TypeError: нехешируемый тип: 'numpy.ndarray' в массиве для установки

Невозможно преобразовать элементы numpy.ndarray напрямую в набор. Вам необходимо преобразовать numpy.ndarray в хешируемый тип, например кортеж.

Что-то вроде этого:

import numpy as np

def evaluate_retrieval(query_idx, retrieved_indices, relevant_indices):
    retrieved_indices_tuples = tuple(tuple(tuple(pixel) for pixel in row) for row in retrieved_indices)
    
    retrieved_indices_set = set(retrieved_indices_tuples)
    
    relevant_indices_set = set(relevant_indices)
    
    # Calculate the intersection of the sets
    relevant_retrieved = len(retrieved_indices_set.intersection(relevant_indices_set))
    
    precision = relevant_retrieved / len(retrieved_indices_set) if len(retrieved_indices_set) > 0 else 0
    
    return precision

retrieved_indices = np.random.randint(0, 256, (128, 128, 3))  # Sample data
relevant_indices = [((0, 0, 0), (1, 1, 1), (2, 2, 2))]  # Sample relevant indices

precision = evaluate_retrieval(0, retrieved_indices, relevant_indices)
print(f"Precision: {precision}")

Я решил эту проблему таким образом:

retrieved_indices_tuples = tuple(
    tuple(
        tuple(
            tuple(pixel) for pixel in slice
        ) for slice in row
    ) for row in retrieved_indices
)
    print(type(retrieved_indices_tuples))  # Should print <class 'tuple'>
    print(type(retrieved_indices_tuples[0]))  # Should print <class 'tuple'>
    print(type(retrieved_indices_tuples[0][0]))  # Should print <class 'tuple'>
    print(type(retrieved_indices_tuples[0][0][0]))  # Should print <class 'tuple'>
    print(type(retrieved_indices_tuples[0][0][0][0])) # Should print <class 'int'>