<｜begin▁of▁sentence｜>### Instruction:
As a photographer, you might need to organize a collection of images into cohesive blocks based on visual similarities. Imagine you have a collection of photos from a wedding, and you want to identify which photos are considered to be between different clusters of guests. The CohesiveBlocks.crossing function in igraph can help you determine which photos might capture moments involving guests from different groups.
### Response:
from igraph import Graph
from igraph.clustering import CohesiveBlocks

# Create a directed graph
edges = [(0, 1), (0, 2), (1, 2), (2, 3), (3, 0)]
g = Graph(edges=edges, directed=True)

# Compute Cohesive Blocks
cb = CohesiveBlocks(g)
blocks = cb.cohesive_blocks()

# Determine which edges are crossing between clusters
crossing_edges = blocks.crossing()

# Print boolean vector indicating crossing edges
print(crossing_edges)
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