remove spaces references - run on hugging face as cpuremove spaces references - run on hugging face as cpu

README.md

@@ -6,7 +6,7 @@ colorFrom: yellow
 colorTo: red
 python_version: 3.10.13
 sdk: gradio
-sdk_version: 5.16.0
+sdk_version: 5.17.0
 app_file: app.py
 license: apache-2.0
 hf_oauth: true
@@ -15,7 +15,7 @@ tags:
 - depth
 - 3d
 thumbnail: >-
-  https://cdn-uploads.huggingface.co/production/uploads/6346595c9e5f0fe83fc60444/s0fQvcoiSBlH36AXpVwPi.png
+  https://cdn-uploads.huggingface.co/production/uploads/6346595c9e5f0fe83fc60444/cyAmkkrQsfDjolwuHb4ZX.png
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -10,11 +10,8 @@ from transformers import DPTForDepthEstimation, DPTImageProcessor
 
 # Initialize the image processor and depth estimation model
 image_processor = DPTImageProcessor.from_pretrained("Intel/dpt-large")
-model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
+depth_model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large", ignore_mismatched_sizes=True)
 
-import spaces
-
-@spaces.GPU(duration=90,progress=gr.Progress(track_tqdm=True))
 def process_image(image_path, resized_width=800, z_scale=208):
     """
     Processes the input image to generate a depth map and a 3D mesh reconstruction.
@@ -41,7 +38,7 @@ def process_image(image_path, resized_width=800, z_scale=208):
 
     # Perform depth estimation
     with torch.no_grad():
-        outputs = model(**encoding)
+        outputs = depth_model(**encoding)
         predicted_depth = outputs.predicted_depth
 
     # Interpolate depth to match the image size
@@ -72,7 +69,6 @@ def process_image(image_path, resized_width=800, z_scale=208):
         torch.cuda.ipc_collect()
     return [img, gltf_path, gltf_path]
 
-@spaces.GPU()
 def create_3d_obj(rgb_image, raw_depth, image_path, depth=10, z_scale=200):
     """
     Creates a 3D object from RGB and depth images.