import cv2 as cv
from skimage import feature 
import numpy as np
import time 
from joblib import dump,load
import yaml 
import os
import sys




# 获取 0_setting.yaml 中的键 key 对应的值 value
def get(key):
    with open("0_setting.yaml","r",encoding='utf-8') as f:
        config=yaml.safe_load(f)
    value=config[key]
    return value

# 预处理图像, 把图像设置为指定大小之后，展平返回
def preprocess_image(file_name, new_size):
    # 1. 读取图像灰度图
    img=cv.imdecode(np.fromfile(file_name,dtype=np.uint8),-1)
    img=cv.cvtColor(img,cv.COLOR_BGR2GRAY)
    img=cv.resize(img,new_size,interpolation=cv.INTER_NEAREST)
    #2.hog滤波
    img=feature.hog(img,orientations=9,pixels_per_cell=(8,8),cells_per_block=(2,2))


    #print(img.shape)
    
    return img

# 用joblib把叫做 name 的对象 obj 保存(序列化)到位置 loc
def dump1(obj, name, loc):
    start = time.time()
    print(f"把{name}保存到{loc}") 
    # 此处序列化对象
    dump(obj,loc)
    end = time.time()
    print(f"保存完毕,文件位置:{loc}, 大小:{os.path.getsize(loc) / 1024 / 1024:.3f}M")
    print(f"运行时间:{end - start:.3f}秒")

# 用joblib读取(反序列化)位置loc的对象obj,对象名为name
def load1(name, loc):
    print(f"从{loc}提取文件{name}")
    # 此处反序列化对象
    obj=load(loc)
    return obj