Spaces:
Running
on
Zero
Running
on
Zero
infinity1096
commited on
Commit
·
b91a473
1
Parent(s):
7b12cd5
add spaces
Browse files
app.py
CHANGED
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@@ -11,6 +11,7 @@ import subprocess
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import sys
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import subprocess
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import importlib
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try:
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import uniception
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@@ -38,10 +39,6 @@ from uniflowmatch.utils.viz import warp_image_with_flow
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model = None
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USE_REFINEMENT_MODEL = False
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use_gpu = torch.cuda.is_available()
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if use_gpu:
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print("Using GPU for processing.")
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def initialize_model(use_refinement: bool = False):
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"""Initialize the model - call this once at startup"""
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global model, USE_REFINEMENT_MODEL
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@@ -59,17 +56,13 @@ def initialize_model(use_refinement: bool = False):
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if hasattr(model, "eval"):
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model.eval()
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if use_gpu:
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print("Moving model to GPU...")
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model = model.to("cuda")
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print("Model loaded successfully!")
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return True
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except Exception as e:
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print(f"Error loading model: {e}")
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return False
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-
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def process_images(source_image, target_image, model_type_choice):
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"""
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Process two uploaded images and return visualizations
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@@ -86,6 +79,9 @@ def process_images(source_image, target_image, model_type_choice):
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if model is None:
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return None, None, None, "Model not loaded. Please restart the application."
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try:
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# Convert PIL images to numpy arrays
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source_np = np.array(source_image)
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import sys
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import subprocess
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import importlib
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import spaces
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try:
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import uniception
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model = None
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USE_REFINEMENT_MODEL = False
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def initialize_model(use_refinement: bool = False):
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"""Initialize the model - call this once at startup"""
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global model, USE_REFINEMENT_MODEL
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if hasattr(model, "eval"):
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model.eval()
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print("Model loaded successfully!")
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return True
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except Exception as e:
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print(f"Error loading model: {e}")
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return False
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@spaces.GPU
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def process_images(source_image, target_image, model_type_choice):
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"""
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Process two uploaded images and return visualizations
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if model is None:
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return None, None, None, "Model not loaded. Please restart the application."
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model = model.to("cuda" if torch.cuda.is_available() else "cpu")
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use_gpu = torch.cuda.is_available()
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try:
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# Convert PIL images to numpy arrays
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source_np = np.array(source_image)
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