abubakar123456 commited on
Commit
2421b42
1 Parent(s): 8193585

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -12
app.py CHANGED
@@ -1,15 +1,11 @@
1
  import argparse
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  import os
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- os.environ['CUDA_HOME'] = '/usr/local/cuda'
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- os.environ['PATH'] = os.environ['PATH'] + ':/usr/local/cuda/bin'
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  from datetime import datetime
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-
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- import spaces
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-
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  import gradio as gr
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  import numpy as np
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  import torch
 
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  from diffusers.image_processor import VaeImageProcessor
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  from huggingface_hub import snapshot_download
@@ -115,19 +111,18 @@ pipeline = CatVTONPipeline(
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  attn_ckpt_version="mix",
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  weight_dtype=init_weight_dtype(args.mixed_precision),
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  use_tf32=args.allow_tf32,
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- device='cuda'
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- #device='cpu'
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  )
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  # AutoMasker
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  mask_processor = VaeImageProcessor(vae_scale_factor=8, do_normalize=False, do_binarize=True, do_convert_grayscale=True)
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  automasker = AutoMasker(
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  densepose_ckpt=os.path.join(repo_path, "DensePose"),
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  schp_ckpt=os.path.join(repo_path, "SCHP"),
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- device='cuda',
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- #device='cpu'
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  )
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- @spaces.GPU(duration=120)
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  def submit_function(
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  person_image,
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  cloth_image,
@@ -154,8 +149,8 @@ def submit_function(
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  generator = None
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  if seed != -1:
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- generator = torch.Generator(device='cuda').manual_seed(seed)
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- #generator = torch.Generator(device='cpu').manual_seed(seed)
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  person_image = Image.open(person_image).convert("RGB")
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  cloth_image = Image.open(cloth_image).convert("RGB")
 
1
  import argparse
2
  import os
 
 
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  from datetime import datetime
4
 
 
 
 
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  import gradio as gr
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  import numpy as np
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  import torch
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+ device = torch.device('cpu') # Explicitly use CPU if desired
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  from diffusers.image_processor import VaeImageProcessor
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  from huggingface_hub import snapshot_download
 
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  attn_ckpt_version="mix",
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  weight_dtype=init_weight_dtype(args.mixed_precision),
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  use_tf32=args.allow_tf32,
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+ # device='cuda'
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+ device='cpu'
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  )
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  # AutoMasker
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  mask_processor = VaeImageProcessor(vae_scale_factor=8, do_normalize=False, do_binarize=True, do_convert_grayscale=True)
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  automasker = AutoMasker(
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  densepose_ckpt=os.path.join(repo_path, "DensePose"),
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  schp_ckpt=os.path.join(repo_path, "SCHP"),
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+ # device='cuda',
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+ device='cpu'
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  )
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  def submit_function(
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  person_image,
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  cloth_image,
 
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  generator = None
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  if seed != -1:
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+ # generator = torch.Generator(device='cuda').manual_seed(seed)
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+ generator = torch.Generator(device='cpu').manual_seed(seed)
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  person_image = Image.open(person_image).convert("RGB")
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  cloth_image = Image.open(cloth_image).convert("RGB")