Create app.py

app.py

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+import gradio as gr
+import moviepy.editor as mp
+import numpy as np
+import librosa
+from PIL import Image, ImageDraw
+import tempfile
+import os
+import logging
+
+# Configuración de logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s',
+    handlers=[logging.StreamHandler()]
+)
+logger = logging.getLogger("audio_to_video")
+
+def generate_video(audio_file, image_file):
+    try:
+        # 1. Cargar audio
+        y, sr = librosa.load(audio_file)
+        duration = librosa.get_duration(y=y, sr=sr)
+        logger.info(f"Audio cargado: {duration:.1f} segundos")
+
+        # 2. Cargar imagen
+        img = Image.open(image_file).convert('RGB')
+        img_w, img_h = img.size
+        logger.info(f"Imagen cargada: {img_w}x{img_h}")
+
+        # 3. Analizar audio
+        audio_envelope = np.abs(y) / np.max(np.abs(y))  # Normalizar
+        audio_envelope_zoom = audio_envelope * 0.2 + 0.9  # Escalar para zoom (0.9x a 1.1x)
+        audio_envelope_wave = audio_envelope * (img_h // 6)  # Para el waveform
+
+        # 4. Generar frames con zoom y waveform
+        def make_frame(t):
+            # Calcular posición en el audio
+            time_idx = int(t * sr)
+            
+            # --- Efecto de Zoom ---
+            zoom_factor = audio_envelope_zoom[time_idx] if time_idx < len(audio_envelope_zoom) else 1.0
+            new_size = (int(img_w * zoom_factor), int(img_h * zoom_factor))
+            zoomed_img = img.resize(new_size, Image.LANCZOS)
+            
+            # Centrar la imagen ampliada
+            x_offset = (new_size[0] - img_w) // 2
+            y_offset = (new_size[1] - img_h) // 2
+            cropped_img = zoomed_img.crop((
+                x_offset,
+                y_offset,
+                x_offset + img_w,
+                y_offset + img_h
+            ))
+
+            # --- Dibujar Waveform ---
+            frame = ImageDraw.Draw(cropped_img)
+            
+            # Posición vertical del waveform (abajo)
+            start_y = int(img_h * 0.75)  # 75% hacia abajo
+            
+            # Extraer slice de audio
+            start = max(0, time_idx - sr//10)
+            end = min(len(audio_envelope_wave), time_idx + sr//10)
+            wave_slice = audio_envelope_wave[start:end]
+            
+            # Dibujar onda
+            points = []
+            for i, val in enumerate(wave_slice):
+                x = int((i / len(wave_slice)) * img_w)
+                y_pos = start_y - int(val)
+                y_neg = start_y + int(val)
+                points.extend([(x, y_pos), (x, y_neg)])
+            
+            if len(points) > 2:
+                frame.polygon(points, fill=(255, 0, 0, 150))  # Rojo semitransparente
+            
+            return np.array(cropped_img)
+
+        # 5. Crear video
+        video = mp.VideoClip(make_frame, duration=duration)
+        video.fps = 24
+        video = video.set_audio(mp.AudioFileClip(audio_file))
+
+        # 6. Guardar video
+        with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
+            video.write_videofile(
+                tmpfile.name,
+                codec="libx264",
+                audio_codec="aac",
+                fps=24,
+                logger=None
+            )
+            
+            logger.info(f"Video guardado: {tmpfile.name}")
+            return tmpfile.name
+
+    except Exception as e:
+        logger.error(f"Error crítico: {str(e)}")
+        return f"Error: {str(e)}"
+
+# Interfaz Gradio
+iface = gr.Interface(
+    fn=generate_video,
+    inputs=[
+        gr.Audio(type="filepath", label="Audio (WAV/MP3)"),
+        gr.Image(type="filepath", label="Imagen de Fondo")
+    ],
+    outputs=gr.File(label="Descargar Video"),
+    title="Generador de Video Musical",
+    description="Crea videos con zoom automático y efectos de audio sincronizados"
+)
+
+if __name__ == "__main__":
+    iface.queue().launch()