76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
# coding:utf-8
|
|
from ultralytics import YOLO
|
|
import cv2
|
|
import detect_tools as tools
|
|
from PIL import ImageFont
|
|
from paddleocr import PaddleOCR
|
|
import matplotlib.pyplot as plt
|
|
import os
|
|
|
|
def get_license_result(ocr, image):
|
|
"""
|
|
image:输入的车牌截取照片
|
|
输出，车牌号与置信度
|
|
"""
|
|
result = ocr.ocr(image, cls=True)[0]
|
|
if result:
|
|
license_name, conf = result[0][1]
|
|
if '·' in license_name:
|
|
license_name = license_name.replace('·', '')
|
|
return license_name, conf
|
|
else:
|
|
return None, None
|
|
|
|
# 获取图片地址
|
|
img_path = "images"
|
|
files = os.listdir(img_path)
|
|
s = []
|
|
for file in files:
|
|
temp = img_path+"/"+file
|
|
s.append(temp)
|
|
fontC = ImageFont.truetype("Fonts/msyhbd.ttc", 50, 0, encoding="utf-8")
|
|
|
|
# 加载ocr模型
|
|
cls_model_dir = 'paddleModels/whl/cls/ch_ppocr_mobile_v2.0_cls_infer'
|
|
rec_model_dir = 'paddleModels/whl/rec/ch/ch_PP-OCRv4_rec_infer'
|
|
ocr = PaddleOCR(use_angle_cls=False, lang="ch", det=False, cls_model_dir=cls_model_dir, rec_model_dir=rec_model_dir)
|
|
|
|
# 所需加载的模型目录
|
|
path = 'runs/detect/train/weights/best.pt'
|
|
# 加载预训练模型
|
|
# conf 0.25 object confidence threshold for detection
|
|
# iou 0.7 int.ersection over union (IoU) threshold for NMS
|
|
model = YOLO(path, task='detect')
|
|
# model = YOLO(path, task='detect',conf=0.5)
|
|
|
|
#检测图片
|
|
i = 0
|
|
for now_img in s:
|
|
now_img = tools.img_cvread(now_img)
|
|
results = model(now_img)[0]
|
|
location_list = results.boxes.xyxy.tolist()
|
|
if len(location_list) >= 1:
|
|
location_list = [list(map(int, e)) for e in location_list]
|
|
# 截取每个车牌区域的照片
|
|
license_imgs = []
|
|
for each in location_list:
|
|
x1, y1, x2, y2 = each
|
|
cropImg = now_img[y1:y2, x1:x2]
|
|
license_imgs.append(cropImg)
|
|
# 车牌识别结果
|
|
lisence_res = []
|
|
conf_list = []
|
|
for each in license_imgs:
|
|
license_num, conf = get_license_result(ocr, each)
|
|
if license_num:
|
|
lisence_res.append(license_num)
|
|
conf_list.append(conf)
|
|
else:
|
|
lisence_res.append('无法识别')
|
|
conf_list.append(0)
|
|
for text, box in zip(lisence_res, location_list):
|
|
now_img = tools.drawRectBox(now_img, box, text, fontC)
|
|
now_img = cv2.resize(now_img, dsize=None, fx=0.5, fy=0.5, interpolation=cv2.INTER_LINEAR)
|
|
# cv2.imshow("YOLOv8 Detection", now_img)
|
|
cv2.imwrite(f"./result/{i}.jpg", now_img)
|
|
i += 1 |