Upload 6 files

app.py

@@ -373,11 +373,11 @@ def main():
                     gc.collect()
                     torch.cuda.empty_cache() if torch.cuda.is_available() else None
                 
-                # Apply VRAM optimization settings
+                # Store VRAM optimization settings to apply after initialization
+                apply_vram_optimization = vram_optimization
+                
+                # Adjust parameters for VRAM optimization if enabled
                 if vram_optimization:
-                    # Set image generator to use VRAM optimization
-                    image_generator.set_vram_optimization(True)
-                    
                     # Set lower inference steps when VRAM optimization is enabled
                     if inference_steps > 25:
                         inference_steps = 25
@@ -400,6 +400,10 @@ def main():
                 animator.set_aspect_ratio(selected_aspect_ratio)
                 video_creator.set_aspect_ratio(selected_aspect_ratio)
                 
+                # Apply VRAM optimization if enabled
+                if apply_vram_optimization:
+                    image_generator.set_vram_optimization(True)
+                
                 # Set maximum segment duration
                 transcriber.set_max_segment_duration(max_segment_duration)
                 video_creator.set_max_segment_duration(max_segment_duration)
@@ -452,7 +456,7 @@ def main():
                             transcriptions.append("")
                 
                 # Force garbage collection after transcription
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     gc.collect()
                     torch.cuda.empty_cache() if torch.cuda.is_available() else None
                 
@@ -502,7 +506,7 @@ def main():
                 status_message.markdown("🎨 **Creating images...**")
                 
                 # For memory optimization, process in smaller batches even with parallel processing
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     batch_size = 2  # Process only 2 images at a time to conserve memory
                     images = []
                     
@@ -551,7 +555,7 @@ def main():
                         st.image(img_path, caption=f"Image {i+1}", use_column_width=True)
                 
                 # Force garbage collection after image generation
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     gc.collect()
                     torch.cuda.empty_cache() if torch.cuda.is_available() else None
                 
@@ -560,7 +564,7 @@ def main():
                 status_message.markdown("✨ **Adding animations...**")
                 
                 # For memory optimization, process in smaller batches
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     batch_size = 3  # Process only 3 animations at a time
                     animated_frames = []
                     
@@ -613,7 +617,7 @@ def main():
                 progress_bar.progress(80)
                 
                 # Force garbage collection before video creation
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     gc.collect()
                     torch.cuda.empty_cache() if torch.cuda.is_available() else None
                 
@@ -643,7 +647,7 @@ def main():
                     output_video = video_creator.optimize_video(
                         output_video, 
                         bitrate=bitrate,
-                        threads=2 if memory_optimization else max_workers  # Use fewer threads for memory optimization
+                        threads=2 if memory_optimization or apply_vram_optimization else max_workers  # Use fewer threads for optimization
                     )
                 
                 # Cache the result if caching is enabled
@@ -678,6 +682,7 @@ def main():
                 - Number of Segments: {len(audio_segments)}
                 - Parallel Processing: {'Enabled' if parallel_processing else 'Disabled'}
                 - Memory Optimization: {'Enabled' if memory_optimization else 'Disabled'}
+                - VRAM Optimization: {'Enabled' if apply_vram_optimization else 'Disabled'}
                 - Workers: {max_workers}
                 - Image Size: {actual_image_size[0]}x{actual_image_size[1]}
                 - Inference Steps: {inference_steps}
@@ -694,7 +699,7 @@ def main():
                             pass
                 
                 # Final garbage collection
-                if memory_optimization:
+                if memory_optimization or apply_vram_optimization:
                     gc.collect()
                     torch.cuda.empty_cache() if torch.cuda.is_available() else None