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'''
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author ： Hatcher W
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Email： hcwang@semi.ac.cn
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use: 用于检测voc数据集是否正确，
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input:（图像的文件夹路径，图像标签文件夹路径）
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output：check路径，所有的可视化结果都在里面
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'''
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import os
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import cv2
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import xml.dom.minidom
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from tqdm import tqdm
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from detection import fine_class_names
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from Y5.utils.plots import plot_one_box
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import numpy as np
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from imatovideo import images_to_video,images_to_video_bigtosmall
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from cv2AddChineseText import cv2AddChineseText
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#BHQ_name = ['Grus_vipio','Grus_leucogeranus','Grus_monacha']
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BHQ_name = ["Mallard", "Anas_poecilorhyncha", "Greylag_Goose", "Swan_Goose", "Domestic_goose","Podiceps_ruficollis"]
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# CUI BHQ_chinese = ['绿头鸭', '斑嘴鸭', '灰雁', '鸿雁', '家鹅', '小鷿鷈']
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BHQ_chinese = ["Mallard", "Anas_poecilorhyncha", "Greylag_Goose", "Swan_Goose", "Domestic_goose","Podiceps_ruficollis"]
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#BHQ_chinese = ['白枕鹤', '白鹤', '白头鹤']
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#BHQ_chinese = ['White-naped Crane', 'Siberian_crane', 'Hooded_Crane']
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image_path="/data1/Hatcher/model/data_MPKFNet/result_raw/hiv00024/"
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annotation_path="/data1/Hatcher/model/data_MPKFNet/result_xml/hiv00024Detection/"
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save_path ="/data1/Hatcher/model/data_MPKFNet/result/hiv00024Detection-English/"
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if not os.path.exists(save_path):
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os.makedirs(save_path)
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def _check_voc(image_path,annotation_path,save_path):
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files_name = os.listdir(image_path)
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files_name.sort()
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num_image=0
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num_count_old = 0
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for filename_ in tqdm(files_name):
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filename, extension= os.path.splitext(filename_)
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#filename=filename.split('__')[0]
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img_path =image_path+filename+'.jpg'
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xml_path =annotation_path+filename+'.xml'
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img = cv2.imread(img_path)
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width_or = img.shape[1]
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if img is None:
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pass
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try:
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dom = xml.dom.minidom.parse(xml_path)
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except:
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#os.remove(img_path)
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continue
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root = dom.documentElement
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objects=dom.getElementsByTagName("object")
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num_detect = 0
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spiec_number = [0 for x in range(0,len(BHQ_name))]
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for object in objects:
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bndbox = object.getElementsByTagName('bndbox')[0]
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xmin = bndbox.getElementsByTagName('xmin')[0]
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ymin = bndbox.getElementsByTagName('ymin')[0]
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xmax = bndbox.getElementsByTagName('xmax')[0]
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ymax = bndbox.getElementsByTagName('ymax')[0]
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#print(xmin.childNodes[0].data)
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#print(type(xmin.childNodes[0].data))
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xmin_data=int(xmin.childNodes[0].data)
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ymin_data=int(ymin.childNodes[0].data)
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xmax_data=int(xmax.childNodes[0].data)
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ymax_data=int(ymax.childNodes[0].data)
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xyxy = [xmin_data,ymin_data,xmax_data,ymax_data]
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label_name=object.getElementsByTagName('name')[0].childNodes[0].data
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if int(label_name) == 99999:
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label = f'{int(label_name)}'
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else:
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label = f'{fine_class_names[int(label_name)]}'
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if label in BHQ_name:
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label = BHQ_chinese[BHQ_name.index(label)]
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spiec_number[BHQ_chinese.index(label)] += 1
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else:
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label = None
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label_name = 0
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palette = (2 ** 11 - 1, 2 ** 15 - 1, 2 ** 20 - 1)
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colors = [int((p * (int(label_name) ** 2 - int(label_name) + 1)) % 255) for p in palette]
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img = plot_one_box(xyxy, img, label=label, color=colors, line_thickness=2)
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num_detect += 1
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flag=0
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if num_image % 10 == 0:
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num_count_old = num_detect
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spiec_number_old = spiec_number
