Delete FantasyTalking/inference.py

FantasyTalking/inference.py

@@ -1,50 +0,0 @@
-import os
-import torch
-from PIL import Image
-import torchvision.transforms as transforms
-from fantasy_talking.model import FantasyTalkingModel
-from moviepy.editor import ImageSequenceClip
-import torchaudio
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-# تحميل الموديل
-model_ckpt = "./models/fantasytalking_model.ckpt"
-model = FantasyTalkingModel()
-model.load_state_dict(torch.load(model_ckpt, map_location=device))
-model = model.to(device)
-model.eval()
-
-# تحويل الصورة إلى Tensor
-def load_image(image_path):
-    image = Image.open(image_path).convert("RGB")
-    transform = transforms.Compose([
-        transforms.Resize((512, 512)),
-        transforms.ToTensor()
-    ])
-    return transform(image).unsqueeze(0).to(device)
-
-# تحويل الصوت إلى Tensor
-def load_audio(audio_path):
-    waveform, sample_rate = torchaudio.load(audio_path)
-    if waveform.shape[0] > 1:
-        waveform = waveform.mean(dim=0, keepdim=True)
-    if sample_rate != 16000:
-        resampler = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)
-        waveform = resampler(waveform)
-    return waveform.to(device), 16000
-
-# توليد الفيديو
-def generate_video(image_path, audio_path, output_path="output.mp4"):
-    image_tensor = load_image(image_path)
-    audio_tensor, _ = load_audio(audio_path)
-
-    with torch.no_grad():
-        frames = model.generate(image_tensor, audio_tensor)
-
-    # حفظ الفيديو من الفريمات
-    frames = [transforms.ToPILImage()(frame.squeeze(0).cpu()) for frame in frames]
-    video_clip = ImageSequenceClip([frame for frame in frames], fps=25)
-    video_clip.write_videofile(output_path, codec="libx264")
-
-    return output_path