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| # 👇 COPY FROM HERE | |
| import os | |
| import tempfile | |
| import streamlit as st | |
| import cv2 | |
| import numpy as np | |
| import whisper | |
| from moviepy.editor import * | |
| from moviepy.video.fx.all import crop | |
| from scenedetect import detect, ContentDetector | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| os.environ["TOKENIZERS_PARALLELISM"] = "false" | |
| def load_whisper_model(): | |
| return whisper.load_model("base") | |
| def detect_engaging_scenes(video_path, num_scenes=5): | |
| scene_list = detect(video_path, ContentDetector(min_scene_len=15)) | |
| return [(s[0].get_seconds(), s[1].get_seconds()) for s in scene_list][:num_scenes] | |
| def detect_face_center(frame): | |
| face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml') | |
| gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
| faces = face_cascade.detectMultiScale(gray, 1.1, 4) | |
| if len(faces) > 0: | |
| x, y, w, h = faces[0] | |
| return (x + w//2, y + h//2) | |
| return None | |
| def create_vertical_short(original_clip, scene, transcript, bg_music_path, idx): | |
| start_time, end_time = scene | |
| duration = end_time - start_time | |
| clip = original_clip.subclip(start_time, end_time) | |
| mid_time = start_time + duration/2 | |
| try: | |
| frame = original_clip.get_frame(mid_time) | |
| frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) | |
| face_center = detect_face_center(frame) | |
| except: | |
| face_center = None | |
| w, h = clip.size | |
| target_width = min(w, int(h * 9/16)) | |
| target_height = min(h, int(w * 16/9)) | |
| if face_center: | |
| x_center, y_center = face_center | |
| x1 = max(0, x_center - target_width//2) | |
| x2 = min(w, x_center + target_width//2) | |
| y1 = max(0, y_center - target_height//2) | |
| y2 = min(h, y_center + target_height//2) | |
| else: | |
| x1 = (w - target_width) // 2 | |
| x2 = x1 + target_width | |
| y1 = (h - target_height) // 2 | |
| y2 = y1 + target_height | |
| cropped_clip = crop(clip, x1=x1, y1=y1, x2=x2, y2=y2) | |
| vertical_clip = cropped_clip.resize((1080, 1920)) | |
| caption_text = "" | |
| for seg in transcript['segments']: | |
| seg_start = seg['start'] | |
| seg_end = seg['end'] | |
| if seg_start >= start_time and seg_end <= end_time: | |
| caption_text += seg['text'] + " " | |
| words = caption_text.split() | |
| if len(words) > 8: | |
| line1 = " ".join(words[:len(words)//2]) | |
| line2 = " ".join(words[len(words)//2:]) | |
| else: | |
| line1 = caption_text | |
| line2 = "" | |
| txt_clip1 = TextClip(line1, fontsize=60, color='white', font='Arial-Bold', | |
| stroke_color='black', stroke_width=2, size=(1000, 100)).set_position(('center', 1400)).set_duration(duration) | |
| caption_clips = [txt_clip1] | |
| if line2: | |
| txt_clip2 = TextClip(line2, fontsize=60, color='white', font='Arial-Bold', | |
| stroke_color='black', stroke_width=2, size=(1000, 100)).set_position(('center', 1480)).set_duration(duration) | |
| caption_clips.append(txt_clip2) | |
| bg_music = AudioFileClip(bg_music_path).volumex(0.2) | |
| if bg_music.duration < duration: | |
| bg_music = afx.audio_loop(bg_music, duration=duration) | |
| else: | |
| bg_music = bg_music.subclip(0, duration) | |
| original_audio = vertical_clip.audio.volumex(0.8) | |
| final_audio = CompositeAudioClip([original_audio, bg_music]) | |
| final_clip = CompositeVideoClip([vertical_clip] + caption_clips) | |
| final_clip = final_clip.set_audio(final_audio) | |
| output_path = f"short_{idx+1}.mp4" | |
| final_clip.write_videofile(output_path, codec="libx264", audio_codec="aac", fps=24, threads=4, | |
| preset='ultrafast', ffmpeg_params=["-crf", "28"]) | |
| return output_path | |
| def main(): | |
| st.set_page_config(page_title="YouTube Shorts Generator", page_icon="🎬", layout="centered") | |
| st.title("🎬 YouTube Shorts Generator") | |
| st.subheader("Create Vertical AI Shorts from Any Video") | |
| st.info(""" | |
| **🎥 Can't paste YouTube link directly?** | |
| 👉 Use our [Google Colab YouTube Downloader](https://colab.research.google.com/drive/1Sy52KiOtN-l7N2rZ8A2JcmW0gYOYFMLx) | |
| Paste your link, download `.mp4`, then upload it below 👇 | |
| """) | |
| uploaded_file = st.file_uploader("📁 Upload a YouTube video (.mp4)", type=["mp4"]) | |
| if st.button("Generate Shorts", type="primary", use_container_width=True): | |
| if not uploaded_file: | |
| st.warning("Please upload a video first.") | |
| return | |
| bg_music_path = "background_music.mp3" | |
| if not os.path.exists(bg_music_path): | |
| st.error("Missing background music: background_music.mp3") | |
| return | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp: | |
| tmp.write(uploaded_file.read()) | |
| video_path = tmp.name | |
| with st.status("Processing...", expanded=True) as status: | |
| try: | |
| original_clip = VideoFileClip(video_path) | |
| duration = original_clip.duration | |
| st.success(f"Video loaded: {duration:.1f} sec") | |
| scenes = detect_engaging_scenes(video_path) | |
| if len(scenes) < 5: | |
| st.warning("Less than 5 scenes detected, using time slices instead") | |
| scenes = [(i*15, min((i+1)*15, duration)) for i in range(5)] | |
| else: | |
| scenes = scenes[:5] | |
| st.success("Scenes selected") | |
| audio_path = video_path.replace(".mp4", ".wav") | |
| original_clip.audio.write_audiofile(audio_path, logger=None) | |
| model = load_whisper_model() | |
| transcript = model.transcribe(audio_path) | |
| st.success(f"Transcribed {len(transcript['segments'])} segments") | |
| output_files = [] | |
| for i, scene in enumerate(scenes): | |
| st.write(f"Creating Short {i+1}/5...") | |
| output = create_vertical_short(original_clip, scene, transcript, bg_music_path, i) | |
| output_files.append(output) | |
| st.success(f"Short {i+1} done ✅") | |
| status.update(label="All Shorts Ready!", state="complete") | |
| except Exception as e: | |
| st.error(f"Error: {str(e)}") | |
| return | |
| st.balloons() | |
| st.subheader("🎉 Download Your Shorts") | |
| cols = st.columns(5) | |
| for i, file in enumerate(output_files): | |
| with open(file, "rb") as f: | |
| cols[i].download_button(f"Short {i+1}", f, file_name=file, mime="video/mp4") | |
| original_clip.close() | |
| os.remove(video_path) | |
| if os.path.exists(audio_path): | |
| os.remove(audio_path) | |
| for file in output_files: | |
| os.remove(file) | |
| if __name__ == "__main__": | |
| main() | |
| # 👆 TO HERE | |