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import numpy as np
import os
import matplotlib.pyplot as plt
import seaborn as sns
def visualize_tensor_frames(tensor, output_dir, tensor_name, num_frames=5):
os.makedirs(output_dir, exist_ok=True)
n, c, t, h, w = tensor.shape
tensor = tensor.squeeze(0).permute(1, 0, 2, 3) # Change to [T, C, H, W]
for i in range(min(t, num_frames)):
frame = tensor[i].cpu().numpy() # Convert to NumPy
frame = np.transpose(frame, (1, 2, 0)) # [H, W, C]
frame = (frame - frame.min()) / (frame.max() - frame.min()) # Normalize to [0, 1]
# Save or display the frame
output_path = os.path.join(output_dir, f"{tensor_name}_frame_{i + 1}.png")
plt.imsave(output_path, frame)
print(f"Saved frame {i + 1} of {tensor_name} to {output_path}")
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