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# if width_or == 2560:
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# img = cv2AddChineseText(img, "识别总数: {}只".format(str(num_count_old)), (50, 1200), textColor=(255, 255, 255),
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# textSize=40)
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# img = cv2AddChineseText(img, "分类识别:", (50, 1250), textColor=(255, 255, 255),
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# textSize=40)
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# for i in range(len(spiec_number)):
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# img = cv2AddChineseText(img, "{}数量:{}只".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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# (250 + i * 300, 1250), textColor=(255, 255, 255),
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# textSize=40)
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# if width_or == 1920:
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# radio_w = 1920/2560.0
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# radio_h = 1080/1440.0
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# img = cv2AddChineseText(img, "识别总数: {}只".format(str(num_count_old)), (int(50*radio_w), int(1200*radio_h)), textColor=(255, 255, 255),
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# textSize=40)
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# img = cv2AddChineseText(img, "分类识别:", (int(50*radio_w), int(1250*radio_h)), textColor=(255, 255, 255),
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# textSize=40)
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# for i in range(len(spiec_number)):
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# img = cv2AddChineseText(img, "{}数量:{}只".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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# (int(250) + i * int(300), int(1250*radio_h)), textColor=(255, 255, 255),
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# textSize=40)
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#yingwen dibu
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# if width_or == 2560:
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# img = cv2AddChineseText(img, "The total number of: {}".format(str(num_count_old)), (50, 1200), textColor=(255, 255, 255),
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# textSize=40)
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# img = cv2AddChineseText(img, "Number of different spieces:", (50, 1250), textColor=(255, 255, 255),
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# textSize=40)
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# for i in range(len(spiec_number)):
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# img = cv2AddChineseText(img, "{} number:{}".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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# (250 + i * 300, 1250), textColor=(255, 255, 255),
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# textSize=40)
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# if width_or == 1920:
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# radio_w = 1920/2560.0
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# radio_h = 1080/1440.0
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# img = cv2AddChineseText(img, "The total number of: {}".format(str(num_count_old)), (int(50*radio_w), int(1200*radio_h)), textColor=(255, 255, 255),
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# textSize=40)
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#
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# for i in range(len(spiec_number)):
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# img = cv2AddChineseText(img, "{}:{}".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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# (int(50*radio_w) + i * int(400), int(1250*radio_h)), textColor=(255, 255, 255),
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# textSize=40)
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if width_or == 2560:
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img = cv2AddChineseText(img, "The total number of: {}".format(str(num_count_old)), (50, 1200), textColor=(255, 255, 255),
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textSize=40)
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temp_pix = 0
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for i in range(len(spiec_number)):
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img = cv2AddChineseText(img, "{}:{}".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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(50 + temp_pix, 1250), textColor=(255, 255, 255),
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textSize=40)
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temp_pix += len(str(BHQ_chinese[i])) * 27
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if i == 0:
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temp_pix+=20
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if i==1:
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temp_pix-=25
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if width_or == 1920:
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radio_w = 1920/2560.0
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radio_h = 1080/1440.0
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img = cv2AddChineseText(img, "The total number of: {}".format(str(num_count_old)), (int(50*radio_w), int(1200*radio_h)), textColor=(255, 255, 255),
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textSize=40)
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for i in range(len(spiec_number)):
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img = cv2AddChineseText(img, "{}:{}".format(str(BHQ_chinese[i]), str(spiec_number_old[i])),
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(int(50*radio_w) + i * int(400), int(1250*radio_h)), textColor=(255, 255, 255),
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textSize=40)
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flag=cv2.imwrite(save_path+"{}.jpg".format(filename),img)
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if not (flag):
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print(filename,"error")
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num_image+=1
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print("all done ====================================")
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CombineVideoRawImgPath = "../data_MPKFNet/result/" + "hiv00024" + "Detection-English"
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CombineVideoResultPath = '../data_MPKFNet/result_vedio/' + "hiv00024" + "DetectionEnglish.avi"
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_check_voc(image_path,annotation_path,save_path)
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images_to_video(CombineVideoRawImgPath, CombineVideoResultPath)
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#(int((xmin_data+xmax_data/2)),int((ymin_data+ymax_data)/2))
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