Panoramic
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@@ -2,15 +2,12 @@ import xml.dom.minidom
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from tqdm import tqdm
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from glob import glob
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import cv2
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import os
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from PIL import Image
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import os,argparse
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import numpy as np
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from jpg import jpg
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txt_root_path = "/data/DataManagement/Project/005_kunmingdianchi/0002_20220412_800_200/Dataset/VOC0050201"
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#xml_files = glob('./temp2/*.xml')
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image_T = 50
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num_count = 0
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root_path = "/data/DataManagement/Project/005_kunmingdianchi/0002_20220412_800_200/Dataset/VOC0050201/Annotations/"
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class_name = ["Anser albifrons" ,"Fulica atra" ,"Leucogeranus leucogeranus" ,"Egretta garzetta","Platalea leucorodia" ,"Mergellus albellus" ,"Grus monacha" ,"Tringa ochropus" ,"Numenius arquata" ,"Anser indicus","Anas zonorhyncha","Ardea cinerea","Mareca strepera" ,"Mareca penelope" ,"Tadorna ferruginea","Ardea alba","Numenius madagascariensis" ,"Botaurus stellaris" ,"Ciconia boyciana" ,"Anser fabalis" ,"Recurvirostra avosetta" ,"Podiceps cristatus","Vanellus vanellus" ,"Aythya fuligula" ,"Tringa erythropus","Calidris alpina" ,"Ciconia nigra" ,"Gallinula chloropus","Porphyrio poliocephalus","Larus ridibundus" ,"Anser cygnoides" ,"Charadrius alexandrinusw" ,"Pluvialis squatarola" ,"Grus grus" ,"Anser anser" ,"Pluvialis fulva" ,"Charadrius dubius" ,"Anas crecca","Anas platyrhynchos","Spatula clypeata","Phalacrocorax carbo","Mergus merganser" ,"Tadorna tadorna" ,"Tringa nebulariaw","Bucephala clangula" ,"Gallinago gallinago" ,"Anser erythropus","Cygnus columbianus" ,"Ichthyaetus ichthyaetus","Anas acuta" ,"Ardea intermedia"]
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def cv2_crop(im, box):
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'''cv2实现类似PIL的裁剪
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@@ -32,111 +29,64 @@ def convert(size, box):
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h = h*dh
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return (x,y,w,h)
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# for xml_path in os.listdir(root_path):
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# xml_files = glob(os.path.join(root_path,xml_path,"*.xml"))
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# print(os.path.join(root_path.replace("xml","image"),xml_path))
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# jpg(os.path.join(root_path.replace("xml","image"),xml_path))
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# f = open("./Hatcher_ALL.txt", "a")
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# txt_lists = []
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# for xml_file in tqdm(xml_files):
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#
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# print(xml_file+" is doing")
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# DOMTree = xml.dom.minidom.parse(xml_file)
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# collection = DOMTree.documentElement
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# #img_name = collection.getElementsByTagName("filename")[0].childNodes[0].data
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# img_name = xml_file.replace("\\xml\\","\\image\\").replace(".xml",".jpg")
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# objects = collection.getElementsByTagName("object")
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# #img = cv2.imread(img_name)
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# img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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# #cv2.imwrite(img_name,img)
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# #img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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# # im = Image.open(img_name)
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# # im.save(img_name, quality=100)
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# # im = Image.open(img_name)
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# for object_id in objects:
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# xmin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmin')[0].childNodes[0].data
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# ymin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymin')[0].childNodes[0].data
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# xmax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmax')[0].childNodes[0].data
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# ymax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymax')[0].childNodes[0].data
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# name = object_id.getElementsByTagName('name')[0].childNodes[0].data
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# xmin = int(xmin)
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# xmax = int(xmax)
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# ymin = int(ymin)
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# ymax = int(ymax)
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# class_index = class_name.index(str(name).replace("\t","").strip())
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# img1 = cv2_crop(img,(xmin, ymin,xmax, ymax))
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# cv2.imwrite("H:\\Fine-grained-identification\\2021.3.25\Hatcher_One\\" + str(name).replace("\t","").strip().replace(" ","_" )+"_{}.jpg".format(num_count), img1)
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# txt_lists.append(str(name).replace("\t","").strip().replace(" ","_" )+"_{}.jpg".format(num_count)+" "+str(class_index)+'\n')
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# #f.write(str(name).replace("\t","").strip().replace(" ","_" )+"_{}.jpg".format(num_count)+" "+str(class_index)+'\n')
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# num_count += 1
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# for txt_list in txt_lists:
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# f.write(txt_list)
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# f.close()
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# f_num = open("./num.txt", "w")
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# f_num.write(str(num_count))
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# f_num.close()
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# print(num_count)
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# for xml_file in tqdm(xml_files):
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# os.remove(xml_file)
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#
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# #os.remove(xml_file)
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# print(num_count)
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def VocToFineWithLabel(num_count,root_path,image_T):
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xml_files = glob(os.path.join(root_path,"*.xml"))
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jpg(os.path.join(root_path.replace("Annotations","JPEGImages")))
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txt_lists = []
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for xml_file in tqdm(xml_files):
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xml_files = glob(os.path.join(root_path,"*.xml"))
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#print(os.path.join(root_path.replace("Annotations","JPEGImages")))
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jpg(os.path.join(root_path.replace("Annotations","JPEGImages")))
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f = open(txt_root_path+"/Hatcher_ALL.txt", "a")
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txt_lists = []
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for xml_file in tqdm(xml_files):
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#print(xml_file+" is doing")
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DOMTree = xml.dom.minidom.parse(xml_file)
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collection = DOMTree.documentElement
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#img_name = collection.getElementsByTagName("filename")[0].childNodes[0].data
