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