Introducing CLI revamp [WIP]

TTS/bin/frogie.py

@@ -0,0 +1,25 @@
+def ascii_art_printer():
+    print(r"""
+
+    #                   ,*++++++*,                ,*++++++*,
+    #                *++.        .+++          *++.        .++*
+    #              *+*     ,++++*   *+*      *+*   ,++++,     *+*
+    #             ,+,   .++++++++++* ,++,,,,*+, ,++++++++++.   *+,
+    #             *+.  .++++++++++++..++    *+.,++++++++++++.  .+*
+    #             .+*   ++++++++++++.*+,    .+*.++++++++++++   *+,
+    #              .++   *++++++++* ++,      .++.*++++++++*   ++,
+    #               ,+++*.    . .*++,          ,++*.      .*+++*
+    #              *+,   .,*++**.                  .**++**.   ,+*
+    #             .+*                                          *+,
+    #             *+.                   Coqui                  .+*
+    #             *+*              +++   TTS  +++              *+*
+    #             .+++*.            .          .             *+++.
+    #              ,+* *+++*...                       ...*+++* *+,
+    #               .++.     .---+++++++****+++++++----.    ++.
+    #                 ,++.                                .++,
+    #                   .++*                            *++.
+    #                       *+++,                  ,+++*
+    #                           .,*++++::::::++++*,.
+    #                                  ``````
+
+    """)

TTS/bin/inquire.py

@@ -0,0 +1,340 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# pylint: disable=redefined-outer-name, unused-argument
+from pathlib import Path
+
+from TTS.utils.manage import ModelManager
+from TTS.utils.synthesizer import Synthesizer
+
+import inquirer
+from inquirer.themes import GreenPassion
+
+# TODO add inquirer in requirements.txt
+
+path = Path(__file__).parent / "../.models.json"
+manager = ModelManager(path)
+
+str2none = lambda i: i or None  # converter for default None (''->None)
+
+
+def official_zoo_inquirer():
+    model_list = {}
+    model_list["tts_models"] = manager.list_tts_models(print_list=False)
+    model_list["vocoder_models"] = manager.list_vocoder_models(print_list=False)
+    model_list["vocoder_models"].insert(0, "default_vocoder")
+    model_load_questions = [
+        inquirer.List(
+            "tts_choose",
+            message="Choose a tts model to load",
+            choices=model_list["tts_models"],
+            default="tts_models/en/ljspeech/tacotron2-DDC",
+        ),
+        inquirer.List(
+            "vocoder_choose",
+            message="Choose a vocoder model to load",
+            choices=model_list["vocoder_models"],
+        ),
+        inquirer.List(
+            "use_cuda",
+            message="Run model on CUDA?",
+            choices=[True, False],
+            default=True,
+        ),
+    ]
+    answers_model_load = inquirer.prompt(model_load_questions, theme=GreenPassion())
+    return answers_model_load
+
+
+def official_zoo_info_inquirer():
+    joint_model_list = manager.list_tts_models(print_list=False) + manager.list_vocoder_models(print_list=False)
+    model_info_questions = [
+        inquirer.List(
+            "model_choose_for_info",
+            message="Choose a tts model for info",
+            choices=joint_model_list,
+        ),
+    ]
+    answers_model_info_request = inquirer.prompt(model_info_questions, theme=GreenPassion())
+    return answers_model_info_request
+
+
+def custom_model_inquirer():
+    custom_model_load_questions = [
+        inquirer.Text(
+            "model_path",
+            message="Path to TTS model path",
+            default=None,
+        ),
+        inquirer.Text(
+            "model_config_path",
+            message="Path to TTS model config path",
+            default=None,
+        ),
+        inquirer.Text(
+            "vocoder_path",
+            message="Path to vocoder model file.",
+            default=None,
+        ),
+        inquirer.Text(
+            "vocoder_config_path",
+            message="Path to vocoder model config file.",
+            default=None,
+        ),
+        inquirer.Text(
+            "encoder_path",
+            message="Path to speaker encoder model file.",
+            default=None,
+        ),
+        inquirer.Text(
+            "encoder_config_path",
