add arrow dataset

src/f5_tts/train/finetune_gradio.py

@@ -22,6 +22,7 @@
 import numpy as np
 import torch
 import torchaudio
+from datasets import load_dataset
 from datasets import Dataset as Dataset_
 from datasets.arrow_writer import ArrowWriter
 from safetensors.torch import save_file
@@ -31,6 +32,7 @@
 from f5_tts.api import F5TTS
 from f5_tts.model.utils import convert_char_to_pinyin
 from importlib.resources import files
+import soundfile as sf
 
 training_process = None
 system = platform.system()
@@ -44,6 +46,7 @@
 path_data = str(files("f5_tts").joinpath("../../data"))
 path_project_ckpts = str(files("f5_tts").joinpath("../../ckpts"))
 
+
 file_train = "src/f5_tts/train/finetune_cli.py"
 
 device = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
@@ -786,6 +789,65 @@ def has_supported_extension(file_name):
     return file_audio
 
 
+def get_nested_value(data, format):
+    keys = format.split("/")
+
+    item = data
+    for key in keys:
+        item = item.get(key)
+        if item is None:
+            return None
+
+    return item
+
+
+def create_metadata_from_arrow(
+    name_project, arrow_type, arrow_path, arrow_name, arrow_text, arrow_audio, arrow_split, progress=gr.Progress()
+):
+    path_project = os.path.join(path_data, name_project)
+    path_project_wavs = os.path.join(path_project, "wavs")
+    file_metadata = os.path.join(path_project, "metadata.csv")
+    file_custom_dataset_dir = os.path.join(path_project, "custom_dataset_dir")
+    os.makedirs(file_custom_dataset_dir, exist_ok=True)
+    os.makedirs(path_project_wavs, exist_ok=True)
+    data = ""
+    num = 0
+    if arrow_type == "Local" or arrow_type == "Online":
+        if arrow_type == "locals":
+            dataset = Dataset_.from_file(arrow_path)
+
+        if arrow_type == "Online":
+            if arrow_split == "":
+                arrow_split = None
+            if arrow_name == "":
+                arrow_name = None
+            dataset = load_dataset(arrow_path, arrow_name, split=arrow_split, cache_dir=file_custom_dataset_dir)
+
+        is_audio_path = None
+        for item in progress.tqdm(dataset):
+            text = get_nested_value(item, arrow_text)
+            audio = get_nested_value(item, arrow_audio)
+
+            if is_audio_path is None:
+                if isinstance(audio, str):
+                    is_audio_path = True
+                else:
+                    is_audio_path = False
+
+            if not is_audio_path:
+                namefile = "segment_{num}"
+                filename = os.path.join(path_project_wavs, namefile + ".wav")
+                sf.write(filename, audio, 24000)
+                num += 1
+            else:
+                filename = audio
+
+            data += f"{filename}|{text}\n"
+
+        with open(file_metadata, "w", encoding="utf-sig") as f:
+            f.write(data)
+
+
 def create_metadata(name_project, ch_tokenizer, progress=gr.Progress()):
     path_project = os.path.join(path_data, name_project)
     path_project_wavs = os.path.join(path_project, "wavs")
@@ -1505,6 +1567,18 @@ def get_audio_select(file_sample):
 Skip this step if you have your dataset, raw.arrow, duration.json, and vocab.txt
 ```""")
 
+            with gr.Accordion("Dataset Arrow", open=False):
+                arrow_type = gr.Radio(label="Type", choices=["Local", "Online"], value="Local")
+                with gr.Row():
+                    arrow_path = gr.Textbox(label="Path", value="")
+                    arrow_name = gr.Textbox(label="Name", value="")
+                    arrow_split = gr.Textbox(label="Split", value="")
+
+                with gr.Row():
+                    arrow_text = gr.Textbox(label="Text", value="audio/array")
+                    arrow_audio = gr.Textbox(label="Audio", value="transcript")
+                    bt_covert_metadata = bt_create = gr.Button("Create Metadata")
+
             gr.Markdown(
                 """```plaintext    
      Place all your "wavs" folder and your "metadata.csv" file in your project name directory.
@@ -1530,6 +1604,7 @@ def get_audio_select(file_sample):
      ```"""
             )
             ch_tokenizern = gr.Checkbox(label="Create Vocabulary", value=False, visible=False)
+
             bt_prepare = bt_create = gr.Button("Prepare")
             txt_info_prepare = gr.Text(label="Info", value="")
             txt_vocab_prepare = gr.Text(label="Vocab", value="")
@@ -1538,6 +1613,12 @@ def get_audio_select(file_sample):
                 fn=create_metadata, inputs=[cm_project, ch_tokenizern], outputs=[txt_info_prepare, txt_vocab_prepare]
             )
 
+            bt_covert_metadata.click(
+                fn=create_metadata_from_arrow,
+                inputs=[cm_project, arrow_type, arrow_path, arrow_name, arrow_text, arrow_audio, arrow_split],
+                outputs=[],
+            )
+
             random_sample_prepare = gr.Button("Random Sample")
 
             with gr.Row():