Alessio Grancini commited on
Commit
297af59
·
verified ·
1 Parent(s): a45b657

Update app.py

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Files changed (1) hide show
  1. app.py +5 -7
app.py CHANGED
@@ -2,6 +2,7 @@ from ultralytics import YOLO
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  import cv2
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  import gradio as gr
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  import numpy as np
 
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  import os
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  import torch
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  import utils
@@ -13,21 +14,20 @@ from point_cloud_generator import display_pcd
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- import spaces # Required for ZeroGPU
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- # Ensure CUDA is NOT initialized before ZeroGPU assigns a device
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- torch.backends.cudnn.enabled = False # Prevents CUDA errors on first GPU allocation
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  def initialize_gpu():
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  """Ensure ZeroGPU assigns a GPU before initializing CUDA"""
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  global device
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  try:
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- with spaces.GPU(): # Ensures GPU is allocated
 
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  if torch.cuda.is_available():
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  device = torch.device("cuda")
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  print(f"✅ GPU initialized: {torch.cuda.get_device_name(0)}")
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- torch.cuda.empty_cache() # Clear memory
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  else:
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  print("❌ No GPU detected after ZeroGPU allocation.")
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  device = torch.device("cpu")
@@ -35,8 +35,6 @@ def initialize_gpu():
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  print(f"🚨 GPU initialization failed: {e}")
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  device = torch.device("cpu")
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- # ✅ Don't call CUDA here!
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- device = torch.device("cpu") # Default to CPU
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  # Run GPU initialization before using CUDA
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  initialize_gpu()
 
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  import cv2
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  import gradio as gr
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  import numpy as np
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+ import spaces
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  import os
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  import torch
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  import utils
 
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+ device = torch.device("cpu") # Start in CPU mode
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+
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  def initialize_gpu():
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  """Ensure ZeroGPU assigns a GPU before initializing CUDA"""
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  global device
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  try:
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+ with spaces.GPU(): # Ensures ZeroGPU assigns a GPU
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+ torch.cuda.empty_cache() # Prevent leftover memory issues
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  if torch.cuda.is_available():
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  device = torch.device("cuda")
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  print(f"✅ GPU initialized: {torch.cuda.get_device_name(0)}")
 
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  else:
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  print("❌ No GPU detected after ZeroGPU allocation.")
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  device = torch.device("cpu")
 
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  print(f"🚨 GPU initialization failed: {e}")
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  device = torch.device("cpu")
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  # Run GPU initialization before using CUDA
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  initialize_gpu()