new

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.glb filter=lfs diff=lfs merge=lfs -text

PIFu/spaces.py

@@ -21,6 +21,9 @@ from apps.crop_img import process_img
 from apps.eval import Evaluator
 from types import SimpleNamespace
 import trimesh
+import glob
+
+os.environ["CUDA_VISIBLE_DEVICES"]="0"
 
 print(
     "torch: ", torch.__version__,
@@ -89,12 +92,12 @@ def process(img_path):
         print("Evaluating via PIFu", time)
         evaluator.eval(data, True)
         print("Success Evaluating via PIFu", datetime.now() - time)
-        result_path = f'{opts.results_path}/{opts.name}/result_{img_name}'
+        result_path = f'./{opts.results_path}/{opts.name}/result_{img_name}'
     except Exception as e:
         print("Error evaluating via PIFu", e)
 
     try:
-        mesh = trimesh.load(result_path + '.obj')\
+        mesh = trimesh.load(result_path + '.obj')
         # flip mesh
         mesh.apply_transform([[1, 0, 0, 0],
                               [0, 1, 0, 0],
@@ -102,16 +105,16 @@ def process(img_path):
                               [0, 0, 0, 1]])
         mesh.export(file_obj=result_path + '.glb')
         result_gltf = result_path + '.glb'
-        return result_gltf
+        return [result_gltf, result_gltf]
 
     except Exception as e:
         print("error generating MESH", e)
 
 
-examples = [["./examples/" + img] for img in sorted(os.listdir("./examples/"))]
+examples = sorted(glob.glob('examples/*.png'))
 description = '''
 # PIFu Clothed Human Digitization
-# PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
+### PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
 <base target="_blank">
 
 This is a demo for <a href="https://github.com/shunsukesaito/PIFu" target="_blank"> PIFu model </a>.
@@ -123,14 +126,14 @@ The pre-trained model has the following warning:
 <details>
 <summary>More</summary>
 
-# Image Credits
+#### Image Credits
 
 * Julien and Clem
 * [StyleGAN Humans](https://huggingface.co/spaces/hysts/StyleGAN-Human)
 * [Renderpeople: Dennis](https://renderpeople.com)
 
 
-# More
+#### More
 * https://phorhum.github.io/
 * https://github.com/yuliangxiu/icon
 * https://shunsukesaito.github.io/PIFuHD/
@@ -141,14 +144,15 @@ The pre-trained model has the following warning:
 iface = gr.Interface(
     fn=process,
     description=description,
-    inputs=gr.Image(type="filepath", label="Input Image"),
-    outputs=gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model"),
+    inputs=gr.inputs.Image(type="filepath", label="Input Image"),
+    outputs=[
+        gr.outputs.Image3D(
+            clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model"),
+        gr.outputs.File(label="Download 3D Model")
+    ],
     examples=examples,
     allow_flagging="never",
-    cache_examples=True
-
-
 )
 
 if __name__ == "__main__":
-    iface.launch(debug=True, enable_queue=False)
+    iface.launch(debug=True, enable_queue=False, cache_examples=True)

README.md

@@ -4,7 +4,7 @@ emoji: 🧍🏽‍♀️🧍🏻🧍🏽‍♂️
 colorFrom: pink
 colorTo: green
 sdk: gradio
-sdk_version: 2.9.0b8
+sdk_version: 2.9.4
 app_file: ./PIFu/spaces.py
 pinned: false
 python_version: 3.7.13

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gradio_cached_examples/log.csv

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-'output/1.glb','','','2022-04-26 14:01:09.394488'
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-'output/8.glb','','','2022-04-26 14:01:02.142050'
-'output/9.glb','','','2022-04-26 14:01:01.142050'
+'3D Model','Download 3D Model'
+'3D Model/0.glb','Download 3D Model/0.glb'
+'3D Model/1.glb','Download 3D Model/1.glb'
+'3D Model/2.glb','Download 3D Model/2.glb'
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+'3D Model/7.glb','Download 3D Model/7.glb'
+'3D Model/8.glb','Download 3D Model/8.glb'

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requirements.txt

@@ -21,4 +21,5 @@ torchvision==0.5.0
 trimesh==3.5.23
 tqdm==4.64.0
 paddlehub
-paddlepaddle
+paddlepaddle
+glob2