Duplicate from Omnibus/Bark-simple

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README.md

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+---
+title: Bark Simple
+emoji: 🐕
+colorFrom: red
+colorTo: gray
+sdk: gradio
+sdk_version: 3.41.2
+app_file: app.py
+duplicated_from: Omnibus/Bark-simple
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+from pathlib import Path
+from transformers import AutoProcessor, BarkModel
+import scipy
+from pytube import YouTube
+from pydub import AudioSegment
+from TTS.api import TTS
+#import ffmpeg
+
+
+# device = "cuda" if torch.cuda.is_available() else "cpu"
+# model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16).to(device)
+# model.enable_cpu_offload()
+
+device = "cpu"
+
+
+processor = AutoProcessor.from_pretrained("suno/bark-small")
+model = BarkModel.from_pretrained("suno/bark-small").to(device)
+num_list = ["1","2","3","4","5","6","7","8","9","10"]
+lang_list = ["en","de"]
+
+def run_bark(text, n, lang):
+    #history_prompt = []
+    semantic_prompt=f"v2/{lang}_speaker_{int(n)-1}"
+
+        #text=["Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as playing tic tac toe."],
+    inputs = processor(text=text,
+        voice_preset = semantic_prompt,
+        return_tensors="pt",
+    )
+    
+    speech_values = model.generate(**inputs, do_sample=True)
+    sampling_rate = model.generation_config.sample_rate
+
+    #sampling_rate = model.config.sample_rate
+    #sampling_rate = 24000
+    scipy.io.wavfile.write("bark_out.wav", rate=sampling_rate, data=speech_values.cpu().numpy().squeeze())
+    return ("bark_out.wav")
+
+def custom_bark(inp):
+    speaker_wav=Path("Mid.mp3")
+    tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False).to(device)
+    tts.tts_to_file(inp, speaker_wav=speaker_wav, language="en", file_path="output.wav")
+    return ("output.wav")
+    
+def load_video_yt(vid):
+    yt = YouTube(vid)
+    vid = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().first().download(filename="tmp.mp4")
+    vid_aud = yt.streams.filter(only_audio=True)[0].download(filename="tmp_aud.mp4")
+    print (yt.length)
+    return vid, vid_aud, "tmp_aud.mp4"
+
+def trim_clip(clip, start_t, end_t):
+    clip = Path("tmp_aud.mp4")
+    #clip = "tmp_aud.mp3"
+    # Open an mp3 file
+    song = AudioSegment.from_file("tmp_aud.mp4", 
+                                  format="mp4")
+      
+    # start and end time
+    #start_min = 0
+    #start_sec = 10
+    #end_min = 0
+    #end_sec = 55
+    start_min = int(start_t.split(":",1)[0])
+    start_sec = int(start_t.split(":",1)[1])
+    end_min = int(end_t.split(":",1)[0])
+    end_sec = int(end_t.split(":",1)[1])
+    # pydub does things in milliseconds, so convert time
+    start = ((start_min*60)+start_sec)*1000
+    end = ((end_min*60)+end_sec)*1000
+    #start = 0
+    #end = 15*1000
+    # song clip of 10 seconds from starting
+    first_10_seconds = song[start: end]
+      
+    # save file
+    first_10_seconds.export("Mid.mp3", format="mp3")
+    print("New Audio file is created and saved")
+
+    return "Mid.mp3"
+    
+with gr.Blocks() as app:
+    with gr.Column():
+        in_text = gr.Textbox()
+        with gr.Tab("Default"):
+            with gr.Row():
+                speaker_num = gr.Dropdown(label="Speaker Voice", choices=num_list,value="1")
+                speaker_lang = gr.Dropdown(label="Speaker Language", choices=lang_list,value="en")
+            go_btn = gr.Button()
+        with gr.Tab("Upload"):
+            with gr.Row():
+                with gr.Column():
+                    in_aud_mic = gr.Audio(source='microphone')
+                    in_aud_file = gr.Audio(source='upload', interactive = True)
+                    aud_file = gr.File()
+                with gr.Column():
+                    in_aud_yt = gr.Textbox(label="YouTube URL")
+                    load_yt_btn = gr.Button("Load URL")
+                with gr.Column():
+                    with gr.Row():
+                        start_time = gr.Textbox(label = "Start", value = "0:00", placeholder = "0:23")
+                        end_time = gr.Textbox(label = "End", value = "0:01", placeholder = "1:12")
+                        
+                    trim_clip_btn = gr.Button("Trim Clip")
+                    trim_aud = gr.Audio(source='upload', interactive = False)
+            alt_go_btn = gr.Button()
+            yt_vid = gr.Video(type = 'filepath')
+        #speaker_num = gr.Number(value=0)
+
+    with gr.Column():
+        out_audio = gr.Audio()
+
+    go_btn.click(run_bark,[in_text, speaker_num, speaker_lang],out_audio)
+    load_yt_btn.click(load_video_yt, in_aud_yt, [yt_vid,in_aud_file,aud_file])
+    trim_clip_btn.click(trim_clip,[aud_file, start_time, end_time],trim_aud)
+    alt_go_btn.click(custom_bark, in_text, out_audio)
+
+app.launch()

requirements.txt

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+torch
+transformers
+scipy
+pytube
+moviepy
+TTS