python中cv2.imdecode()与cv2.imencode()的使用小结

import cv2
img_path = "/home/dataset/狗/101.jpg"
img = cv2.imread(img_path)

import numpy as np
import cv2
from PIL import Image
img_path = "/home/dataset/狗/101.jpg"
arr_img = np.fromfile(img_path, dtype=np.uint8)   # 将文本或二进制文件中数据构造成数组
img = cv2.imdecode(arr_img, cv2.IMREAD_COLOR)     # BGR通道，和cv2.imread()读图片一样
# 转成Image对象
# rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# pil_img = Image.fromarray(rgb_img)

# 用opencv自带的显示函数显示图像
cv2.imshow("opencv imgshow", img)
cv2.waitKey()

# 用matplotlib.pyplot显示图像
from matplotlib import pyplot as plt
plt.figure("pylot imgshow")  # 图像窗口名称
plt.imshow(img)
plt.axis('off')  # 关掉坐标轴为 off
plt.title('pylot imgshow')  # 图像题目
plt.show()

import cv2
save_path = "/home/dataset/狗/101.jpg"
cv2.imwrite(save_path, img)

import cv2
import numpy as np
img_path = "/home/dataset/狗/101.jpg"
arr_img = np.fromfile(img_path, dtype=np.uint8)   # 将文本或二进制文件中数据构造成数组
img = cv2.imdecode(arr_img, cv2.IMREAD_COLOR)     # BGR通道，和cv2.imread()读图片一样

arr_buffer = cv2.imencode('.jpg', img)[1]
# 保存为图片
save_path = "/home/dataset/狗/101_copy.jpg"
arr_buffer.tofile(save_path)    # 保存到文件

# 保存为txt
data_encode = np.array(arr_buffer)
str_encode = data_encode.tostring()
# 缓存数据保存到本地
with open('./img_encode.txt', 'w') as f:
    f.write(str_encode)
    f.flush

from flask import Flask, request, jsonify
import numpy as np
import cv2

app = Flask(__name__)

@app.route("/upload_img", methods=['POST'])
def upload_img():
    f_obj = request.files.get('file', None)
    if f_obj is None:
        return jsonify("没有接收到图片")
    else:
        img_data = f_obj.read()
        #nparr = np.fromstring(img_data, np.uint8)
        nparr = np.frombuffer(img_data, np.uint8)   # 两者均可，建议使用np.frombuffer
        img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
        cv2.imwrite("./received_img.jpg", img)
        return jsonify("接收图片成功")


if __name__ == "__main__":
    app.run(host='0.0.0.0', port=9000)

import requests
import time

upload_img_url = "http://localhost:9000/upload_img"
imgfile = {'file':open('/home/dataset/狗/101.jpg','rb')}
start = time.time()
r = requests.post(upload_img_url, files=imgfile)
end = time.time()
running_time = end - start
print(f"时间消耗: {running_time:.5f} 秒")
print(f"响应内容：{r.text}")