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app.py

@@ -385,15 +385,6 @@ def preprocess_image(input: Image.Image) -> Image.Image:
     return output
 
 
-def preprocess_images(images):
-    """
-    Preprocess a list of input images for multi-image conditioning.
-    """
-    images = [image[0] for image in images]
-    processed_images = [preprocess_image(img) for img in images]
-    return processed_images
-
-
 def pack_state(latents: Tuple[SparseTensor, SparseTensor, int]) -> dict:
     shape_slat, tex_slat, res = latents
     return {
@@ -487,18 +478,9 @@ def split_image(image: Image.Image) -> List[Image.Image]:
     return [preprocess_image(image) for image in images]
 
 
-def preprocess_for_generate(multiimages):
-    """Preprocess images before GPU generation. No GPU needed — background
-    removal is a network call to the BRIA RMBG Space."""
-    if not multiimages:
-        raise gr.Error("Please upload images or select an example first.")
-    images = [image[0] for image in multiimages]
-    return [preprocess_image(img) for img in images]
-
-
 @spaces.GPU(duration=120)
 def image_to_3d(
-    processed_images,
+    multiimages,
     seed,
     resolution,
     ss_guidance_strength,
@@ -518,6 +500,13 @@ def image_to_3d(
     req: gr.Request,
     progress=gr.Progress(track_tqdm=True),
 ):
+    if not multiimages:
+        raise gr.Error("Please upload images or select an example first.")
+
+    # Preprocess images (background removal for images without alpha)
+    images = [image[0] for image in multiimages]
+    processed_images = [preprocess_image(img) for img in images]
+
     # --- Sampling ---
     outputs, latents = pipeline.run_multi_image(
         processed_images,
@@ -750,7 +739,6 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="orange", neutral_hue="slate"),
                 )
 
     output_buf = gr.State()
-    processed_buf = gr.State()
     selected_img_idx = gr.State(value=None)
 
 
@@ -776,24 +764,14 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="orange", neutral_hue="slate"),
         outputs=[multiimage_prompt, selected_img_idx],
     )
 
-    multiimage_prompt.upload(
-        preprocess_images,
-        inputs=[multiimage_prompt],
-        outputs=[multiimage_prompt],
-    )
-
     generate_btn.click(
         get_seed,
         inputs=[randomize_seed, seed],
         outputs=[seed],
-    ).then(
-        preprocess_for_generate,
-        inputs=[multiimage_prompt],
-        outputs=[processed_buf],
     ).then(
         image_to_3d,
         inputs=[
-            processed_buf, seed, resolution,
+            multiimage_prompt, seed, resolution,
             ss_guidance_strength, ss_guidance_rescale, ss_sampling_steps, ss_rescale_t,
             shape_slat_guidance_strength, shape_slat_guidance_rescale, shape_slat_sampling_steps, shape_slat_rescale_t,
             tex_slat_guidance_strength, tex_slat_guidance_rescale, tex_slat_sampling_steps, tex_slat_rescale_t,