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Commit
482feb0
1 Parent(s): dd12f3e

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Files changed (3) hide show
  1. PIFu/apps/eval_spaces.py +1 -1
  2. app.py +9 -6
  3. requirements.txt +3 -1
PIFu/apps/eval_spaces.py CHANGED
@@ -38,7 +38,7 @@ class Evaluator:
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  ])
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  # set cuda
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  cuda = torch.device('cuda:%d' % opt.gpu_id) if torch.cuda.is_available() else torch.device('cpu')
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- print("CUDDAAAAA ???", torch.cuda.get_device_name(0))
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  # create net
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  netG = HGPIFuNet(opt, projection_mode).to(device=cuda)
 
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  ])
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  # set cuda
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  cuda = torch.device('cuda:%d' % opt.gpu_id) if torch.cuda.is_available() else torch.device('cpu')
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+ print("CUDDAAAAA ???", torch.cuda.get_device_name(0) if torch.cuda.is_available() else "NO ONLY CPU")
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  # create net
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  netG = HGPIFuNet(opt, projection_mode).to(device=cuda)
app.py CHANGED
@@ -1,5 +1,9 @@
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  import os
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- os.system("pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html")
 
 
 
 
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  from pydoc import describe
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  from huggingface_hub import hf_hub_download
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  import gradio as gr
@@ -30,21 +34,20 @@ def process(img_path):
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  print("image name", img_name)
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  img = Image.open(img_path)
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  # remove background
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- print("remove background")
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  foreground = Image.fromarray(remove_bg.inference(img), 'RGBA')
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  foreground.save("./PIFu/inputs/" + img_name + ".png")
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- print("align mask with input training image")
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  subprocess.Popen(["python", "./apps/crop_img.py", "--input_image",
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  f'./inputs/{img_name}.png', "--out_path", "./inputs"], cwd="PIFu").communicate()
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- print("generate 3D model")
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  subprocess.Popen("./scripts/test.sh", env={
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  **env,
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  "INPUT_IMAGE_PATH": f'./inputs/{img_name}.png',
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  "VOL_RES": "128"},
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  cwd="PIFu").communicate()
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-
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- print("inference")
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  return f'./PIFu/results/spaces_demo/result_{img_name}.glb'
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  import os
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+ try:
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+ os.system("pip install --upgrade torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html")
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+ except Exception as e:
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+ print(e)
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+
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  from pydoc import describe
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  from huggingface_hub import hf_hub_download
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  import gradio as gr
 
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  print("image name", img_name)
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  img = Image.open(img_path)
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  # remove background
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+ print("Removeing background")
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  foreground = Image.fromarray(remove_bg.inference(img), 'RGBA')
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  foreground.save("./PIFu/inputs/" + img_name + ".png")
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+ print("Aliging mask with input training image")
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  subprocess.Popen(["python", "./apps/crop_img.py", "--input_image",
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  f'./inputs/{img_name}.png', "--out_path", "./inputs"], cwd="PIFu").communicate()
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+ print("Generating 3D model")
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  subprocess.Popen("./scripts/test.sh", env={
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  **env,
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  "INPUT_IMAGE_PATH": f'./inputs/{img_name}.png',
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  "VOL_RES": "128"},
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  cwd="PIFu").communicate()
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+ print("DONE 3D model")
 
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  return f'./PIFu/results/spaces_demo/result_{img_name}.glb'
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requirements.txt CHANGED
@@ -17,4 +17,6 @@ Shapely==1.7.0
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  six==1.14.0
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  tqdm==4.43.0
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  trimesh==3.5.23
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- xxhash==1.4.3
 
 
 
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  six==1.14.0
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  tqdm==4.43.0
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  trimesh==3.5.23
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+ xxhash==1.4.3
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+ torch==1.11
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+ torchvision==0.12.0