Delete app-old-backup.py

app-old-backup.py

@@ -1,355 +0,0 @@
-import spaces
-import logging
-from datetime import datetime
-from pathlib import Path
-import gradio as gr
-import torch
-import torchaudio
-import os
-import requests
-from transformers import pipeline
-import tempfile
-import numpy as np
-from einops import rearrange
-import cv2
-from scipy.io import wavfile
-import librosa
-import json
-from typing import Optional, Tuple, List
-import atexit
-
-try:
-    import mmaudio
-except ImportError:
-    os.system("pip install -e .")
-    import mmaudio
-
-from mmaudio.eval_utils import (ModelConfig, all_model_cfg, generate, load_video, make_video,
-                                setup_eval_logging)
-from mmaudio.model.flow_matching import FlowMatching
-from mmaudio.model.networks import MMAudio, get_my_mmaudio
-from mmaudio.model.sequence_config import SequenceConfig
-from mmaudio.model.utils.features_utils import FeaturesUtils
-
-# 로깅 설정
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-)
-log = logging.getLogger()
-
-# CUDA 설정
-if torch.cuda.is_available():
-    device = torch.device("cuda")
-    torch.backends.cuda.matmul.allow_tf32 = True
-    torch.backends.cudnn.allow_tf32 = True
-    torch.backends.cudnn.benchmark = True
-else:
-    device = torch.device("cpu")
-
-dtype = torch.bfloat16
-
-# 모델 설정
-model: ModelConfig = all_model_cfg['large_44k_v2']
-model.download_if_needed()
-output_dir = Path('./output/gradio')
-
-setup_eval_logging()
-
-# 번역기 및 Pixabay API 설정
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", device="cpu")
-PIXABAY_API_KEY = "33492762-a28a596ec4f286f84cd328b17"
-
-
-
-def cleanup_temp_files():
-    temp_dir = tempfile.gettempdir()
-    for file in os.listdir(temp_dir):
-        if file.endswith(('.mp4', '.flac')):
-            try:
-                os.remove(os.path.join(temp_dir, file))
-            except:
-                pass
-
-atexit.register(cleanup_temp_files)
-
-def get_model() -> tuple[MMAudio, FeaturesUtils, SequenceConfig]:
-    with torch.cuda.device(device):
-        seq_cfg = model.seq_cfg
-        net: MMAudio = get_my_mmaudio(model.model_name).to(device, dtype).eval()
-        net.load_weights(torch.load(model.model_path, map_location=device, weights_only=True))
-        log.info(f'Loaded weights from {model.model_path}')
-
-        feature_utils = FeaturesUtils(
-            tod_vae_ckpt=model.vae_path,
-            synchformer_ckpt=model.synchformer_ckpt,
-            enable_conditions=True,
-            mode=model.mode,
-            bigvgan_vocoder_ckpt=model.bigvgan_16k_path,
-            need_vae_encoder=False
-        ).to(device, dtype).eval()
-
-        return net, feature_utils, seq_cfg
-
-net, feature_utils, seq_cfg = get_model()
-
-
-# search_videos 함수 수정
-@torch.no_grad()
-def search_videos(query):
-    try:
-        # CPU에서 번역 실행
-        query = translate_prompt(query)
-        return search_pixabay_videos(query, PIXABAY_API_KEY)
-    except Exception as e:
-        logging.error(f"Video search error: {e}")
-        return []
-
-# translate_prompt 함수도 수정
-def translate_prompt(text):
-    try:
-        if text and any(ord(char) >= 0x3131 and ord(char) <= 0xD7A3 for char in text):
-            # CPU에서 번역 실행
-            with torch.no_grad():
-                translation = translator(text)[0]['translation_text']
-            return translation
-        return text
-    except Exception as e:
-        logging.error(f"Translation error: {e}")
