mirror of
https://github.com/MemeMeow-Studio/MemeMeow.git
synced 2026-10-17 04:41:01 +08:00
Infstellar
150 lines
4.5 KiB
Python
150 lines
4.5 KiB
Python
import hashlib
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import os
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import sys
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import threading
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import requests
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import pickle
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import random
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from typing import List, Optional, Union
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import numpy as np
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import cv2
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from base import *
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def get_file_hash(file_path, algorithm='sha256'):
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"""
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该函数用于计算文件的哈希值
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:param file_path: 文件的路径
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:param algorithm: 哈希算法，默认为 sha256
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:return: 文件的哈希值
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"""
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# 根据指定的算法创建哈希对象
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hash_object = hashlib.new(algorithm)
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try:
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# 以二进制模式打开文件
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with open(file_path, 'rb') as file:
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# 分块读取文件内容，避免大文件占用过多内存
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for chunk in iter(lambda: file.read(4096), b""):
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# 更新哈希对象的内容
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hash_object.update(chunk)
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# 获取最终的哈希值
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return hash_object.hexdigest()
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except FileNotFoundError:
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print(f"文件 {file_path} 未找到。")
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return None
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from PIL import Image
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import base64
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from io import BytesIO
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def image_to_base64_jpg(image_path):
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try:
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# 打开图像文件
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with Image.open(image_path) as img:
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img = img.convert('RGB')
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# 创建一个内存缓冲区
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buffer = BytesIO()
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# 将图像保存为JPEG格式到缓冲区
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img.save(buffer, format="JPEG")
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# 获取缓冲区中的二进制数据
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img_bytes = buffer.getvalue()
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# 将二进制数据编码为Base64字符串
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base64_encoded = base64.b64encode(img_bytes).decode('utf-8')
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img.close()
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return base64_encoded
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except Exception as e:
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raise (f"处理图像时出现错误: {e}")
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def load_image(image_path) -> np.ndarray:
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# opencv不能打开含有中文路径的图片和gif图，一定要用PIL
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try:
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# 打开图像文件
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with Image.open(image_path) as img:
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img = img.convert('RGB')
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npimg = np.array(img)
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img.close()
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npimg = cv2.cvtColor(npimg, cv2.COLOR_RGB2BGR)
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return npimg
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except Exception as e:
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raise (f"处理图像时出现错误: {e}")
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def calculate_image_similarity(img1, img2):
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"""
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该函数用于计算两张图片的相似度
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:param image_path1: 第一张图片的路径
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:param image_path2: 第二张图片的路径
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:return: 两张图片的相似度值
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"""
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# 确保图片尺寸相同
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img2 = cv2.resize(img2, (img1.shape[1], img1.shape[0]))
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# # 计算直方图
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# hist1 = cv2.calcHist([img1], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
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# hist2 = cv2.calcHist([img2], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
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#
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# # 归一化直方图
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# hist1 = cv2.normalize(hist1, hist1).flatten()
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# hist2 = cv2.normalize(hist2, hist2).flatten()
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#
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# # 计算相似度
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# similarity = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
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result = cv2.matchTemplate(img1, img2, cv2.TM_CCORR_NORMED) # TM_CCOEFF_NORMED
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min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
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similarity = max_val
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if DEBUG_MODE:
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logger.trace(similarity)
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return similarity
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import requests
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import os
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def download_file(url, save_path, ignore_ssl=True):
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"""
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下载指定链接的文件到指定目录，可选择忽略 SSL 验证。
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:param url: 文件的下载链接
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:param save_path: 文件保存的路径
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:param ignore_ssl: 是否忽略 SSL 验证，默认为 True
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:return: 如果下载成功返回 True，否则返回 False
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"""
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try:
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# 创建保存文件的目录
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verify_folder(save_path)
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url = url.replace('\\\\', '/').replace('\\', '/')
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# 发送请求
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response = requests.get(url, verify=not ignore_ssl)
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# 检查响应状态码
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response.raise_for_status()
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# 将文件内容写入指定路径
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with open(save_path, 'wb') as file:
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file.write(response.content)
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return True
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except requests.RequestException as e:
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print(f"下载文件时发生错误: {e}")
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return False
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except Exception as e:
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print(f"发生未知错误: {e}")
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return False
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def download_files(urls_and_paths):
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threads = []
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# 为每个文件下载任务创建一个线程
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for url, save_path in urls_and_paths:
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thread = threading.Thread(target=download_file, args=(url, save_path))
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threads.append(thread)
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thread.start()
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# 等待所有线程完成
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for thread in threads:
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thread.join()
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return |