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README.md

@@ -9,15 +9,14 @@ app_file: app.py
 pinned: false
 ---
 
-# SadTalker API 🎭
+# SadTalker API (CPU) 🎭
 
-Talking head generation using SadTalker with **ZeroGPU**.
+Talking head generation using SadTalker in **CPU mode**.
 
 ## Features
-- ⚡ GPU-accelerated (~20-40 seconds)
-- 🎨 Face enhancement with GFPGAN
+- 🐢 Runs on CPU (2-5 min per video)
+- ♾️ No quota limits
 - 📹 Returns MP4 video
 
 ## Usage
-
 Upload a face image and audio file, click Generate.

app.py

@@ -82,46 +82,64 @@ def generate_video_gpu(image_path: str, audio_path: str, output_dir: str) -> str
 
 def gradio_generate(image, audio):
     """Gradio interface wrapper"""
-    if image is None or audio is None:
-        raise gr.Error("Por favor, envie uma imagem e um áudio")
+    # Debug logging
+    print(f"=== RECEIVED ===")
+    print(f"Image type: {type(image)}, value: {image}")
+    print(f"Audio type: {type(audio)}, value: {audio}")
+    
+    # Better validation
+    if not image:
+        raise gr.Error("Envie uma imagem primeiro!")
+    if not audio:
+        raise gr.Error("Envie um áudio primeiro!")
     
     with tempfile.TemporaryDirectory() as tmpdir:
-        # Save uploaded files
         image_path = os.path.join(tmpdir, "input.png")
         audio_path = os.path.join(tmpdir, "input.wav")
         output_dir = os.path.join(tmpdir, "output")
         os.makedirs(output_dir, exist_ok=True)
         
-        # Handle image - Gradio gives filepath
-        if isinstance(image, str):
-            shutil.copy(image, image_path)
-        else:
-            from PIL import Image
-            if hasattr(image, 'save'):
-                image.save(image_path)
+        # Handle image
+        try:
+            if isinstance(image, str) and os.path.exists(image):
+                shutil.copy(image, image_path)
+            elif hasattr(image, 'name'):  # File object
+                shutil.copy(image.name, image_path)
             else:
-                Image.fromarray(image).save(image_path)
-        
-        # Handle audio - Gradio gives filepath
-        if isinstance(audio, str):
-            shutil.copy(audio, audio_path)
-        elif isinstance(audio, tuple):
-            # (sample_rate, audio_data) format
-            import scipy.io.wavfile as wav
-            sr, data = audio
-            wav.write(audio_path, sr, data)
+                from PIL import Image as PILImage
+                PILImage.fromarray(image).save(image_path)
+        except Exception as e:
+            raise gr.Error(f"Erro ao processar imagem: {e}")
         
-        print(f"Image: {image_path}, exists: {os.path.exists(image_path)}")
-        print(f"Audio: {audio_path}, exists: {os.path.exists(audio_path)}")
-        
-        # Generate video with GPU
-        video_path = generate_video_gpu(image_path, audio_path, output_dir)
+        # Handle audio
+        try:
+            if isinstance(audio, str) and os.path.exists(audio):
+                shutil.copy(audio, audio_path)
+            elif hasattr(audio, 'name'):  # File object
+                shutil.copy(audio.name, audio_path)
+            elif isinstance(audio, tuple):
+                import scipy.io.wavfile as wav
+                sr, data = audio
+                wav.write(audio_path, sr, data)
+            else:
+                raise gr.Error(f"Formato de áudio não reconhecido: {type(audio)}")
+        except Exception as e:
+            raise gr.Error(f"Erro ao processar áudio: {e}")
         
-        # Copy to persistent location for Gradio
-        final_path = "/tmp/sadtalker_output.mp4"
-        shutil.copy(video_path, final_path)
+        print(f"Image saved: {image_path}, exists: {os.path.exists(image_path)}")
+        print(f"Audio saved: {audio_path}, exists: {os.path.exists(audio_path)}")
         
-        return final_path
+        # Generate video
+        try:
+            video_path = generate_video_gpu(image_path, audio_path, output_dir)
+            
+            # Copy to persistent location
+            final_path = "/tmp/sadtalker_output.mp4"
+            shutil.copy(video_path, final_path)
+            
+            return final_path
+        except Exception as e:
+            raise gr.Error(f"Erro na geração: {e}")
 
 # Create Gradio app
 with gr.Blocks(title="SadTalker API") as demo: