agent 1.9

models/matanyone_loader.py

@@ -872,26 +872,3 @@ def _flush_chunk(self, frames_bgr, seed_1hw, alpha_writer, fg_writer):
             log.error(error_msg, exc_info=True)
             raise MatAnyError(error_msg) from e
 
-        # Normalize to numpy list of HW float32 [0,1]
-        if isinstance(alphas, torch.Tensor):
-            alphas_np = alphas.detach().float().clamp(0, 1).cpu().numpy()
-        else:
-            alphas_np = np.asarray(alphas)
-            if alphas_np.max() > 1.0:
-                alphas_np = (alphas_np / 255.0).clip(0, 1)
-
-        if alphas_np.ndim == 3:
-            T, H, W = alphas_np.shape
-            pass
-        elif alphas_np.ndim == 4 and alphas_np.shape[1] in (1, 3):
-            # Possibly T,1,H,W — squeeze channel
-            alphas_np = np.squeeze(alphas_np, axis=1) if alphas_np.shape[1] == 1 else np.mean(alphas_np, axis=1)
-        else:
-            raise MatAnyError(f"Unexpected alphas shape from process_video: {alphas_np.shape}")
-
-        for f_bgr, a_hw in zip(frames_bgr, alphas_np):
-            a_u8 = (a_hw * 255.0 + 0.5).astype(np.uint8)
-            a_rgb = cv2.cvtColor(a_u8, cv2.COLOR_GRAY2BGR)
-            fg_bgr = (f_bgr.astype(np.float32) * (a_hw[..., None])).clip(0, 255).astype(np.uint8)
-            alpha_writer.write(a_rgb)
-            fg_writer.write(fg_bgr)