将#!/usr/bin/env python2.7 -- coding: UTF-8 -- import time import cv2 from PIL import Image import numpy as np from PIL import Image if name == 'main': rtsp_url = "rtsp://127.0.0.1:8554/live" cap = cv2.VideoCapture(rtsp_url) #判断摄像头是否可用 #若可用,则获取视频返回值ref和每一帧返回值frame if cap.isOpened(): ref, frame = cap.read() else: ref = False #间隔帧数 imageNum = 0 sum=0 timeF = 24 while ref: ref,frame=cap.read() sum+=1 #每隔timeF获取一张图片并保存到指定目录 #"D:/photo/"根据自己的目录修改 if (sum % timeF == 0): # 格式转变,BGRtoRGB frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # 转变成Image frame = Image.fromarray(np.uint8(frame)) frame = np.array(frame) # RGBtoBGR满足opencv显示格式 frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) imageNum = imageNum + 1 cv2.imwrite("/root/Pictures/Pictures" + str(imageNum) + '.png', frame) print("success to get frame") #1毫秒刷新一次 k = cv2.waitKey(1) #按q退出 #if k==27:则为按ESC退出 if k == ord('q'): cap.release() break和#!/usr/bin/env python2.7 coding=UTF-8 import os import sys import cv2 from pyzbar import pyzbar def main(image_folder_path, output_file_name): img_files = [f for f in os.listdir(image_folder_path) if f.endswith(('.png'))] qr_codes_found = [] print("Image files:") for img_file in img_files: print(img_file) for img_file in img_files: img_path = os.path.join(image_folder_path,img_file) img = cv2.imread(img_path) barcodes = pyzbar.decode(img) for barcode in barcodes: if barcode.type == 'QRCODE': qr_data = barcode.data.decode("utf-8") qr_codes_found.append((img_file, qr_data)) unique_qr_codes = [] for file_name, qr_content in qr_codes_found: if qr_content not in unique_qr_codes: unique_qr_codes.append(qr_content) with open(output_file_name,'w') as f: for qr_content in unique_qr_codes: f.write("{}\n".format(qr_content)) if name == "main": image_folder_path = '/root/Pictures' output_file_name = 'qr_codes_found.txt' main(image_folder_path,output_file_name)合并成一个代码
时间: 2024-04-14 19:26:20 浏览: 189
Python使用PIL库实现验证码图片的方法
以下是将两段代码合并为一个代码的结果:
```python
#!/usr/bin/env python2.7
# -*- coding: UTF-8 -*-
import time
import cv2
from PIL import Image
import numpy as np
from PIL import Image
import os
import sys
from pyzbar import pyzbar
def main(image_folder_path, output_file_name):
img_files = [f for f in os.listdir(image_folder_path) if f.endswith(('.png'))]
qr_codes_found = []
print("Image files:")
for img_file in img_files:
print(img_file)
for img_file in img_files:
img_path = os.path.join(image_folder_path,img_file)
img = cv2.imread(img_path)
barcodes = pyzbar.decode(img)
for barcode in barcodes:
if barcode.type == 'QRCODE':
qr_data = barcode.data.decode("utf-8")
qr_codes_found.append((img_file, qr_data))
unique_qr_codes = []
for file_name, qr_content in qr_codes_found:
if qr_content not in unique_qr_codes:
unique_qr_codes.append(qr_content)
with open(output_file_name,'w') as f:
for qr_content in unique_qr_codes:
f.write("{}\n".format(qr_content))
if __name__ == '__main__':
rtsp_url = "rtsp://127.0.0.1:8554/live"
cap = cv2.VideoCapture(rtsp_url)
# 判断摄像头是否可用
# 若可用,则获取视频返回值ref和每一帧返回值frame
if cap.isOpened():
ref, frame = cap.read()
else:
ref = False
# 间隔帧数
imageNum = 0
sum = 0
timeF = 24
while ref:
ref, frame = cap.read()
sum += 1
# 每隔timeF获取一张图片并保存到指定目录
# "D:/photo/"根据自己的目录修改
if (sum % timeF == 0):
# 格式转变,BGRtoRGB
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# 转变成Image
frame = Image.fromarray(np.uint8(frame))
frame = np.array(frame)
# RGBtoBGR满足opencv显示格式
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
imageNum = imageNum + 1
cv2.imwrite("/root/Pictures/Pictures" + str(imageNum) + '.png', frame)
print("success to get frame")
# 1毫秒刷新一次
k = cv2.waitKey(1)
# 按q退出
# 如果按下的是q键,则退出循环
if k == ord('q'):
cap.release()
image_folder_path = '/root/Pictures'
output_file_name = 'qr_codes_found.txt'
main(image_folder_path,output_file_name)
```
这样,代码中的摄像头捕获和图像识别逻辑将在同一个程序中运行,并且在摄像头捕获每一帧图像后会进行图像识别操作。您可以根据需要对代码进行进一步的调整和优化。
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