-        return text
-
-# 디바이스 설정 부분 수정
-if torch.cuda.is_available():
-    device = torch.device("cuda")
-    torch.backends.cuda.matmul.allow_tf32 = True
-    torch.backends.cudnn.allow_tf32 = True
-    torch.backends.cudnn.benchmark = True
-else:
-    device = torch.device("cpu")
-
-# 번역기 설정 수정
-translator = pipeline("translation", 
-                     model="Helsinki-NLP/opus-mt-ko-en", 
-                     device="cpu")  # 명시적으로 CPU 지정
-
-
-
-def search_pixabay_videos(query, api_key):
-    try:
-        base_url = "https://pixabay.com/api/videos/"
-        params = {
-            "key": api_key,
-            "q": query,
-            "per_page": 40
-        }
-        
-        response = requests.get(base_url, params=params)
-        if response.status_code == 200:
-            data = response.json()
-            return [video['videos']['large']['url'] for video in data.get('hits', [])]
-        return []
-    except Exception as e:
-        logging.error(f"Pixabay API error: {e}")
-        return []
-
-
-@spaces.GPU
-@torch.inference_mode()
-def video_to_audio(video: gr.Video, prompt: str, negative_prompt: str, seed: int, num_steps: int,
-                   cfg_strength: float, duration: float):
-    prompt = translate_prompt(prompt)
-    negative_prompt = translate_prompt(negative_prompt)
-
-    rng = torch.Generator(device=device)
-    rng.manual_seed(seed)
-    fm = FlowMatching(min_sigma=0, inference_mode='euler', num_steps=num_steps)
-
-    clip_frames, sync_frames, duration = load_video(video, duration)
-    clip_frames = clip_frames.unsqueeze(0)
-    sync_frames = sync_frames.unsqueeze(0)
-    seq_cfg.duration = duration
-    net.update_seq_lengths(seq_cfg.latent_seq_len, seq_cfg.clip_seq_len, seq_cfg.sync_seq_len)
-
-    audios = generate(clip_frames,
-                      sync_frames, [prompt],
-                      negative_text=[negative_prompt],
-                      feature_utils=feature_utils,
-                      net=net,
-                      fm=fm,
-                      rng=rng,
-                      cfg_strength=cfg_strength)
-    audio = audios.float().cpu()[0]
-
-    video_save_path = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4').name
-    make_video(video,
-               video_save_path,
-               audio,
-               sampling_rate=seq_cfg.sampling_rate,
-               duration_sec=seq_cfg.duration)
-    return video_save_path
-
-@spaces.GPU
-@torch.inference_mode()
-def text_to_audio(prompt: str, negative_prompt: str, seed: int, num_steps: int, cfg_strength: float,
-                  duration: float):
-    prompt = translate_prompt(prompt)
-    negative_prompt = translate_prompt(negative_prompt)
-
-    rng = torch.Generator(device=device)
-    rng.manual_seed(seed)
-    fm = FlowMatching(min_sigma=0, inference_mode='euler', num_steps=num_steps)
-
-    clip_frames = sync_frames = None
-    seq_cfg.duration = duration
-    net.update_seq_lengths(seq_cfg.latent_seq_len, seq_cfg.clip_seq_len, seq_cfg.sync_seq_len)
-
-    audios = generate(clip_frames,
-                      sync_frames, [prompt],
-                      negative_text=[negative_prompt],
-                      feature_utils=feature_utils,
-                      net=net,
-                      fm=fm,
-                      rng=rng,
-                      cfg_strength=cfg_strength)
-    audio = audios.float().cpu()[0]
-
-    audio_save_path = tempfile.NamedTemporaryFile(delete=False, suffix='.flac').name
