zeroGPU OK

Rodin.py

@@ -73,9 +73,8 @@ def crop_image(image, type):
         new_image.paste(cropped_image, (i * 360, 0))
     return new_image
 
-# Perform Rodin mesh operation
-
 
+# Perform Rodin mesh operation
 def rodin_mesh(prompt, group_uuid, settings, images, name, token):
     images = [convert_base64_to_binary(img) for img in images]
 
@@ -95,9 +94,8 @@ def rodin_mesh(prompt, group_uuid, settings, images, name, token):
     response = requests.post(f"{BASE_URL}/task/rodin_mesh", data=m, headers=headers)
     return response
 
-# Convert base64 to binary since the result from `rodin_preprocess_image` is encoded with base64
-
 
+# Convert base64 to binary since the result from `rodin_preprocess_image` is encoded with base64
 def convert_base64_to_binary(base64_string):
     if ',' in base64_string:
         base64_string = base64_string.split(',')[1]

app.py

@@ -1,6 +1,6 @@
-from OpenCLAY.openclay.pipeline_openclay import OpenClayPipeline
-from OpenCLAY.openclay.models import ClayVAE, ClayLDM, ClayConditionNet
-from OpenCLAY.openclay.utils import read_image_square
+from openclay.pipeline_openclay import OpenClayPipeline
+from openclay.models import ClayVAE, ClayLDM, ClayConditionNet
+from openclay.utils import read_image_square
 from transformers import Dinov2Model, BitImageProcessor, CLIPTextModel, CLIPTokenizer
 import trimesh
 import cv2
@@ -20,7 +20,7 @@ import spaces
 import re
 from gradio_fake3d import Fake3D
 from PIL import Image
-from Rodin import Generator, crop_image, log
+from Rodin import Generator, crop_image, log, convert_base64_to_binary
 from constant import *
 
 generator = Generator(USER, PASSWORD, TOKEN)
@@ -58,8 +58,9 @@ def read_image(path, image_processor, image_encoder, size=224):
     return render, image_embeds_patch
 
 @spaces.GPU
-def local_inference(block_prompt, block_image):
-    _, image_embeds_patch = read_image(block_image, image_processor, image_encoder)
+def local_inference(block_prompt, cache_image_base64):
+    image = convert_base64_to_binary(cache_image_base64)
+    _, image_embeds_patch = read_image(image, image_processor, image_encoder)
 
     mesh = pipe(
         prompt=block_prompt, negative_prompt='fragmentation.',
@@ -389,7 +390,7 @@ with gr.Blocks() as demo:
         queue=True
     ).success(
         fn=local_inference,
-        inputs=[block_prompt, block_image],
+        inputs=[block_prompt, cache_image_base64],
         outputs=[block_3d],
         queue=True
     ).then(