import numpy as np
import json

json_file_path = './knn-model.json'
bin_file_path = './knn-model.bin'

with open(json_file_path, 'r') as f:
    model_data = json.load(f)

with open(bin_file_path, 'rb') as f:
    binary_full_data = f.read()

feature_dim = model_data['featureDim']

print(f"Feature Dimension: {feature_dim}")

for label, meta in model_data['dataset'].items():
    start_byte = meta['start']
    length_byte = meta['length']

    print(f"\n--- Class: {label} ---")
    print(f"Start Byte: {start_byte}")
    print(f"Length Byte: {length_byte}")

    # 提取当前类别的数据片段
    class_binary_data = binary_full_data[start_byte : start_byte + length_byte]

    # 转换为 Float32 数组
    try:
        class_features_elements = np.frombuffer(class_binary_data, dtype=np.float32)
        num_elements = len(class_features_elements)
        print(f"Float32 elements extracted: {num_elements}")

        if num_elements % feature_dim == 0:
            num_samples = num_elements // feature_dim
            print(f"SUCCESS: Aligned. Number of samples: {num_samples}")
        else:
            print(f"ERROR: Not aligned. {num_elements} elements / {feature_dim} dim = {num_elements / feature_dim} (not an integer).")
            print(f"Expected length in bytes to be multiple of {feature_dim * 4} = {feature_dim * 4} bytes.")
            print(f"Actual length in bytes: {length_byte}. Remainder when dividing by {feature_dim * 4}: {length_byte % (feature_dim * 4)}")

    except Exception as e:
        print(f"Error processing binary data for class {label}: {e}")