loss names from state file
Fix print loss function
Set snapshot iterations correctly
* Revert original model to Keras Model structure rather than custom layer
Output full model and sub model summary
Change NNBlocks to callables rather than custom keras layers
* Apply custom Conv2D layer
* Finalize NNBlock restructure
Update Dfaker blocks
* Fix reloading model under a different distribution strategy
* Pass command line arguments through to trainer
* Remove training_opts from model and reference params directly
* Tidy up model __init__
* Re-enable tensorboard logging
Suppress "Model Not Compiled" warning
* Fix timelapse
* lib.model.nnblocks - Bugfix residual block
Port dfaker
bugfix original
* dfl-h128 ported
* DFL SAE ported
* IAE Ported
* dlight ported
* port lightweight
* realface ported
* unbalanced ported
* villain ported
* lib.cli.args - Update Batchsize + move allow_growth to config
* Remove output shape definition
Get image sizes per side rather than globally
* Strip mask input from encoder
* Fix learn mask and output learned mask to preview
* Trigger Allow Growth prior to setting strategy
* Fix GUI Graphing
* GUI - Display batchsize correctly + fix training graphs
* Fix penalized loss
* Enable mixed precision training
* Update analysis displayed batch to match input
* Penalized Loss - Multi-GPU Fix
* Fix all losses for TF2
* Fix Reflect Padding
* Allow different input size for each side of the model
* Fix conv-aware initialization on reload
* Switch allow_growth order
* Move mixed_precision to cli
* Remove distrubution strategies
* Compile penalized loss sub-function into LossContainer
* Bump default save interval to 250
Generate preview on first iteration but don't save
Fix iterations to start at 1 instead of 0
Remove training deprecation warnings
Bump some scripts.train loglevels
* Add ability to refresh preview on demand on pop-up window
* Enable refresh of training preview from GUI
* Fix Convert
Debug logging in Initializers
* Fix Preview Tool
* Update Legacy TF1 weights to TF2
Catch stats error on loading stats with missing logs
* lib.gui.popup_configure - Make more responsive + document
* Multiple Outputs supported in trainer
Original Model - Mask output bugfix
* Make universal inference model for convert
Remove scaling from penalized mask loss (now handled at input to y_true)
* Fix inference model to work properly with all models
* Fix multi-scale output for convert
* Fix clipnorm issue with distribution strategies
Edit error message on OOM
* Update plaidml losses
* Add missing file
* Disable gmsd loss for plaidnl
* PlaidML - Basic training working
* clipnorm rewriting for mixed-precision
* Inference model creation bugfixes
* Remove debug code
* Bugfix: Default clipnorm to 1.0
* Remove all mask inputs from training code
* Remove mask inputs from convert
* GUI - Analysis Tab - Docstrings
* Fix rate in totals row
* lib.gui - Only update display pages if they have focus
* Save the model on first iteration
* plaidml - Fix SSIM loss with penalized loss
* tools.alignments - Remove manual and fix jobs
* GUI - Remove case formatting on help text
* gui MultiSelect custom widget - Set default values on init
* vgg_face2 - Move to plugins.extract.recognition and use plugins._base base class
cli - Add global GPU Exclude Option
tools.sort - Use global GPU Exlude option for backend
lib.model.session - Exclude all GPUs when running in CPU mode
lib.cli.launcher - Set backend to CPU mode when all GPUs excluded
* Cascade excluded devices to GPU Stats
* Explicit GPU selection for Train and Convert
* Reduce Tensorflow Min GPU Multiprocessor Count to 4
* remove compat.v1 code from extract
* Force TF to skip mixed precision compatibility check if GPUs have been filtered
* Add notes to config for non-working AMD losses
* Rasie error if forcing extract to CPU mode
* Fix loading of legace dfl-sae weights + dfl-sae typo fix
* Remove unused requirements
Update sphinx requirements
Fix broken rst file locations
* docs: lib.gui.display
* clipnorm amd condition check
* documentation - gui.display_analysis
* Documentation - gui.popup_configure
* Documentation - lib.logger
* Documentation - lib.model.initializers
* Documentation - lib.model.layers
* Documentation - lib.model.losses
* Documentation - lib.model.nn_blocks
* Documetation - lib.model.normalization
* Documentation - lib.model.session
* Documentation - lib.plaidml_stats
* Documentation: lib.training_data
* Documentation: lib.utils
* Documentation: plugins.train.model._base
* GUI Stats: prevent stats from using GPU
* Documentation - Original Model
* Documentation: plugins.model.trainer._base
* linting
* unit tests: initializers + losses
* unit tests: nn_blocks
* bugfix - Exclude gpu devices in train, not include
* Enable Exclude-Gpus in Extract
* Enable exclude gpus in tools
* Disallow multiple plugin types in a single model folder
* Automatically add exclude_gpus argument in for cpu backends
* Cpu backend fixes
* Relax optimizer test threshold
* Default Train settings - Set mask to Extended
* Update Extractor cli help text
Update to Python 3.8
* Fix FAN to run on CPU
* lib.plaidml_tools - typofix
* Linux installer - check for curl
* linux installer - typo fix
- Remove lib.utils.keras_backend_quiet and replace with get_backend() where relevant
- Document lib.gpu_stats and lib.sys_info
- Remove call to GPUStats.is_plaidml from convert and replace with get_backend()
- lib.gui.menu - typofix
* Smart Masks - Training
- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code
* Update mask helptext in cli.py
* Fix Warp to Landmarks
Remove SHA1 hashing from training data
* Update mask training config
* Capture missing masks at training init
* lib.image.read_image_batch - Return filenames with batch for ordering
* scripts.train - Documentation
* plugins.train.trainer - documentation
* Ensure backward compatibility.
