<｜begin▁of▁sentence｜>### Instruction:
As a videographer, one might encounter a scenario where they are tasked with recording and producing video content for a complex event, such as a large music festival. In this situation, the organizer may want to understand the maximum flow of attendee movement through different pathways within the festival grounds, taking into account the capacity of each pathway. To address this, the videographer's team could use networkx, a Python library for creating and analyzing complex networks, to calculate the maximum flow from the entrance (source vertex) to the main stage area (target vertex) while considering the capacities of the pathways (directed edges).
### Response:
from igraph import Graph

# Define the edges and the corresponding capacities for the graph
capacity = [10, 10, 10, 1, 6, 4]
edges = [(0, 1), (1, 2), (0, 2), (1, 3), (3, 4), (2, 4)]

# Create the graph with the defined edges and capacitiesg = Graph(edges=edges)
g.es['capacity'] = capacity

# Calculate the maximum flow value between vertex 0 (source) and vertex 4 (target)
max_flow_value = g.maxflow_value(source=0, target=4, capacity='capacity')
print('The value of the maximum flow from vertex 0 to 4 is:', max_flow_value)
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