new

app.py

@@ -396,17 +396,10 @@ with gr.Blocks(css="""
                     with gr.Row(elem_id="example-container"):
                         gr.Examples(
                             examples=[
-                                # ["A tree with red leaves"],
-                                # ["A dragon with black texture"],
                                 ["A girl with pink hair"],
                                 ["A boy playing guitar"],
-
-
                                 ["A dog wearing a hat"],
                                 ["A boy playing basketball"],
-                                # [""],
-                                # [""],
-                                # [""],
 
                             ],
                             inputs=[prompt],  # 将选中的示例填入 prompt 文本框

pipeline/kiss3d_wrapper.py

@@ -69,14 +69,16 @@ def init_wrapper_from_config(config_path):
     # flux_lora_pth = config_['flux'].get('lora', None)
     flux_lora_pth = hf_hub_download(repo_id="LTT/Kiss3DGen", filename="rgb_normal_large.safetensors", repo_type="model", token=access_token)
     flux_redux_pth = config_['flux'].get('redux', None)
-    taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype_[flux_dtype]).to(flux_device)
+    # taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype_[flux_dtype]).to(flux_device)
     if flux_base_model_pth.endswith('safetensors'):
         flux_pipe = FluxImg2ImgPipeline.from_single_file(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
     else:
         flux_pipe = FluxImg2ImgPipeline.from_pretrained(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
     # flux_pipe.enable_vae_slicing()
     # flux_pipe.enable_vae_tiling()
-    flux_pipe.vae = taef1
+    # flux_pipe.vae = taef1
+    flux_pipe.vae.enable_slicing() # 多批次生图优化
+    flux_pipe.vae.enable_tiling()
     
     # flux_pipe.enable_sequential_cpu_offload()
     # load flux model and controlnet