Alesteba commited on
Commit
89c6edc
·
1 Parent(s): 9f80763

Update app.py

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Files changed (1) hide show
  1. app.py +7 -2
app.py CHANGED
@@ -39,9 +39,13 @@ import base64
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  file = open(r'./training(3).gif', 'rb')
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  contents = file.read()
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- data_url = base64.b64encode(contents).decode('utf-8-sig')
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  file.close()
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- st.markdown(f'<img src="data:image/gif;base64,{data_url}>',unsafe_allow_html = True)
 
 
 
 
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  st.markdown("[NeRF](https://arxiv.org/abs/2003.08934) proposes an ingenious way to synthesize novel views of a scene by modelling the volumetric scene function through a neural network. The network learns to model the volumetric scene, thus generating novel views (images) of the 3D scene that the model was not shown at training time.")
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  st.markdown("![](https://github.com/alesteba/training_NeRF/blob/e89da9448b3993117c78532c14c7142970f0d8df/training(3).gif)")
@@ -54,6 +58,7 @@ st.markdown("## Interactive Demo")
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  from huggingface_hub import from_pretrained_keras
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  nerf_loaded = from_pretrained_keras("Alesteba/NeRF_ficus")
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  # set the values of r theta phi
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  r = 4.0
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  theta = st.slider("",min_value=0.0, max_value=360.0, label_visibility="hidden")
 
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  file = open(r'./training(3).gif', 'rb')
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  contents = file.read()
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+ data_url = base64.b64encode(contents).decode('utf-8')
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  file.close()
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+
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+ st.markdown(
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+ f'<img src="data:image/gif;base64,{data_url}" alt="cat gif">',
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+ unsafe_allow_html=True,
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+ )
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  st.markdown("[NeRF](https://arxiv.org/abs/2003.08934) proposes an ingenious way to synthesize novel views of a scene by modelling the volumetric scene function through a neural network. The network learns to model the volumetric scene, thus generating novel views (images) of the 3D scene that the model was not shown at training time.")
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  st.markdown("![](https://github.com/alesteba/training_NeRF/blob/e89da9448b3993117c78532c14c7142970f0d8df/training(3).gif)")
 
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  from huggingface_hub import from_pretrained_keras
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  nerf_loaded = from_pretrained_keras("Alesteba/NeRF_ficus")
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+
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  # set the values of r theta phi
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  r = 4.0
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  theta = st.slider("",min_value=0.0, max_value=360.0, label_visibility="hidden")