diff --git a/requirements.txt b/requirements.txt index ced4da7..b4868d1 100644 --- a/requirements.txt +++ b/requirements.txt @@ -34,4 +34,6 @@ loguru sentencepiece av opencv-python +pygame>=2.1.0 +sounddevice>=0.4.0 # rembg==2.0.65 diff --git a/wan/utils/notification_sound.py b/wan/utils/notification_sound.py new file mode 100644 index 0000000..47d2e3d --- /dev/null +++ b/wan/utils/notification_sound.py @@ -0,0 +1,261 @@ +"""Add commentMore actions +Notification sounds for Wan2GP video generation application +Pure Python audio notification system with multiple backend support +""" + +import os +import sys +import threading +import time +import numpy as np + + +def generate_notification_beep(volume=50, sample_rate=44100): + """Generate pleasant C major chord notification sound""" + if volume == 0: + return np.array([]) + + volume = max(0, min(100, volume)) + + # Volume curve mapping: 25%->50%, 50%->75%, 75%->100%, 100%->105% + if volume <= 25: + volume_mapped = (volume / 25.0) * 0.5 + elif volume <= 50: + volume_mapped = 0.5 + ((volume - 25) / 25.0) * 0.25 + elif volume <= 75: + volume_mapped = 0.75 + ((volume - 50) / 25.0) * 0.25 + else: + volume_mapped = 1.0 + ((volume - 75) / 25.0) * 0.05 # Only 5% boost instead of 15% + + volume = volume_mapped + + # C major chord frequencies + freq_c = 261.63 # C4 + freq_e = 329.63 # E4 + freq_g = 392.00 # G4 + + duration = 0.8 + t = np.linspace(0, duration, int(sample_rate * duration), False) + + # Generate chord components + wave_c = np.sin(freq_c * 2 * np.pi * t) * 0.4 + wave_e = np.sin(freq_e * 2 * np.pi * t) * 0.3 + wave_g = np.sin(freq_g * 2 * np.pi * t) * 0.2 + + wave = wave_c + wave_e + wave_g + + # Prevent clipping + max_amplitude = np.max(np.abs(wave)) + if max_amplitude > 0: + wave = wave / max_amplitude * 0.8 + + # ADSR envelope + def apply_adsr_envelope(wave_data): + length = len(wave_data) + attack_time = int(0.2 * length) + decay_time = int(0.1 * length) + release_time = int(0.5 * length) + + envelope = np.ones(length) + + if attack_time > 0: + envelope[:attack_time] = np.power(np.linspace(0, 1, attack_time), 3) + + if decay_time > 0: + start_idx = attack_time + end_idx = attack_time + decay_time + envelope[start_idx:end_idx] = np.linspace(1, 0.85, decay_time) + + if release_time > 0: + start_idx = length - release_time + envelope[start_idx:] = 0.85 * np.exp(-4 * np.linspace(0, 1, release_time)) + + return wave_data * envelope + + wave = apply_adsr_envelope(wave) + + # Simple low-pass filter + def simple_lowpass_filter(signal, cutoff_ratio=0.8): + window_size = max(3, int(len(signal) * 0.001)) + if window_size % 2 == 0: + window_size += 1 + + kernel = np.ones(window_size) / window_size + padded = np.pad(signal, window_size//2, mode='edge') + filtered = np.convolve(padded, kernel, mode='same') + return filtered[window_size//2:-window_size//2] + + wave = simple_lowpass_filter(wave) + + # Add reverb effect + if len(wave) > sample_rate // 4: + delay_samples = int(0.12 * sample_rate) + reverb = np.zeros_like(wave) + reverb[delay_samples:] = wave[:-delay_samples] * 0.08 + wave = wave + reverb + + # Apply volume first, then normalize to prevent clipping + wave = wave * volume * 0.5 + + # Final normalization with safety margin + max_amplitude = np.max(np.abs(wave)) + if max_amplitude > 0.85: # If approaching clipping threshold + wave = wave / max_amplitude * 0.85 # More conservative normalization + + return wave + + +def play_audio_with_pygame(audio_data, sample_rate=44100): + """Play audio using pygame backend""" + try: + import pygame + # Initialize pygame mixer only if not already initialized + if not pygame.mixer.get_init(): + pygame.mixer.pre_init(frequency=sample_rate, size=-16, channels=2, buffer=1024) + pygame.mixer.init() + else: + # Reinitialize with new settings if needed + current_freq, current_size, current_channels = pygame.mixer.get_init() + if current_freq != sample_rate or current_channels != 2: + pygame.mixer.quit() + pygame.mixer.pre_init(frequency=sample_rate, size=-16, channels=2, buffer=1024) + pygame.mixer.init() + + audio_int16 = (audio_data * 32767).astype(np.int16) + + # Convert mono to stereo + if len(audio_int16.shape) == 1: + stereo_data = np.column_stack((audio_int16, audio_int16)) + else: + stereo_data = audio_int16 + + sound = pygame.sndarray.make_sound(stereo_data) + sound.play() + pygame.time.wait(int(len(audio_data) / sample_rate * 1000) + 100) + # Don't quit mixer - this can interfere with Gradio server + # pygame.mixer.quit() + return True + + except ImportError: + return False + except Exception as e: + print(f"Pygame error: {e}") + return False + + +def play_audio_with_sounddevice(audio_data, sample_rate=44100): + """Play audio using sounddevice backend""" + try: + import sounddevice as sd + sd.play(audio_data, sample_rate) + sd.wait() + return True + + except ImportError: + return False + except Exception as e: + print(f"Sounddevice error: {e}") + return False + + +def play_audio_with_winsound(audio_data, sample_rate=44100): + """Play audio using winsound backend (Windows only)""" + if sys.platform != "win32": + return False + + try: + import winsound + import wave + import tempfile + import uuid + + temp_dir = tempfile.gettempdir() + temp_filename = os.path.join(temp_dir, f"notification_{uuid.uuid4().hex}.wav") + + try: + with wave.open(temp_filename, 'w') as wav_file: + wav_file.setnchannels(1) + wav_file.setsampwidth(2) + wav_file.setframerate(sample_rate) + + audio_int16 = (audio_data * 32767).astype(np.int16) + wav_file.writeframes(audio_int16.tobytes()) + + winsound.PlaySound(temp_filename, winsound.SND_FILENAME) + + finally: + # Clean up temp file + for _ in range(3): + try: + if os.path.exists(temp_filename): + os.unlink(temp_filename) + break + except: + time.sleep(0.1) + + return True + + except ImportError: + return False + except Exception as e: + print(f"Winsound error: {e}") + return False + + +def play_notification_sound(volume=50): + """Play notification sound with specified volume""" + if volume == 0: + return + + audio_data = generate_notification_beep(volume=volume) + + if len(audio_data) == 0: + return + + # Try audio backends in order + audio_backends = [ + play_audio_with_pygame, + play_audio_with_sounddevice, + play_audio_with_winsound, + ] + + for backend in audio_backends: + try: + if backend(audio_data): + return + except Exception as e: + continue + + # Fallback: terminal beep + print(f"All audio backends failed, using terminal beep") + print('\a') + + +def play_notification_async(volume=50): + """Play notification sound asynchronously (non-blocking)""" + def play_sound(): + try: + play_notification_sound(volume) + except Exception as e: + print(f"Error playing notification sound: {e}") + + sound_thread = threading.Thread(target=play_sound, daemon=True) + sound_thread.start() + + +def notify_video_completion(video_path=None, volume=50): + """Notify about completed video generation""" + play_notification_async(volume) + + +if __name__ == "__main__": + print("Testing notification sounds with different volumes...") + print("Auto-detecting available audio backends...") + + volumes = [25, 50, 75, 100] + for vol in volumes: + print(f"Testing volume {vol}%:") + play_notification_sound(vol) + time.sleep(2) + + print("Test completed!") \ No newline at end of file diff --git a/wgp.py b/wgp.py index 15d35dc..73dc710 100644 --- a/wgp.py +++ b/wgp.py @@ -14,6 +14,7 @@ import gradio as gr import random import json import wan +from wan.utils import notification_sound from wan.configs import MAX_AREA_CONFIGS, WAN_CONFIGS, SUPPORTED_SIZES, VACE_SIZE_CONFIGS from