Fix convert for new predicted masks
* Update removed masks to components for legacy models.
* Move image utils to lib.image
* Add .pylintrc file
* Remove some cv2 pylint ignores
* TrainingData: Load images from disk in batches
* TrainingData: get_landmarks to batch
* TrainingData: transform and flip to batches
* TrainingData: Optimize color augmentation
* TrainingData: Optimize target and random_warp
* TrainingData - Convert _get_closest_match for batching
* TrainingData: Warp To Landmarks optimized
* Save models to threadpoolexecutor
* Move stack_images, Rename ImageManipulation. ImageAugmentation Docstrings
* Masks: Set dtype and threshold for lib.masks based on input face
* Docstrings and Documentation
* requirements.txt: - Pin opencv to 4.1.1 (fixes cv2-dnn error)
* lib.face_detect.DetectedFace: change LandmarksXY to landmarks_xy. Add left, right, top, bottom attributes
* lib.model.session: Session manager for loading models into different graphs (for Nvidia + CPU)
* plugins.extract._base: New parent class for all extract plugins
* plugins.extract.pipeline. Remove MultiProcessing. Dynamically limit batchsize for Nvidia cards. Remove loglevel input
* S3FD + FAN plugins. Standardise to Keras version for all backends
* Standardize all extract plugins to new threaded codebase
* Documentation. Start implementing Numpy style docstrings for Sphinx Documentation
* Remove s3fd_amd. Change convert OTF to expect DetectedFace object
* faces_detect - clean up and documentation
* Remove PoolProcess
* Migrate manual tool to new extract workflow
* Remove AMD specific extractor code from cli and plugins
* Sort tool to new extract workflow
* Remove multiprocessing from project
* Remove multiprocessing queues from QueueManager
* Remove multiprocessing support from logger
* Move face_filter to new extraction pipeline
* Alignments landmarksXY > landmarks_xy and legacy handling
* Intercept get_backend for sphinx doc build
# Add Sphinx documentation
- utils.py: Set FS backend if .faceswap config file doesn't exist
- setup.py: set .faceswap config on setup
- Dynamically load options for AMD/CPU/NVIDIA backends
Deprecation Warning: Rotation in Extract
Deprecation Warning: Multiple models within a single folder
Error Handling: Useful message for training size assertion error
Error Handling: Useful message for fewer images than batch size
Bugfix: BoundingBox object sometimes not available inside spawned process
- Analysis: Handle missing session Ids
- Analysis: Handle invalid data selections
- Analysis: Don't update graph on check box selection
- Analysis: Add cursor events to analysis tab
- Analysis: Change default graph view
- Training: Prevent GUI from attempting to close graphs which do not exist
- Extract/Convert: Make file extensions case-insensitive for preview
- Progress bar: Make compatible for downloads
- Progress bar: Add TQDM Description to progress bar stats text
* PlaidML support in setup.py
* Add AMD flag for plaidml support
* PlaidML - Use .plaidML file if present, otherwise default to largest available
* Update training info message for GUI
* Add AMD option to Windows Installer
* Add quiet keras.backend importer and minor sysinfo amend.
