SRT

app.py

@@ -1,26 +1,36 @@
+import whisper
 import gradio as gr
-import shutil
 
-# Function to display the video and return a downloadable file
-def upload_and_download(video_file):
-    # Get the file name of the uploaded video
-    video_file_path = video_file.name
-    video_file_name = video_file_path.split('/')[-1]
-    
-    # Create a downloadable copy of the video file
-    downloaded_file = f"downloaded_{video_file_name}"
-    shutil.copy(video_file_path, downloaded_file)
-    
-    # Return the video file and a downloadable link
-    return video_file_path, downloaded_file
+# Load the Whisper model
+model = whisper.load_model("base")  # Choose 'tiny', 'base', 'small', 'medium', or 'large'
 
-# Gradio interface
-interface = gr.Interface(
-    fn=upload_and_download,
-    inputs=gr.Video(label="Upload your video"),  # Video input
-    outputs=[gr.Video(label="Uploaded Video"), gr.File(label="Download Video")],  # Show video and download link
-    title="Video Uploader and Downloader"
+def transcribe_video(video_file):
+    # Transcribe the video to generate subtitles
+    result = model.transcribe(video_file)
+
+    # Create the SRT file content
+    srt_content = ""
+    for i, segment in enumerate(result['segments']):
+        start = segment['start']
+        end = segment['end']
+        text = segment['text']
+        # Format timestamps for SRT
+        start_time = whisper.utils.format_timestamp(start)
+        end_time = whisper.utils.format_timestamp(end)
+        srt_content += f"{i + 1}\n"
+        srt_content += f"{start_time} --> {end_time}\n"
+        srt_content += f"{text.strip()}\n\n"
+
+    return srt_content
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=transcribe_video,
+    inputs=gr.Video(label="Upload Video"),
+    outputs=gr.File(label="Download Subtitles"),
+    title="Video Transcription to SRT",
+    description="Upload a video file, and this tool will transcribe it and generate SRT subtitles."
 )
 
 # Launch the Gradio app
-interface.launch()
+iface.launch()