wan.utils.utils import cache_video from wan.modules.attention import get_attention_modes, get_supported_attention_modes @@ -1518,20 +1519,22 @@ for src,tgt in zip(src_move,tgt_move): if not Path(server_config_filename).is_file(): - server_config = {"attention_mode" : "auto", - "transformer_types": [], - "transformer_quantization": "int8", - "text_encoder_quantization" : "int8", - "save_path": "outputs", #os.path.join(os.getcwd(), - "compile" : "", - "metadata_type": "metadata", - "default_ui": "t2v", - "boost" : 1, - "clear_file_list" : 5, - "vae_config": 0, - "profile" : profile_type.LowRAM_LowVRAM, - "preload_model_policy": [], - "UI_theme": "default" } + server_config = { + "attention_mode" : "auto", + "transformer_types": [], + "transformer_quantization": "int8", + "text_encoder_quantization" : "int8", + "save_path": "outputs", #os.path.join(os.getcwd(), + "compile" : "", + "metadata_type": "metadata", + "default_ui": "t2v", + "boost" : 1, + "clear_file_list" : 5, + "vae_config": 0, + "profile" : profile_type.LowRAM_LowVRAM, + "preload_model_policy": [], + "UI_theme": "default" + } with open(server_config_filename, "w", encoding="utf-8") as writer: writer.write(json.dumps(server_config)) @@ -2436,33 +2439,38 @@ def apply_changes( state, UI_theme_choice = "default", enhancer_enabled_choice = 0, fit_canvas_choice = 0, - preload_in_VRAM_choice = 0 + preload_in_VRAM_choice = 0, + notification_sound_enabled_choice = 1, + notification_sound_volume_choice = 50 ): if args.lock_config: return if gen_in_progress: return "
Unable to change config when a generation is in progress
", gr.update(), gr.update() global offloadobj, wan_model, server_config, loras, loras_names, default_loras_choices, default_loras_multis_str, default_lora_preset_prompt, default_lora_preset, loras_presets - server_config = {"attention_mode" : attention_choice, - "transformer_types": transformer_types_choices, - "text_encoder_quantization" : text_encoder_quantization_choice, - "save_path" : save_path_choice, - "compile" : compile_choice, - "profile" : profile_choice, - "vae_config" : vae_config_choice, - "vae_precision" : VAE_precision_choice, - "mixed_precision" : mixed_precision_choice, - "metadata_type": metadata_choice, - "transformer_quantization" : quantization_choice, - "transformer_dtype_policy" : transformer_dtype_policy_choice, - "boost" : boost_choice, - "clear_file_list" : clear_file_list, - "preload_model_policy" : preload_model_policy_choice, - "UI_theme" : UI_theme_choice, - "fit_canvas": fit_canvas_choice, - "enhancer_enabled" : enhancer_enabled_choice, - "preload_in_VRAM" : preload_in_VRAM_choice - } + server_config = { + "attention_mode" : attention_choice, + "transformer_types": transformer_types_choices, + "text_encoder_quantization" : text_encoder_quantization_choice, + "save_path" : save_path_choice, + "compile" : compile_choice, + "profile" : profile_choice, + "vae_config" : vae_config_choice, + "vae_precision" : VAE_precision_choice, + "mixed_precision" : mixed_precision_choice, + "metadata_type": metadata_choice, + "transformer_quantization" : quantization_choice, + "transformer_dtype_policy" : transformer_dtype_policy_choice, + "boost" : boost_choice, + "clear_file_list" : clear_file_list, + "preload_model_policy" : preload_model_policy_choice, + "UI_theme" : UI_theme_choice, + "fit_canvas": fit_canvas_choice, + "enhancer_enabled" : enhancer_enabled_choice, + "preload_in_VRAM" : preload_in_VRAM_choice, + "notification_sound_enabled" : notification_sound_enabled_choice, + "notification_sound_volume" : notification_sound_volume_choice + } if Path(server_config_filename).is_file(): with open(server_config_filename, "r", encoding="utf-8") as reader: @@ -2496,7 +2504,7 @@ def apply_changes( state, transformer_types = server_config["transformer_types"] model_filename = get_model_filename(transformer_type, transformer_quantization, transformer_dtype_policy) state["model_filename"] = model_filename - if all(change in ["attention_mode", "vae_config", "boost", "save_path", "metadata_type", "clear_file_list", "fit_canvas"] for change in changes ): + if all(change in ["attention_mode", "vae_config", "boost", "save_path", "metadata_type", "clear_file_list", "fit_canvas", "notification_sound_enabled", "notification_sound_volume"] for change in changes ): model_choice = gr.Dropdown() else: reload_needed = True @@ -2647,7 +2655,21 @@ def refresh_gallery(state): #, msg for img_uri in list_uri: thumbnails += f'Start' - html = "" + thumbnails + "
" + prompt + "
" + # Get current theme from server config + current_theme = server_config.get("UI_theme", "default") + + # Use minimal, adaptive styling that blends with any background + # This creates a subtle container that doesn't interfere with the page's theme + table_style = """ + border: 1px solid rgba(128, 128, 128, 0.3); + background-color: transparent; + color: inherit; + padding: 8px; + border-radius: 6px; + box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); + """ + + html = f"" + thumbnails + "
" + prompt + "
" html_output = gr.HTML(html, visible= True) return gr.Gallery(selected_index=choice, value = file_list), html_output, gr.Button(visible=False), gr.Button(visible=True), gr.Row(visible=True), update_queue_data(queue), gr.Button(interactive= abort_interactive), gr.Button(visible= onemorewindow_visible) @@ -3562,6 +3584,17 @@ def generate_video( print(f"New video saved to Path: "+video_path) file_list.append(video_path) file_settings_list.append(configs) + + # Play notification sound for single video + try: + if server_config.get("notification_sound_enabled", 1): + volume = server_config.get("notification_sound_volume", 50) + notification_sound.notify_video_completion( + video_path=video_path, + volume=volume + ) + except Exception as e: + print(f"Error playing notification sound for individual video: {e}") send_cmd("output") @@ -3905,6 +3938,13 @@ def process_tasks(state): status = f"Video generation was aborted. Total Generation Time: {end_time-start_time:.1f}s" else: status = f"Total Generation Time: {end_time-start_time:.1f}s" + # Play notification sound when video generation completed successfully + try: + if server_config.get("notification_sound_enabled", 1): + volume = server_config.get("notification_sound_volume", 50) + notification_sound.notify_video_completion(volume=volume) + except Exception as e: + print(f"Error playing notification sound: {e}") gen["status"] = status gen["status_display"] = False @@ -5738,6 +5778,24 @@ def generate_configuration_tab(state, blocks, header, model_choice, prompt_enhan ) preload_in_VRAM_choice = gr.Slider(0, 40000, value=server_config.get("preload_in_VRAM", 0), step=100, label="Number of MB of Models that are Preloaded in VRAM (0 will use Profile default)") + with gr.Tab("Notifications"): + gr.Markdown("### Notification Settings") + notification_sound_enabled_choice = gr.Dropdown( + choices=[ + ("On", 1), + ("Off", 0), + ], + value=server_config.get("notification_sound_enabled", 1), + label="Notification Sound Enabled" + ) + + notification_sound_volume_choice = gr.Slider( + minimum=0, + maximum=100, + value=server_config.get("notification_sound_volume", 50), + step=5, + label="Notification Sound Volume (0 = silent, 100 = very loud)" + ) @@ -5765,7 +5823,9 @@ def generate_configuration_tab(state, blocks, header, model_choice, prompt_enhan UI_theme_choice, enhancer_enabled_choice, fit_canvas_choice, - preload_in_VRAM_choice + preload_in_VRAM_choice, + notification_sound_enabled_choice, + notification_sound_volume_choice ], outputs= [msg , header, model_choice, prompt_enhancer_row] )