* plug PlaidMLStats into GPUStats
* Update Docs
* 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
* model_refactor (#571)
* original model to new structure
* IAE model to new structure
* OriginalHiRes to new structure
* Fix trainer for different resolutions
* Initial config implementation
* Configparse library added
* improved training data loader
* dfaker model working
* Add logging to training functions
* Non blocking input for cli training
* Add error handling to threads. Add non-mp queues to queue_handler
* Improved Model Building and NNMeta
* refactor lib/models
* training refactor. DFL H128 model Implementation
* Dfaker - use hashes
* Move timelapse. Remove perceptual loss arg
* Update INSTALL.md. Add logger formatting. Update Dfaker training
* DFL h128 partially ported
* Add mask to dfaker (#573)
* Remove old models. Add mask to dfaker
* dfl mask. Make masks selectable in config (#575)
* DFL H128 Mask. Mask type selectable in config.
* remove gan_v2_2
* Creating Input Size config for models
Creating Input Size config for models
Will be used downstream in converters.
Also name change of image_shape to input_shape to clarify ( for future models with potentially different output_shapes)
* Add mask loss options to config
* MTCNN options to config.ini. Remove GAN config. Update USAGE.md
* Add sliders for numerical values in GUI
* Add config plugins menu to gui. Validate config
* Only backup model if loss has dropped. Get training working again
* bugfixes
* Standardise loss printing
* GUI idle cpu fixes. Graph loss fix.
* mutli-gpu logging bugfix
* Merge branch 'staging' into train_refactor
* backup state file
* Crash protection: Only backup if both total losses have dropped
* Port OriginalHiRes_RC4 to train_refactor (OriginalHiRes)
* Load and save model structure with weights
* Slight code update
* Improve config loader. Add subpixel opt to all models. Config to state
* Show samples... wrong input
* Remove AE topology. Add input/output shapes to State
* Port original_villain (birb/VillainGuy) model to faceswap
* Add plugin info to GUI config pages
* Load input shape from state. IAE Config options.
* Fix transform_kwargs.
Coverage to ratio.
Bugfix mask detection
* Suppress keras userwarnings.
Automate zoom.
Coverage_ratio to model def.
* Consolidation of converters & refactor (#574)
* Consolidation of converters & refactor
Initial Upload of alpha
Items
- consolidate convert_mased & convert_adjust into one converter
-add average color adjust to convert_masked
-allow mask transition blur size to be a fixed integer of pixels and a fraction of the facial mask size
-allow erosion/dilation size to be a fixed integer of pixels and a fraction of the facial mask size
-eliminate redundant type conversions to avoid multiple round-off errors
-refactor loops for vectorization/speed
-reorganize for clarity & style changes
TODO
- bug/issues with warping the new face onto a transparent old image...use a cleanup mask for now
- issues with mask border giving black ring at zero erosion .. investigate
- remove GAN ??
- test enlargment factors of umeyama standard face .. match to coverage factor
- make enlargment factor a model parameter
- remove convert_adjusted and referencing code when finished
* Update Convert_Masked.py
default blur size of 2 to match original...
description of enlargement tests
breakout matrxi scaling into def
* Enlargment scale as a cli parameter
* Update cli.py
* dynamic interpolation algorithm
Compute x & y scale factors from the affine matrix on the fly by QR decomp.
Choose interpolation alogrithm for the affine warp based on an upsample or downsample for each image
* input size
input size from config
* fix issues with <1.0 erosion
* Update convert.py
* Update Convert_Adjust.py
more work on the way to merginf
* Clean up help note on sharpen
* cleanup seamless
* Delete Convert_Adjust.py
* Update umeyama.py
* Update training_data.py
* swapping
* segmentation stub
* changes to convert.str
* Update masked.py
* Backwards compatibility fix for models
Get converter running
* Convert:
Move masks to class.
bugfix blur_size
some linting
* mask fix
* convert fixes
- missing facehull_rect re-added
- coverage to %
- corrected coverage logic
- cleanup of gui option ordering
* Update cli.py
* default for blur
* Update masked.py
* added preliminary low_mem version of OriginalHighRes model plugin
* Code cleanup, minor fixes
* Update masked.py
* Update masked.py
* Add dfl mask to convert
* histogram fix & seamless location
* update
* revert
* bugfix: Load actual configuration in gui
* Standardize nn_blocks
* Update cli.py
* Minor code amends
* Fix Original HiRes model
* Add masks to preview output for mask trainers
refactor trainer.__base.py
* Masked trainers converter support
* convert bugfix
* Bugfix: Converter for masked (dfl/dfaker) trainers
* Additional Losses (#592)
* initial upload
* Delete blur.py
* default initializer = He instead of Glorot (#588)
* Allow kernel_initializer to be overridable
* Add ICNR Initializer option for upscale on all models.
