diff --git a/app.py b/app.py
index 402e691..c48cff7 100644
--- a/app.py
+++ b/app.py
@@ -1,7 +1,8 @@
import gradio as gr
from modules.whisper_Inference import WhisperInference
+from modules.nllb_inference import NLLBInference
import os
-from ui.htmls import CSS, MARKDOWN
+from ui.htmls import *
from modules.youtube_manager import get_ytmetas
@@ -21,6 +22,7 @@ def on_change_models(model_size):
whisper_inf = WhisperInference()
+nllb_inf = NLLBInference()
block = gr.Blocks(css=CSS).queue(api_open=False)
with block:
@@ -100,4 +102,29 @@ with block:
btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
+ with gr.TabItem("T2T Translation"): # tab 4
+ with gr.Row():
+ file_subs = gr.Files(type="file", label="Upload Subtitle Files to translate here",
+ file_types=['.vtt', '.srt'])
+
+ with gr.TabItem("NLLB"): # sub tab1
+ with gr.Row():
+ dd_nllb_model = gr.Dropdown(label="Model", value=nllb_inf.default_model_size,
+ choices=nllb_inf.available_models)
+ dd_nllb_sourcelang = gr.Dropdown(label="Source Language", choices=nllb_inf.available_source_langs)
+ dd_nllb_targetlang = gr.Dropdown(label="Target Language", choices=nllb_inf.available_target_langs)
+ with gr.Row():
+ btn_run = gr.Button("TRANSLATE SUBTITLE FILE", variant="primary")
+ with gr.Row():
+ tb_indicator = gr.Textbox(label="Output")
+ btn_openfolder = gr.Button('📂').style(full_width=False)
+ with gr.Column():
+ md_vram_table = gr.HTML(NLLB_VRAM_TABLE, elem_id="md_nllb_vram_table")
+
+ btn_run.click(fn=nllb_inf.translate_file,
+ inputs=[file_subs, dd_nllb_model, dd_nllb_sourcelang, dd_nllb_targetlang],
+ outputs=[tb_indicator])
+ btn_openfolder.click(fn=lambda: open_fodler("outputs\\translations"), inputs=None, outputs=None)
+
+
block.launch()
diff --git a/modules/nllb_inference.py b/modules/nllb_inference.py
index 9646fed..2595ff7 100644
--- a/modules/nllb_inference.py
+++ b/modules/nllb_inference.py
@@ -68,7 +68,7 @@ class NLLBInference:
write_file(subtitle, f"{output_path}.srt")
- elif file_path == ".vtt":
+ elif file_ext == ".vtt":
parsed_dicts = parse_vtt(file_path=file_path)
total_progress = len(parsed_dicts)
for index, dic in enumerate(parsed_dicts):
diff --git a/outputs/translations/outputs for translation are saved here.txt b/outputs/translations/outputs for translation are saved here.txt
new file mode 100644
index 0000000..e69de29
diff --git a/ui/htmls.py b/ui/htmls.py
index e4947fc..e0b028c 100644
--- a/ui/htmls.py
+++ b/ui/htmls.py
@@ -39,4 +39,59 @@ CSS = """
MARKDOWN = """
### [Whisper Web-UI](https://github.com/jhj0517/Whsiper-WebUI)
+"""
+
+
+NLLB_VRAM_TABLE = """
+
+
+
+
+
+
+
+
+
+
+ VRAM usage for each model
+
+
+
+ | Model name |
+ Required VRAM |
+
+
+
+
+ | nllb-200-3.3B |
+ ~16GB |
+
+
+ | nllb-200-1.3B |
+ ~8GB |
+
+
+ | nllb-200-distilled-600M |
+ ~4GB |
+
+
+
+ Note: Be mindful of your VRAM! The table above provides an approximate VRAM usage for each model.
+
+
+
+
"""
\ No newline at end of file