fahadqazi commited on
Commit
2845ac7
·
1 Parent(s): 2b45ac4

removed youtube dlp

Browse files
Files changed (1) hide show
  1. app.py +9 -22
app.py CHANGED
@@ -6,7 +6,6 @@ import requests
6
  from moviepy import VideoFileClip
7
  from transformers import pipeline, WhisperProcessor, WhisperForConditionalGeneration, Wav2Vec2Processor, Wav2Vec2Model
8
  import torchaudio
9
- import yt_dlp as youtube_dl
10
 
11
  # Load Whisper model to confirm English
12
  whisper_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device="cpu")
@@ -22,25 +21,13 @@ def classify_accent(audio_tensor, sample_rate):
22
  }
23
 
24
  def download_video(url):
25
- if "youtube.com" in url or "youtu.be" in url:
26
- ydl_opts = {
27
- 'format': 'best[ext=mp4]',
28
- 'outtmpl': tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name,
29
- 'quiet': True,
30
- 'noplaylist': True,
31
- }
32
-
33
- with youtube_dl.YoutubeDL(ydl_opts) as ydl:
34
- info = ydl.extract_info(url, download=True)
35
- return ydl.prepare_filename(info)
36
- else:
37
- video_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
38
- response = requests.get(url, stream=True)
39
- with open(video_path, "wb") as f:
40
- for chunk in response.iter_content(chunk_size=1024*1024):
41
- if chunk:
42
- f.write(chunk)
43
- return video_path
44
 
45
  def extract_audio(video_path):
46
  audio_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name
@@ -83,8 +70,8 @@ def analyze_accent(url):
83
 
84
  gr.Interface(
85
  fn=analyze_accent,
86
- inputs=gr.Textbox(label="Public Video URL (e.g. MP4, Loom)", placeholder="https://..."),
87
  outputs=gr.Markdown(label="Accent Analysis Result"),
88
  title="English Accent Classifier",
89
- description="Paste a video URL (MP4/Loom) to extract audio, transcribe speech, and classify the English accent (e.g., American, British, etc.)."
90
  ).launch()
 
6
  from moviepy import VideoFileClip
7
  from transformers import pipeline, WhisperProcessor, WhisperForConditionalGeneration, Wav2Vec2Processor, Wav2Vec2Model
8
  import torchaudio
 
9
 
10
  # Load Whisper model to confirm English
11
  whisper_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device="cpu")
 
21
  }
22
 
23
  def download_video(url):
24
+ video_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
25
+ response = requests.get(url, stream=True)
26
+ with open(video_path, "wb") as f:
27
+ for chunk in response.iter_content(chunk_size=1024*1024):
28
+ if chunk:
29
+ f.write(chunk)
30
+ return video_path
 
 
 
 
 
 
 
 
 
 
 
 
31
 
32
  def extract_audio(video_path):
33
  audio_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name
 
70
 
71
  gr.Interface(
72
  fn=analyze_accent,
73
+ inputs=gr.Textbox(label="Public Video URL (e.g. MP4)", placeholder="https://..."),
74
  outputs=gr.Markdown(label="Accent Analysis Result"),
75
  title="English Accent Classifier",
76
+ description="Paste a video URL (MP4) to extract audio, transcribe speech, and classify the English accent (e.g., American, British, etc.)."
77
  ).launch()