* Hopefully fixes RSoDs with original-highres model plugin
* remove debug line
* Original-HighRes model plugin Red Screen of Death fix, take #2
* Move global options to _base. Rename Villain model
* clipnorm and res block biases
* scale the end of res block
* res block
* dfaker pre-activation res
* OHRES pre-activation
* villain pre-activation
* tabs/space in nn_blocks
* fix for histogram with mask all set to zero
* fix to prevent two networks with same name
* GUI: Wider tooltips. Improve TQDM capture
* Fix regex bug
* Convert padding=48 to ratio of image size
* Add size option to alignments tool extract
* Pass through training image size to convert from model
* Convert: Pull training coverage from model
* convert: coverage, blur and erode to percent
* simplify matrix scaling
* ordering of sliders in train
* Add matrix scaling to utils. Use interpolation in lib.aligner transform
* masked.py Import get_matrix_scaling from utils
* fix circular import
* Update masked.py
* quick fix for matrix scaling
* testing thus for now
* tqdm regex capture bugfix
* Minor ammends
* blur size cleanup
* Remove coverage option from convert (Now cascades from model)
* Implement convert for all model types
* Add mask option and coverage option to all existing models
* bugfix for model loading on convert
* debug print removal
* Bugfix for masks in dfl_h128 and iae
* Update preview display. Add preview scaling to cli
* mask notes
* Delete training_data_v2.py
errant file
* training data variables
* Fix timelapse function
* Add new config items to state file for legacy purposes
* Slight GUI tweak
* Raise exception if problem with loaded model
* Add Tensorboard support (Logs stored in model directory)
* ICNR fix
* loss bugfix
* convert bugfix
* Move ini files to config folder. Make TensorBoard optional
* Fix training data for unbalanced inputs/outputs
* Fix config "none" test
* Keep helptext in .ini files when saving config from GUI
* Remove frame_dims from alignments
* Add no-flip and warp-to-landmarks cli options
* Revert OHR to RC4_fix version
* Fix lowmem mode on OHR model
* padding to variable
* Save models in parallel threads
* Speed-up of res_block stability
* Automated Reflection Padding
* Reflect Padding as a training option
Includes auto-calculation of proper padding shapes, input_shapes, output_shapes
Flag included in config now
* rest of reflect padding
* Move TB logging to cli. Session info to state file
* Add session iterations to state file
* Add recent files to menu. GUI code tidy up
* [GUI] Fix recent file list update issue
* Add correct loss names to TensorBoard logs
* Update live graph to use TensorBoard and remove animation
* Fix analysis tab. GUI optimizations
* Analysis Graph popup to Tensorboard Logs
* [GUI] Bug fix for graphing for models with hypens in name
* [GUI] Correctly split loss to tabs during training
* [GUI] Add loss type selection to analysis graph
* Fix store command name in recent files. Switch to correct tab on open
* [GUI] Disable training graph when 'no-logs' is selected
* Fix graphing race condition
* rename original_hires model to unbalanced
* Convert main scripts to use face hashes
* Alignment tool: Use hashes, add logging, add face rename function
* More logging. Update Manual tool to work with hashing
* add new cli options
* add timelapse script
* add batch size on image generation
* fix circular dependency
* add attribute check
* refactor to 3 parameters
* fix some typos
* do not shuffle the set
* default to models folder when no timelapse output supplied
* almost forgot this
* Pre push commit.
Add filetypes support to gui through new classes in lib/cli.py
Add various new functions to tools/effmpeg.py
* Finish developing basic effmpeg functionality.
Ready for public alpha test.
* Add ffmpy to requirements.
Fix gen-vid to allow specifying a new file in GUI.
Fix extract throwing an error when supplied with a valid directory.
Add two new gui user pop interactions: save (allows you to create new
files/directories) and nothing (disables the prompt button when it's not
needed).
Improve logic and argument processing in effmpeg.
* Fix post merge bugs.
Reformat tools.py to match the new style of faceswap.py
Fix some whitespace issues.
* Fix matplotlib.use() being called after pyplot was imported.
* Fix various effmpeg bugs and add ability do terminate nested subprocess
to GUI.
effmpeg changes:
Fix get-fps not printing to terminal.
Fix mux-audio not working.
Add verbosity option. If verbose is not specified than ffmpeg output is
reduced with the -hide_banner flag.
scripts/gui.py changes:
Add ability to terminate nested subprocesses, i.e. the following type of
process tree should now be terminated safely:
gui -> command -> command-subprocess
-> command-subprocess -> command-sub-subprocess
* Add functionality to tools/effmpeg.py, fix some docstring and print statement issues in some files.
tools/effmpeg.py:
Transpose choices now display detailed name in GUI, while in cli they can
still be entered as a number or the full command name.