-    torchaudio.save(audio_save_path, audio, seq_cfg.sampling_rate)
-    return audio_save_path
-
-
-
-# CSS 스타일 수정
-custom_css = """
-.gradio-container {
-    background: linear-gradient(45deg, #1a1a1a, #2a2a2a);
-    border-radius: 15px;
-    box-shadow: 0 8px 32px rgba(0,0,0,0.3);
-    color: #e0e0e0;
-}
-
-.input-container, .output-container {
-    background: rgba(40, 40, 40, 0.95);
-    backdrop-filter: blur(10px);
-    border-radius: 10px;
-    padding: 20px;
-    transform-style: preserve-3d;
-    transition: transform 0.3s ease;
-    border: 1px solid rgba(255, 255, 255, 0.1);
-}
-
-.input-container:hover {
-    transform: translateZ(20px);
-    box-shadow: 0 8px 32px rgba(0,0,0,0.5);
-}
-
-.gallery-item {
-    transition: transform 0.3s ease;
-    border-radius: 8px;
-    overflow: hidden;
-    background: #2a2a2a;
-}
-
-.gallery-item:hover {
-    transform: scale(1.05);
-    box-shadow: 0 4px 15px rgba(0,0,0,0.4);
-}
-
-.tabs {
-    background: rgba(30, 30, 30, 0.95);
-    border-radius: 10px;
-    padding: 10px;
-    border: 1px solid rgba(255, 255, 255, 0.05);
-}
-
-button {
-    background: linear-gradient(45deg, #2196F3, #1976D2);
-    border: none;
-    border-radius: 5px;
-    transition: all 0.3s ease;
-    color: white;
-}
-
-button:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 4px 15px rgba(33,150,243,0.3);
-}
-
-/* 텍스트 입력 필드 스타일 */
-textarea, input[type="text"], input[type="number"] {
-    background: rgba(30, 30, 30, 0.95) !important;
-    border: 1px solid rgba(255, 255, 255, 0.1) !important;
-    color: #e0e0e0 !important;
-    border-radius: 5px !important;
-}
-
-/* 레이블 스타일 */
-label {
-    color: #e0e0e0 !important;
-}
-
-/* 갤러리 그리드 스타일 */
-.gallery {
-    background: rgba(30, 30, 30, 0.95);
-    padding: 15px;
-    border-radius: 10px;
-    border: 1px solid rgba(255, 255, 255, 0.05);
-}
-"""
-
-text_to_audio_tab = gr.Interface(
-    fn=text_to_audio,
-    inputs=[
-        gr.Textbox(label="Prompt(한글지원)"),
-        gr.Textbox(label="Negative Prompt"),
-        gr.Number(label="Seed", value=0),
-        gr.Number(label="Steps", value=25),
-        gr.Number(label="Guidance Scale", value=4.5),
-        gr.Number(label="Duration (sec)", value=8),
-    ],
-    outputs=gr.Audio(label="Generated Audio"),
-    css=custom_css
-)
-
-
-video_to_audio_tab = gr.Interface(
-    fn=video_to_audio,
-    inputs=[
-        gr.Video(label="Input Video"),
-        gr.Textbox(label="Prompt(한글지원)"),
-        gr.Textbox(label="Negative Prompt", value="music"),
-        gr.Number(label="Seed", value=0),
-        gr.Number(label="Steps", value=25),
-        gr.Number(label="Guidance Scale", value=4.5),
-        gr.Number(label="Duration (sec)", value=8),
-    ],
-    outputs=gr.Video(label="Generated Result"),
-    css=custom_css
-)
-
-# 인터페이스 정의 수정 (영문으로 변경)
-video_search_tab = gr.Interface(
-    fn=search_videos,
-    inputs=gr.Textbox(label="Search Query(한글지원)"),
-    outputs=gr.Gallery(label="Search Results", columns=4, rows=20),
-    css=custom_css,
-    api_name=False
-)
-
-
-
-# CSS 스타일 수정
-css = """
-footer {
-    visibility: hidden;
-}
-""" + custom_css  # 기존 custom_css와 새로운 css를 결합
-
-# 메인 실행 부분 수정
-if __name__ == "__main__":
-    gr.TabbedInterface(
-        [video_search_tab, video_to_audio_tab, text_to_audio_tab],
-        ["Video Search", "Video-to-Audio", "Text-to-Audio"],
-        theme="Yntec/HaleyCH_Theme_Orange",
-        css=css
-    ).launch(allowed_paths=[output_dir])