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@@ -1,3 +1,4 @@
+
 # ---------- base image -------------------------------------------------------
 FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
 
@@ -37,9 +38,7 @@ RUN git clone https://github.com/xinntao/Real-ESRGAN.git && \
     cd Real-ESRGAN && \
     pip install basicsr==1.4.2 facexlib==0.2.5 gfpgan==1.3.8 && \
     pip install -r requirements.txt && \
-    python setup.py develop && \
-    mkdir -p weights && \
-    wget -q -O weights/RealESRGAN_x2plus.pth https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.0/RealESRGAN_x2plus.pth
+    python setup.py develop
 
 # ---------- app --------------------------------------------------------------
 COPY app.py .

README.md

@@ -1,3 +1,4 @@
+
 ---
 title: Vertical SadTalker
 emoji: 🎤
@@ -9,14 +10,20 @@ app_file: app.py
 pinned: false
 ---
 
-# Vertical Talking-Head Generator (SadTalker + Real-ESRGAN)
+# Vertical Talking‑Head Generator (SadTalker)
+
+Turns a portrait + audio **or** portrait + text into a 576 × 1024 MP4 ready for TikTok/Shorts.
 
-This Space turns a portrait + audio **or** portrait + text into a 576 × 1024 (9∶16) lip‑synced video, perfect for TikTok/Shorts.
+* XTTS‑v2 TTS when only text is provided  
+* SadTalker for lip‑sync & motion  
+* Optional Real‑ESRGAN upscaling (512 → 1024)  
+* CUDA 12, fp16, xformers; works on one H‑200 or two T4s with `deepspeed --num_gpus 2`
 
-**Pipeline**
-1. XTTS‑v2 (Coqui‑TTS) → WAV (if you supply text)
-2. SadTalker generates 512² talking‑head video
-3. Real‑ESRGAN upscales frames to 1024²
-4. FFmpeg crops/pads to 576 × 1024 and re‑encodes as MP4
+## Simple API
 
-Designed for **ZeroGPU** H‑200 slices; add `deepspeed --num_gpus 2 app.py` if you spin it on a dual‑GPU runtime.
+```python
+from gradio_client import Client
+cli = Client("your‑hf‑org/vertical‑sadtalker")
+vid = cli.predict(image="face.png", text="Breaking news!")
+cli.download(vid, "clip.mp4")
+```

app.py

@@ -1,112 +1,79 @@
-import os, sys, subprocess, tempfile, uuid, torch, gradio as gr, cv2, numpy as np
+
+import sys, os, subprocess, tempfile, uuid, torch, gradio as gr
 from pathlib import Path
 from PIL import Image
-from TTS.api import TTS
-
-# add SadTalker to path if not installed as pkg
-SAD_PATH = '/workspace/SadTalker'
-if SAD_PATH not in sys.path and Path(SAD_PATH).exists():
-    sys.path.append(SAD_PATH)
-from sadtalker.inference import SadTalker
-
-from realesrgan import RealESRGANer
-from basicsr.archs.rrdbnet_arch import RRDBNet
 
-DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
+# ensure SadTalker repo is importable
+sys.path.append('/workspace/SadTalker')
 
-# TTS
-tts = TTS(model_name='tts_models/en/xtts_v2', progress_bar=False).to(DEVICE)
+from TTS.api import TTS
+from sadtalker.inference import SadTalker
 
-# SadTalker
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+tts = TTS(model_name="tts_models/en/xtts_v2", progress_bar=False).to(DEVICE)
 sadtalker = SadTalker(device=DEVICE, half=True)  # fp16
 
-# Real‑ESRGAN upsampler (×2 so 512→1024)
-model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
-upsampler = RealESRGANer(
-    scale=2,
-    model_path='/workspace/Real-ESRGAN/weights/RealESRGAN_x2plus.pth',
-    model=model,
-    tile=0,
-    half=True,
-    gpu_id=0 if DEVICE == 'cuda' else None
-)
-
-def _upscale_video(in_path: Path, out_path: Path):
-    cap = cv2.VideoCapture(str(in_path))
-    fps = cap.get(cv2.CAP_PROP_FPS) or 25
-    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    # first frame upscale to get new dims
-    ret, frame = cap.read()
-    if not ret:
-        cap.release()
-        raise RuntimeError('Empty video input for upscaling.')
-    up_frame, _ = upsampler.enhance(frame, outscale=2)
-    new_h, new_w = up_frame.shape[:2]
-    writer = cv2.VideoWriter(str(out_path), fourcc, fps, (new_w, new_h))
-    writer.write(up_frame)
-    while True:
-        ret, frame = cap.read()
-        if not ret:
-            break
-        up_frame, _ = upsampler.enhance(frame, outscale=2)
-        writer.write(up_frame)
-    writer.release()
-    cap.release()
-
-def generate(image: Image, audio=None, text: str = ''):
+def generate(image: Image, audio=None, text: str = ""):
     tmp = Path(tempfile.mkdtemp())
-    img_path = tmp / 'input.png'
-    image.convert('RGB').save(img_path)
+    img_path = tmp / "input.png"
+    image.convert("RGB").save(img_path)
 