Add quiet option to effmpeg that only shows critical ffmpeg errors.
Improve user input handling.
lib/cli.py; scripts/convert.py; scripts/extract.py; scripts/train.py:
Fix some line length issues and typos in docstrings, help text and print statements.
Fix some whitespace issues.
lib/cli.py:
Add filetypes to '--alignments' argument.
Change argument action to DirFullPaths where appropriate.
* Bug fixes and improvements to tools/effmpeg.py
Fix bug where duration would not be used even when end time was not set.
Add option to specify output filetype for extraction.
Enchance gen-vid to be able to generate a video from images that were zero padded to any arbitrary number, and not just 5.
Enchance gen-vid to be able to use any of the image formats that a video can be extracted into.
Improve gen-vid output video quality.
Minor code quality improvements and ffmpeg argument formatting improvements.
* Remove dependency on psutil in scripts/gui.py and various small improvements.
lib/utils.py:
Add _image_extensions and _video_extensions as global variables to make them easily portable across all of faceswap.
Fix lack of new lines between function and class declarions to conform to PEP8.
Fix some typos and line length issues in doctsrings and comments.
scripts/convert.py:
Make tqdm print to stdout.
scripts/extract.py:
Make tqdm print to stdout.
Apply workaround for occasional TqdmSynchronisationWarning being thrown.
Fix some typos and line length issues in doctsrings and comments.
scripts/fsmedia.py:
Did TODO in scripts/fsmedia.py in Faces.load_extractor(): TODO Pass extractor_name as argument
Fix lack of new lines between function and class declarions to conform to PEP8.
Fix some typos and line length issues in doctsrings and comments.
Change 2 print statements to use format() for string formatting instead of the old '%'.
scripts/gui.py:
Refactor subprocess generation and termination to remove dependency on psutil.
Fix some typos and line length issues in comments.
tools/effmpeg.py
Refactor DataItem class to use new lib/utils.py global media file extensions.
Improve ffmpeg subprocess termination handling.
* Refactor for PEP 8 and split process function
* Remove backwards compatibility for skip frames
* Split optional functions into own class. Make functions more modular
* train.py - Fix write image bug. Make more modular
* convert.py: Extract alignments from frames if they don't exist
* BugFix: SkipExisting broken since face name refactor
* train.py - Semi-fix for hang on reaching target iteration. Now quits on preview mode
Make tensorflow / system warning less verbose
* Final bugfixes
* Add 'all' back in for selectable detectors
* Final minor tweaks
* Refactor for PEP 8 and split process function
* Remove backwards compatibility for skip frames
* Split optional functions into own class. Make functions more modular
* Conform scripts folder to PEP 8
* train.py - Fix write image bug. Make more modular
* extract.py - Make more modular, Put optional actions into own class
* cli.py - start PEP 8
* cli,py - Pep 8. Refactor and make modular. Bugfixes
* 1st round refactor. Completely untested and probably broken.
* convert.py: Extract alignments from frames if they don't exist
* BugFix: SkipExisting broken since face name refactor
* Extract.py tested
* Minor formatting
* convert.py + train.py amended not tested
* train.py - Semi-fix for hang on reaching target iteration. Now quits on preview mode
Make tensorflow / system warning less verbose
* 2nd pass refactor. Semi tested
bugfixes
* Remove obsolete code. imread/write to Utils
* rename inout.py to fsmedia.py
* Final bugfixes
* Sort images properly (to make the frame range parameter meaningfull)
* Add backup mechanism for model weights.
* Replace 'print' call by 'tqdm.write' call.
* Add support for user-specified rotation angle in extract
* Added rotation-angle-list option to enumerate a list of angles to rotate through
* Adjust rotation matrix translation coords to avoid cropping
* Merged rotation-angle and rotation-angle-list options into rotate_images option
* Backwards compatibility
* Updated check whether to run image rotator
* Switched rotation convention to use positive angle = clockwise rotation, for backwards compatibility
* Image rotator for extract and convert ready for testing
* Revert "Image rotator for extract and convert ready for testing"
This reverts commit bbeb19ef26.
Error in extract code
* add image rotation support to detect more faces
* Update convert.py
Amended to do a single check for for rotation rather than checking twice. Performance gain is likely to be marginal to non-existent, but can't hurt.
* Update convert.py
remove type
* cli.py: Only output message on verbose. Convert.py: Only check for rotation amount once
* Changed command line flag to take arguments to ease future development
* Realigning for upstream/Master
* Minor fix