+            message="Path to speaker encoder config file.",
+            default=None,
+        ),
+        inquirer.List(
+            "use_cuda",
+            message="Run model on CUDA?",
+            choices=[True, False],
+            default=True,
+        ),
+    ]
+    answers_custom_model_load = inquirer.prompt(custom_model_load_questions, theme=GreenPassion())
+    return answers_custom_model_load
+
+
+def multispeaker_inquirer():
+    multispeaker_questions = [
+        inquirer.Text(
+            "speakers_file_path",
+            message="JSON file for multi-speaker model.",
+            default=None,
+        ),
+        inquirer.Text(
+            "language_ids_file_path",
+            message="JSON file for multi-lingual model.",
+            default=None,
+        ),
+        inquirer.Text("speaker_idx", message="Enter speaker idx", default=None),
+        inquirer.Text("language_idx", message="Enter language idx", default=None),
+        inquirer.Text("speaker_wav", message="Enter speaker wav file path", default=None),
+        inquirer.Text("reference_wav", message="Enter ref wav file path", default=None),
+        inquirer.Text("reference_speaker_idx", message="Enter reference speaker idx", default=None),
+    ]
+    answers_multispeaker = inquirer.prompt(multispeaker_questions, theme=GreenPassion())
+    return answers_multispeaker
+
+
+def capacitron_inquirer():
+    capacitron_questions = [
+        inquirer.Text("capacitron_style_wav", message="Enter capacitron style wav path", default=None),
+        inquirer.Text("capacitron_style_text", message="Enter capacitron style text", default=None),
+    ]
+    answers_capacitron = inquirer.prompt(capacitron_questions, theme=GreenPassion())
+    return answers_capacitron
+
+
+def continue_inquirer():
+    continue_questions = [
+        inquirer.List(
+            "to_do", message="What to do next?", choices=["try another text-input", "restart tts", "exit tts"]
+        ),
+    ]
+
+    continue_answers = inquirer.prompt(continue_questions, theme=GreenPassion())
+    return continue_answers
+
+
+def tts_inquirer(
+    synthesizer,
+    speaker_idx,
+    language_idx,
+    speaker_wav,
+    reference_wav,
+    reference_speaker_idx,
+    capacitron_style_wav,
+    capacitron_style_text,
+):
+    tts_questions = [
+        inquirer.Text(
+            "text_input",
+            message="Type text to convert to speech",
+        ),
+        inquirer.Text("out_path", message="Enter output wav path", default="tts_output.wav"),
+    ]
+    answers_tts = inquirer.prompt(tts_questions, theme=GreenPassion())
+    text = str2none(answers_tts["text_input"])
+    outpath = answers_tts["out_path"]
+    text = text if text is not None else "Enter random text."
+    print(f" > Text: {text}")
+    # kick it
+    wav = synthesizer.tts(
+        text,
+        speaker_idx,
+        language_idx,
+        speaker_wav,
+        reference_wav=reference_wav,
+        reference_speaker_name=reference_speaker_idx,
+        style_wav=capacitron_style_wav,
+        style_text=capacitron_style_text,
+    )
+
+    # save the results
+    print(f" > Saving output to {outpath}")
+    synthesizer.save_wav(wav, outpath)
+
+    continue_answers = continue_inquirer()
+    return continue_answers
+
+
+def block_prompt(synthesizer, isCapacitron=False):
+    speaker_idx = None
+    language_idx = None
+    speaker_wav = None
+    reference_wav = reference_wav = None
+    reference_speaker_idx = None
+    capacitron_style_wav = None
+    capacitron_style_text = None
+
+    if synthesizer.tts_speakers_file or hasattr(synthesizer.tts_model.speaker_manager, "ids"):
+        answers_multispeaker = multispeaker_inquirer()
+        for key, item in answers_multispeaker.items():
+            answers_multispeaker[key] = str2none(item)
+        speaker_idx = answers_multispeaker["speaker_idx"]
+        language_idx = answers_multispeaker["language_idx"]
+        speaker_wav = answers_multispeaker["speaker_wav"]
+        reference_wav = reference_wav = answers_multispeaker["reference_wav"]
+        reference_speaker_idx = answers_multispeaker["reference_speaker_idx"]
+
+    if isCapacitron:
+        answers_capacitron = capacitron_inquirer()
+        for key, item in answers_capacitron.items():
