create app.py

app.py

@@ -0,0 +1,126 @@
+!pip install -U openai-whisper
+!pip install -U git+https://github.com/linto-ai/whisper-timestamped
+!pip install gradio moviepy whisper-timestamped
+
+import os
+import datetime as dt
+import json
+import whisper_timestamped as whisper
+from moviepy.video.io.VideoFileClip import VideoFileClip
+import gradio as gr
+
+# Helper functions and global variables
+outdir = dt.datetime.now().strftime("%Y%m%d%H%M")
+if os.path.exists(outdir):
+    random_digits = str(random.randint(1000, 9999))
+    new_outdir = outdir + random_digits
+    os.mkdir(new_outdir)
+    outdir = new_outdir
+    print("Created new output directory:", new_outdir)
+else:
+    os.system(f"mkdir {outdir}")
+print("date time now:" + outdir)
+
+model = whisper.load_model("base")
+
+def generate_timestamps(vidname):
+    audio = whisper.load_audio(vidname)
+    result = whisper.transcribe(model, audio, language="en")
+    return result
+
+def get_segment_info(data):
+    new_list = []
+    for segment in data.get("segments", []):
+        if "id" in segment and "start" in segment and "end" in segment and "text" in segment:
+            new_item = {
+                "id": segment["id"],
+                "start": segment["start"],
+                "end": segment["end"],
+                "text": segment["text"]
+            }
+            new_list.append(new_item)
+    return new_list
+
+def combine_entries(entries):
+    combined_entries = []
+    current_entry = None
+    total_duration = 0
+
+    for entry in entries:
+        entry_duration = entry["end"] - entry["start"]
+
+        if total_duration + entry_duration > 30:
+            if current_entry:
+                current_entry["end"] = entry["end"]
+                combined_entries.append(current_entry)
+
+            current_entry = {
+                "start": entry["start"],
+                "end": entry["end"],
+                "text": entry["text"]
+            }
+            total_duration = entry_duration
+        else:
+            if current_entry:
+                current_entry["end"] = entry["end"]
+                current_entry["text"] += " " + entry["text"]
+                total_duration += entry_duration
+            else:
+                current_entry = {
+                    "start": entry["start"],
+                    "end": entry["end"],
+                    "text": entry["text"]
+                }
+                total_duration = entry_duration
+
+    if current_entry:
+        combined_entries.append(current_entry)
+
+    return combined_entries
+
+def extract_video_segment(input_video, output_video, start_time, end_time):
+    video_clip = VideoFileClip(input_video).subclip(start_time, end_time)
+    video_clip.write_videofile(output_video, codec="libx264", audio_codec="aac")
+    video_clip.close()
+
+def save_segments(outdir, name, combined_entries):
+    segments = combined_entries
+    input_video = name
+    for i, segment in enumerate(segments):
+        start_time = segment['start']
+        end_time = segment['end']
+        output_video_file = f'{outdir}/output_segment_{i + 1}.mp4'
+        extract_video_segment(input_video, output_video_file, start_time, end_time)
+
+def split_up_video(video_path, output_dir):
+    result = generate_timestamps(video_path)
+    combined_entries = combine_entries(get_segment_info(result))
+
+    scribeout = open(f"{output_dir}/transcript.txt", "w")
+    scribeout.write(json.dumps(combined_entries, indent=2, ensure_ascii=False))
+    scribeout.close()
+
+    save_segments(output_dir, video_path, combined_entries)
+
+    filename, extension = os.path.splitext(video_path)
+    os.system(f"zip -r {filename}.zip {output_dir}")
+
+    return f"{filename}.zip"
+
+# Gradio interface
+def process_video(video):
+    output_dir = dt.datetime.now().strftime("%Y%m%d%H%M")
+    os.mkdir(output_dir)
+    video_path = video.name
+    output_zip = split_up_video(video_path, output_dir)
+    return output_zip
+
+iface = gr.Interface(
+    fn=process_video,
+    inputs=gr.File(file_count="single", type="filepath", label="Upload a Video"),
+    outputs=gr.File(label="Download Zipped Segments and Transcript"),
+    title="Video Splitter",
+    description="Upload a video and get a zipped file with segmented videos and a transcript."
+)
+
+iface.launch()