F5-TTS Engine/Settings changes
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erew123 authored and GitHub committed
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@@ -39,7 +39,9 @@ import sys
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def install_and_restart():
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try:
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print("##########################################")
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print("F5-TTS not found. Attempting to install...")
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print("##########################################")
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subprocess.check_call([
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sys.executable,
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"-m",
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@@ -47,7 +49,9 @@ def install_and_restart():
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"install",
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"git+https://github.com/SWivid/F5-TTS.git"
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])
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print("########################################################")
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print("F5-TTS installed successfully! Restarting application...")
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print("########################################################")
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# Get the current script's path
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script_path = sys.argv[0]
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@@ -56,7 +60,9 @@ def install_and_restart():
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os.execv(sys.executable, ['python'] + sys.argv)
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except subprocess.CalledProcessError as e:
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print("########################################################")
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print(f"Failed to install F5-TTS: {str(e)}")
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print("########################################################")
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raise ImportError("Could not install required package F5-TTS")
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try:
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@@ -152,6 +158,9 @@ class tts_class:
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self.debug_tts = configfile_data.get("debugging").get("debug_tts") # Can be used within this script as a True/False flag for generally debugging the TTS generation process.
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self.debug_tts_variables = configfile_data.get("debugging").get("debug_tts_variables") # Can be used within this script as a True/False flag for generally debugging variables (if you wish).
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############################################################################
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# DONT CHANGE # These settings are specific to the F5-TTS Model/Engine ####
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############################################################################
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# Add F5-TTS specific parameters
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self.target_sample_rate = 24000
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self.n_mel_channels = 100
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@@ -444,16 +453,10 @@ class tts_class:
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#################################################################################
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#################################################################################
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# CHANGE ME # Model loading # Piper does not actually load/stay resident in RAM #
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# CHANGE ME # Model loading #####################################################
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#################################################################################
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#################################################################################
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# This function will handle the loading of your model, into VRAM/CUDA, System RAM or whatever.
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# In XTTS, which has 2x model loader types, there are 2x loaders. They are called by "def handle_tts_method_change"
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# In Piper we fake a model loader as Piper doesnt actually load a model into CUDA/System RAM as such. So, in that
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# situation, api_manual_load_model is kind of a blank function. Though we do set self.is_tts_model_loaded = True
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# as this is used elsewhere in the scripts to confirm that a model is available to be used for TTS generation.
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# We always check for "No Models Available" being sent as that means we are trying to load in a model that
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# doesnt exist/wasnt found on script start-up e.g. someone deleted the model from the folder or something.
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async def api_manual_load_model(self, model_name):
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if model_name == "No Models Found":
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print(f"[{self.branding}ENG] \033[91mError\033[0m: No models for this TTS engine were found to load.")
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@@ -567,11 +570,6 @@ class tts_class:
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###############################
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###############################
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# This function will handle the UN-loading of your model, from VRAM/CUDA, System RAM or whatever.
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# In XTTS, that model loads into CUDA/System Ram, so when we swap models, we want to unload the current model
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# free up the memory and then load in the new model to VRAM/CUDA. On the flip side of that, Piper doesnt
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# doesnt load into memory, so we just need to put a fake function here that doesnt really do anything
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# other than set "self.is_tts_model_loaded = False", which would be set back to true by the model loader.
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# So look at the Piper model_engine.py if you DONT need to unload models.
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async def unload_model(self):
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# ↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑
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# ↑↑↑ Keep everything above this line ↑↑↑
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@@ -597,15 +595,11 @@ class tts_class:
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###################################################################################################################################
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###################################################################################################################################
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# CHANGE ME # Model changing. Unload out old model and load in a new one # XTTS is very unusal as it has 2x model loading methods #
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# CHANGE ME # Model changing. Unload out old model and load in a new one ##########################################################
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###################################################################################################################################
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###################################################################################################################################
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# This function is your central model loading/unloading handler that deals with the above functions as necesary, to call loading, unloading,
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# swappng DeepSpeed, Low vram etc. This function gets called with a "engine name - model name" type call. In XTTS, because there are 2x
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# model loader types, (XTTS and APILocal), we take tts_method and split the "engine name - model name" into a loader type and the model
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# that it needs to load in and then we call the correct loader function. Whereas in Piper, which doesnt load models into memory at all,
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# we just have a fake function that doesnt really do anything. We always check to see if the model name has "No Models Available" in the
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# name thats sent over, just to catch any potential errors. We display the start load time and end load time. Thats about it.
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# swappng DeepSpeed, Low vram etc. This function gets called with a "engine name - model name" type call.
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async def handle_tts_method_change(self, tts_method):
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generate_start_time = time.time() # Record the start time of loading the model
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if "No Models Available" in self.available_models:
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@@ -887,9 +881,9 @@ class tts_class:
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return chunks
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##########################################################################################################################################
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##########################################################################################################################################
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# CHANGE ME # Model changing. Unload out old model and load in a new one # XTTS is very unusal as it has 2x model TTS generation methods #
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##########################################################################################################################################
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# CHANGE ME # Model changing. Unload out old model and load in a new one #################################################################
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##########################################################################################################################################
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##########################################################################################################################################
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# In here all the possible options are sent over (text, voice to use, lanugage, speed etc etc) and its up to you how you use them, or not.
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@@ -904,9 +898,7 @@ class tts_class:
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# we have to have an option for Streaming, even if our TTS engine doesnt support streaming. So in that case, we would set streaming_capable
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# as false in our model_settings.JSON file, meaning streaming will never be called. However, we have to put a fake streaming routine in our
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# function below (or a real function if it does support streaming of course). Parler has an example of a fake streaming function, which is
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# very clearly highlighted in its model_engine.py script.
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# Piper TTS, which uses command line based calls and therefore has different ones for Windows and Linux/Mac, has an example of doing this
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# within its model_engine.py file.
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# very clearly highlighted in its model_engine.py script.
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async def generate_tts(self, text, voice, language, temperature, repetition_penalty, speed, pitch, output_file, streaming):
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if voice == "No Voices Found":
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print(f"[{self.branding}ENG] \033[91mError\033[0m: No voices found to generate TTS.")
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