+            answers_capacitron[key] = str2none(item)
+        capacitron_style_wav = answers_capacitron["capacitron_style_wav"]
+        capacitron_style_text = answers_capacitron["capacitron_style_text"]
+
+    continue_answers = tts_inquirer(
+        synthesizer,
+        speaker_idx,
+        language_idx,
+        speaker_wav,
+        reference_wav,
+        reference_speaker_idx,
+        capacitron_style_wav,
+        capacitron_style_text,
+    )
+
+    if continue_answers["to_do"] == "exit tts":
+        return
+    if continue_answers["to_do"] == "restart tts":
+        print("restart")
+        init_prompt()
+    if continue_answers["to_do"] == "try another text-input":
+        block_prompt(synthesizer, isCapacitron=isCapacitron)
+
+
+def init_prompt():
+    model_path = None
+    config_path = None
+    speakers_file_path = None
+    language_ids_file_path = None
+    vocoder_path = None
+    vocoder_config_path = None
+    encoder_path = None
+    encoder_config_path = None
+    use_cuda = True
+    isCapacitron = False
+
+    init_questions = [
+        inquirer.List(
+            "to_do",
+            message="What do you need?",
+            choices=[
+                "get info from official model zoo",
+                "play with official model zoo",
+                "play with your own model",
+                "exit tts",
+            ],
+        ),
+    ]
+
+    init_answers = inquirer.prompt(init_questions, theme=GreenPassion())
+
+    if init_answers["to_do"] == "get info from official model zoo":
+        answers_model_load = official_zoo_info_inquirer()
+        manager.model_info_by_full_name(answers_model_load["model_choose_for_info"])
+
+    if init_answers["to_do"] == "exit tts":
+        return
+
+    if init_answers["to_do"] == "play with official model zoo":
+        answers_model_load = official_zoo_inquirer()
+        tts_model_name = answers_model_load["tts_choose"]
+        model_path, config_path, model_item = manager.download_model(tts_model_name)
+        vocoder_name = (
+            answers_model_load["vocoder_choose"]
+            if answers_model_load["vocoder_choose"] != "default_vocoder"
+            else model_item["default_vocoder"]
+        )
+        if vocoder_name is not None:
+            vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name)
+        use_cuda = answers_model_load["use_cuda"]
+
+        synthesizer = Synthesizer(
+            model_path,
+            config_path,
+            speakers_file_path,
+            language_ids_file_path,
+            vocoder_path,
+            vocoder_config_path,
+            encoder_path,
+            encoder_config_path,
+            use_cuda,
+        )
+
+        if "capacitron" in tts_model_name:
+            isCapacitron = True
+
+        block_prompt(synthesizer, isCapacitron=isCapacitron)
+
+    if init_answers["to_do"] == "play with your own model":
+        answers_custom_model_load = custom_model_inquirer()
+        for key, item in answers_custom_model_load.items():
+            answers_custom_model_load[key] = str2none(item)
+
+        model_path = answers_custom_model_load["model_path"]
+        config_path = answers_custom_model_load["model_config_path"]
+        vocoder_path = answers_custom_model_load["vocoder_path"]
+        vocoder_config_path = answers_custom_model_load["vocoder_config_path"]
+        encoder_path = answers_custom_model_load["encoder_path"]
+        encoder_config_path = answers_custom_model_load["encoder_config_path"]
+        use_cuda = answers_custom_model_load["use_cuda"]
+
+        synthesizer = Synthesizer(
+            model_path,
+            config_path,
+            speakers_file_path,
+            language_ids_file_path,
+            vocoder_path,
+            vocoder_config_path,
+            encoder_path,
+            encoder_config_path,
+            use_cuda,
+        )
+
+        if "use_capacitron_vae" in synthesizer.tts_config:  # find if model is capacitron
+            print("yes cap")
+            isCapacitron = True
+
+        block_prompt(synthesizer, isCapacitron=isCapacitron)
+
+
+def main():
+    from TTS.bin.frogie import ascii_art_printer
+
+    ascii_art_printer()
+    print("welcome to COQUI TTS")
+    init_prompt()
+
+
+if __name__ == "__main__":
+    main()