Create utils/clip_detector.py

utils/clip_detector.py

@@ -0,0 +1,200 @@
+import numpy as np
+from transformers import pipeline
+import re
+
+class ClipDetector:
+    def __init__(self):
+        # Load emotion detection model
+        self.emotion_classifier = pipeline(
+            "text-classification",
+            model="j-hartmann/emotion-english-distilroberta-base",
+            return_all_scores=True
+        )
+    
+    def find_engaging_segments(self, video_path, transcript, max_clips=10):
+        """Detect engaging segments from video using multiple signals"""
+        segments = []
+        
+        for i, segment in enumerate(transcript['segments']):
+            # Skip very short segments
+            duration = segment['end'] - segment['start']
+            if duration < 20 or duration > 90:  # 20-90 seconds ideal for shorts
+                continue
+            
+            text = segment['text']
+            
+            # Analyze emotion
+            emotions = self.emotion_classifier(text[:512])[0]
+            emotion_scores = {e['label']: e['score'] for e in emotions}
+            
+            # Calculate engagement score
+            engagement_score = self._calculate_engagement(
+                text,
+                emotion_scores,
+                duration
+            )
+            
+            # Detect hooks
+            hook = self._detect_hook(text)
+            
+            # Generate title
+            title = self._generate_title(text, emotion_scores)
+            
+            # Determine caption style based on emotion
+            caption_style = self._determine_caption_style(emotion_scores)
+            
+            # Suggest sound effects
+            sound_effects = self._suggest_sound_effects(emotion_scores, text)
+            
+            segments.append({
+                'start': segment['start'],
+                'end': segment['end'],
+                'start_time': self._format_time(segment['start']),
+                'end_time': self._format_time(segment['end']),
+                'duration': self._format_duration(duration),
+                'text': text,
+                'emotions': emotion_scores,
+                'engagement_score': engagement_score,
+                'hook': hook,
+                'title': title,
+                'caption_style': caption_style,
+                'sound_effects': sound_effects,
+                'emotion': max(emotion_scores, key=emotion_scores.get)
+            })
+        
+        # Sort by engagement score
+        segments.sort(key=lambda x: x['engagement_score'], reverse=True)
+        
+        return segments[:max_clips]
+    
+    def _calculate_engagement(self, text, emotions, duration):
+        """Calculate engagement score based on multiple factors"""
+        score = 0
+        
+        # Emotional intensity (excitement, surprise, joy)
+        score += emotions.get('joy', 0) * 30
+        score += emotions.get('surprise', 0) * 35
+        score += emotions.get('anger', 0) * 20  # Controversy can be engaging
+        
+        # Hook words
+        hook_words = ['wait', 'watch', 'look', 'amazing', 'incredible', 'shocking', 
+                      'unbelievable', 'secret', 'reveal', 'must', 'never']
+        hook_count = sum(1 for word in hook_words if word in text.lower())
+        score += hook_count * 5
+        
+        # Question marks (engagement)
+        score += text.count('?') * 3
+        
+        # Ideal duration bonus (30-60 seconds)
+        if 30 <= duration <= 60:
+            score += 10
+        
+        # Numbers (concrete, specific)
+        if re.search(r'\d+', text):
+            score += 5
+        
+        return min(score, 100)
+    
+    def _detect_hook(self, text):
+        """Detect or generate a hook for the clip"""
+        text_lower = text.lower()
+        
+        # Common hook patterns
+        if 'wait' in text_lower:
+            return '"Wait until you see this..."'
+        elif 'how' in text_lower or 'why' in text_lower:
+            return '"You need to know this..."'
+        elif 'never' in text_lower:
+            return '"This changes everything..."'
+        elif '?' in text:
+            sentences = text.split('.')
+            for s in sentences:
+                if '?' in s:
+                    return f'"{s.strip()}"'
+        
+        # Extract first compelling sentence
+        sentences = text.split('.')
+        if sentences:
+            return f'"{sentences[0].strip()}..."'
+        
+        return '"Watch what happens next..."'
+    
+    def _generate_title(self, text, emotions):
+        """Generate catchy title based on content and emotion"""
+        top_emotion = max(emotions, key=emotions.get)
+        
+        emotion_emojis = {
+            'joy': '🎉',
+            'surprise': '😱',
+            'anger': '😤',
+            'sadness': '😢',
+            'fear': '😨',
+            'disgust': '🤢',
+            'neutral': '🎯'
+        }
+        
+        emoji = emotion_emojis.get(top_emotion, '✨')
+        
+        # Extract key words
+        words = text.split()[:10]
+        
+        if 'amazing' in text.lower() or 'incredible' in text.lower():
+            return f'{emoji} Mind-Blowing Moment'
+        elif 'fail' in text.lower() or 'wrong' in text.lower():
+            return f'{emoji} Epic Fail'
+        elif 'how' in text.lower() or 'why' in text.lower():
+            return f'{emoji} Life-Changing Tip'
+        elif '?' in text:
+            return f'{emoji} The Answer Revealed'
+        else:
+            return f'{emoji} Must-Watch Moment'
+    
+    def _determine_caption_style(self, emotions):
+        """Determine caption color/style based on emotion"""
+        top_emotion = max(emotions, key=emotions.get)
+        
+        styles = {
+            'joy': 'Bold Yellow with Pop',
+            'surprise': 'Red Bold with Shake',
+            'anger': 'Orange Bold with Pulse',
+            'sadness': 'Blue Soft',
+            'fear': 'Purple Bold',
+            'neutral': 'White Bold with Glow'
+        }
+        
+        return styles.get(top_emotion, 'White Bold')
+    
+    def _suggest_sound_effects(self, emotions, text):
+        """Suggest appropriate sound effects"""
+        effects = []
+        top_emotion = max(emotions, key=emotions.get)
+        
+        # Emotion-based effects
+        if top_emotion == 'surprise':
+            effects.extend(['Dramatic Boom', 'Record Scratch'])
+        elif top_emotion == 'joy':
+            effects.extend(['Success Ding', 'Celebration'])
+        elif top_emotion == 'anger':
+            effects.extend(['Dramatic Whoosh', 'Impact'])
+        
+        # Text-based effects
+        if any(word in text.lower() for word in ['wait', 'watch', 'look']):
+            effects.append('Suspense Build')
+        
+        if '?' in text:
+            effects.append('Thinking Sound')
+        
+        if not effects:
+            effects = ['Whoosh', 'Transition']
+        
+        return effects[:3]  # Max 3 effects
+    
+    def _format_time(self, seconds):
+        """Format seconds to MM:SS"""
+        mins = int(seconds // 60)
+        secs = int(seconds % 60)
+        return f"{mins}:{secs:02d}"
+    
+    def _format_duration(self, seconds):
+        """Format duration"""
+        return f"0:{int(seconds):02d}"