要优化本地PostgreSQL到Blob的性能，可以考虑以下解决方法：

1. 使用二进制数据进行批量插入：将Blob数据以二进制格式存储在本地文件中，然后使用PostgreSQL的COPY命令或pg_bulkload工具将数据批量插入到数据库中。这种方法可以提高插入性能，尤其是在处理大量Blob数据时。

示例代码：

import psycopg2
import psycopg2.extensions

def insert_blobs(file_paths):
    conn = psycopg2.connect(database="your_database", user="your_user", password="your_password", host="your_host", port="your_port")
    cur = conn.cursor()
  
    cur.execute("CREATE TABLE IF NOT EXISTS blobs (id serial PRIMARY KEY, data bytea)")

    for file_path in file_paths:
        with open(file_path, 'rb') as f:
            data = psycopg2.extensions.Binary(f.read())
            cur.execute("INSERT INTO blobs (data) VALUES (%s)", (data,))
    
    conn.commit()
    cur.close()
    conn.close()

file_paths = ["blob1.bin", "blob2.bin", "blob3.bin"]
insert_blobs(file_paths)

2. 使用并行插入：通过使用多个线程或进程同时插入Blob数据，可以提高插入性能。可以使用Python的多线程或多进程库来实现并行插入。

示例代码：

import psycopg2
import psycopg2.extensions
import concurrent.futures

def insert_blob(file_path):
    conn = psycopg2.connect(database="your_database", user="your_user", password="your_password", host="your_host", port="your_port")
    cur = conn.cursor()
  
    cur.execute("CREATE TABLE IF NOT EXISTS blobs (id serial PRIMARY KEY, data bytea)")

    with open(file_path, 'rb') as f:
        data = psycopg2.extensions.Binary(f.read())
        cur.execute("INSERT INTO blobs (data) VALUES (%s)", (data,))

    conn.commit()
    cur.close()
    conn.close()

file_paths = ["blob1.bin", "blob2.bin", "blob3.bin"]

with concurrent.futures.ThreadPoolExecutor() as executor:
    executor.map(insert_blob, file_paths)

3. 使用预处理语句：使用PostgreSQL的预处理语句可以提高插入性能。预处理语句在执行过程中会被缓存，减少了语法解析和编译的开销。

示例代码：

import psycopg2
import psycopg2.extensions

def insert_blobs(file_paths):
    conn = psycopg2.connect(database="your_database", user="your_user", password="your_password", host="your_host", port="your_port")
    cur = conn.cursor()
  
    cur.execute("CREATE TABLE IF NOT EXISTS blobs (id serial PRIMARY KEY, data bytea)")
    cur.execute("PREPARE blob_insert AS INSERT INTO blobs (data) VALUES ($1)")

    for file_path in file_paths:
        with open(file_path, 'rb') as f:
            data = psycopg2.extensions.Binary(f.read())
            cur.execute("EXECUTE blob_insert (%s)", (data,))
    
    conn.commit()
    cur.close()
    conn.close()

file_paths = ["blob1.bin", "blob2.bin", "blob3.bin"]
insert_blobs(file_paths)

通过以上优化方法，可以提高本地PostgreSQL到Blob的性能。具体的优化效果可能因系统配置和数据量大小而有所不同，建议根据实际情况进行测试和调整。