Deadmon commited on
Commit
ec39d6f
1 Parent(s): e398be8

Update app.py

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Files changed (1) hide show
  1. app.py +13 -24
app.py CHANGED
@@ -27,21 +27,6 @@ device = torch.device("cuda")
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  offload = False
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  is_schnell = name == "flux-schnell"
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- model, ae, t5, clip, controlnet = None, None, None, None, None
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-
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- def load_models():
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- global model, ae, t5, clip, controlnet
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- t5 = load_t5(device, max_length=256 if is_schnell else 512)
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- clip = load_clip(device)
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- model = load_flow_model(name, device=device)
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- ae = load_ae(name, device=device)
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- controlnet = load_controlnet(name, device).to(device).to(torch.bfloat16)
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-
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- checkpoint = load_safetensors(model_path)
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- controlnet.load_state_dict(checkpoint, strict=False)
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-
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- load_models()
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-
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  def preprocess_image(image, target_width, target_height, crop=True):
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  if crop:
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  image = c_crop(image) # Crop the image to square
@@ -78,11 +63,16 @@ def generate_image(prompt, control_image, num_steps=50, guidance=4, width=512, h
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  torch_device = torch.device("cuda")
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- model.to(torch_device)
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- t5.to(torch_device)
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- clip.to(torch_device)
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- ae.to(torch_device)
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- controlnet.to(torch_device)
 
 
 
 
 
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  width = 16 * width // 16
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  height = 16 * height // 16
@@ -116,8 +106,8 @@ interface = gr.Interface(
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  gr.Image(type="pil", label="Control Image"),
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  gr.Slider(step=1, minimum=1, maximum=64, value=28, label="Num Steps"),
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  gr.Slider(minimum=0.1, maximum=10, value=4, label="Guidance"),
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- gr.Slider(minimum=128, maximum=2048, step=128, value=1024, label="Width"),
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- gr.Slider(minimum=128, maximum=2048, step=128, value=1024, label="Height"),
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  gr.Number(value=42, label="Seed"),
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  gr.Checkbox(label="Random Seed")
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  ],
@@ -127,5 +117,4 @@ interface = gr.Interface(
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  )
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  if __name__ == "__main__":
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- interface.launch()
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-
 
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  offload = False
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  is_schnell = name == "flux-schnell"
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  def preprocess_image(image, target_width, target_height, crop=True):
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  if crop:
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  image = c_crop(image) # Crop the image to square
 
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  torch_device = torch.device("cuda")
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+ torch.cuda.empty_cache() # Clear GPU cache
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+
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+ model = load_flow_model(name, device=torch_device)
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+ t5 = load_t5(torch_device, max_length=256 if is_schnell else 512)
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+ clip = load_clip(torch_device)
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+ ae = load_ae(name, device=torch_device)
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+ controlnet = load_controlnet(name, torch_device).to(torch_device).to(torch.bfloat16)
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+
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+ checkpoint = load_safetensors(model_path)
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+ controlnet.load_state_dict(checkpoint, strict=False)
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  width = 16 * width // 16
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  height = 16 * height // 16
 
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  gr.Image(type="pil", label="Control Image"),
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  gr.Slider(step=1, minimum=1, maximum=64, value=28, label="Num Steps"),
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  gr.Slider(minimum=0.1, maximum=10, value=4, label="Guidance"),
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+ gr.Slider(minimum=128, maximum=1024, step=128, value=512, label="Width"),
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+ gr.Slider(minimum=128, maximum=1024, step=128, value=512, label="Height"),
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  gr.Number(value=42, label="Seed"),
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  gr.Checkbox(label="Random Seed")
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  ],
 
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  )
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  if __name__ == "__main__":
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+ interface.launch()