-    # handle audio or text
+    # 1️⃣ handle audio or text -> wav
     if audio is None and text.strip():
-        wav_path = tmp / 'speech.wav'
+        wav_path = tmp / "speech.wav"
         tts.tts_to_file(text=text, file_path=str(wav_path))
     elif audio is not None:
         wav_path = Path(audio)
     else:
-        raise gr.Error('Provide either audio or text!')
+        raise gr.Error("Provide either audio or text!")
 
-    # SadTalker inference
-    vid_path = tmp / f'{uuid.uuid4().hex}_base.mp4'
+    # 2️⃣ run SadTalker
+    vid_path = tmp / f"{uuid.uuid4().hex}.mp4"
     sadtalker.infer(
         source_image=str(img_path),
         driven_audio=str(wav_path),
         result_dir=str(tmp),
         size=512,
-        preprocess='crop',
+        preprocess="crop",
         still=False,
         enhancer=None,
         write_video=True,
         output_path=str(vid_path)
     )
 
-    # Upscale video with Real-ESRGAN (×2 => 1024×1024)
-    upscaled_vid = tmp / f'{uuid.uuid4().hex}_sr.mp4'
-    _upscale_video(vid_path, upscaled_vid)
+    # 3️⃣ (optional) upscale to ~1024 height with Real-ESRGAN
+    upscaled_path = tmp / "up.mp4"
+    try:
+        subprocess.run([
+            "python", "/workspace/Real-ESRGAN/inference_realesrgan_video.py",
+            "-n", "RealESRGAN_x4plus",
+            "-i", str(vid_path),
+            "-o", str(upscaled_path),
+            "--fp32"
+        ], check=True)
+    except Exception:
+        upscaled_path = vid_path  # fallback
+
+    # 4️⃣ pad/crop to 576×1024 vertical
+    out_vid = tmp / "vertical.mp4"
+    subprocess.run([
+        "ffmpeg", "-y", "-i", str(upscaled_path),
+        "-vf", "scale=576:-1,pad=576:1024:0:(1024-ih)/2:black,fps=30",
+        "-c:v", "libx264", "-crf", "18", "-pix_fmt", "yuv420p", str(out_vid)
+    ], check=True)
 
-    # scale & pad to 576×1024 portrait
-    final_vid = tmp / 'vertical.mp4'
-    cmd = [
-        'ffmpeg', '-y', '-i', str(upscaled_vid),
-        '-vf', 'scale=576:-1,pad=576:1024:0:(1024-ih)/2:black,fps=30',
-        '-c:v', 'libx264', '-crf', '18', '-pix_fmt', 'yuv420p', str(final_vid)
-    ]
-    subprocess.run(cmd, check=True)
-    return str(final_vid)
+    return str(out_vid)
 
 demo = gr.Interface(
     fn=generate,
     inputs=[
-        gr.Image(type='pil', label='Portrait 512×512'),
-        gr.Audio(type='filepath', optional=True, label='Voice (wav/mp3)'),
-        gr.Textbox(lines=2, placeholder='…or paste text', label='Text')
+        gr.Image(type="pil", label="Portrait 512×512"),
+        gr.Audio(type="filepath", optional=True, label="Voice (wav/mp3)"),
+        gr.Textbox(lines=2, placeholder="…or paste text", label="Text")
     ],
-    outputs=gr.Video(label='576×1024 MP4'),
-    title='ZeroGPU SadTalker 9:16'
+    outputs=gr.Video(label="576×1024 MP4"),
+    title="ZeroGPU SadTalker 9:16"
 )
 
-if __name__ == '__main__':
-    demo.queue(concurrency_count=1, max_size=4).launch()
+if __name__ == "__main__":
+    demo.queue(concurrency_count=2, max_size=8).launch()

requirements.txt

@@ -1,3 +1,4 @@
+
 gradio==4.26.0
 huggingface_hub>=0.23.1
 transformers>=4.43.0
@@ -9,4 +10,3 @@ facenet-pytorch
 scipy
 pydub
 ninja
-numpy