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img_name = xml_file.replace("Annotations","JPEGImages").replace(".xml",".jpg")
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objects = collection.getElementsByTagName("object")
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#img = cv2.imread(img_name)
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img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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#cv2.imwrite(img_name,img)
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#img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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# im = Image.open(img_name)
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# im.save(img_name, quality=100)
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# im = Image.open(img_name)
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for object_id in objects:
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xmin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmin')[0].childNodes[0].data
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ymin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymin')[0].childNodes[0].data
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xmax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmax')[0].childNodes[0].data
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ymax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymax')[0].childNodes[0].data
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name = object_id.getElementsByTagName('name')[0].childNodes[0].data
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ratio_x = (3840.0/3840.0)
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ratio_y = (2160.0/2160.0)
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#print(ratio_x," ",ratio_y)
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#print(type(xmin))
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#exit()
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xmin = int(float(xmin)*ratio_x)
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xmax = int(float(xmax)*ratio_x)
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ymin = int(float(ymin)*ratio_y)
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ymax = int(float(ymax)*ratio_y)
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if ((xmax - xmin)<image_T) | ((ymax - ymin)<image_T):
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continue
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img1 = cv2_crop(img,(xmin, ymin,xmax, ymax))
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if not os.path.exists(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip())):
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os.makedirs(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip()))
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cv2.imwrite(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip(),"{}.jpg".format(str(num_count).zfill(5))), img1)
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#txt_lists.append(str(name).replace("\t","").strip()+"{}.jpg".format(str(num_count).zfill(5))+" "+str(class_index)+'\n')
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#f.write(str(name).replace("\t","").strip().replace(" ","_" )+"_{}.jpg".format(num_count)+" "+str(class_index)+'\n')
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num_count += 1
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print(num_count)
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# for xml_file in tqdm(xml_files):
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# os.remove(xml_file)
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#print(xml_file+" is doing")
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DOMTree = xml.dom.minidom.parse(xml_file)
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collection = DOMTree.documentElement
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#img_name = collection.getElementsByTagName("filename")[0].childNodes[0].data
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img_name = xml_file.replace("Annotations","JPEGImages").replace(".xml",".jpg")
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objects = collection.getElementsByTagName("object")
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#img = cv2.imread(img_name)
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img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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#cv2.imwrite(img_name,img)
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#img = cv2.imdecode(np.fromfile(img_name,dtype=np.uint8),-1)
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# im = Image.open(img_name)
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# im.save(img_name, quality=100)
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# im = Image.open(img_name)
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for object_id in objects:
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xmin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmin')[0].childNodes[0].data
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ymin = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymin')[0].childNodes[0].data
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xmax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('xmax')[0].childNodes[0].data
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ymax = object_id.getElementsByTagName('bndbox')[0].getElementsByTagName('ymax')[0].childNodes[0].data
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name = object_id.getElementsByTagName('name')[0].childNodes[0].data
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ratio_x = (3840.0/3840.0)
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ratio_y = (2160.0/2160.0)
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#print(ratio_x," ",ratio_y)
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#print(type(xmin))
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#exit()
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xmin = int(float(xmin)*ratio_x)
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xmax = int(float(xmax)*ratio_x)
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ymin = int(float(ymin)*ratio_y)
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ymax = int(float(ymax)*ratio_y)
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if ((xmax - xmin)<image_T) | ((ymax - ymin)<image_T):
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continue
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#class_index = class_name.index(str(name).replace("\t","").strip())
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img1 = cv2_crop(img,(xmin, ymin,xmax, ymax))
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if not os.path.exists(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip())):
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os.makedirs(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip()))
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cv2.imwrite(os.path.join(root_path.replace("Annotations","FineDataset_{}".format(str(image_T))),str(name).replace("\t","").strip(),"{}.jpg".format(str(num_count).zfill(5))), img1)
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#txt_lists.append(str(name).replace("\t","").strip()+"{}.jpg".format(str(num_count).zfill(5))+" "+str(class_index)+'\n')
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#f.write(str(name).replace("\t","").strip().replace(" ","_" )+"_{}.jpg".format(num_count)+" "+str(class_index)+'\n')
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num_count += 1
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for txt_list in txt_lists:
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f.write(txt_list)
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f.close()
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f_num = open("./num.txt", "w")
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f_num.write(str(num_count))
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f_num.close()
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print(num_count)
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# for xml_file in tqdm(xml_files):
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# os.remove(xml_file)
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#os.remove(xml_file)
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print(num_count)
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if __name__ == '__main__':
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print("Starting dealing......")
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parser1 = argparse.ArgumentParser(description="GYD")
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parser1.add_argument("image_T", default='0001', type=str,
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help='Video name.')
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parser1.add_argument("root_path", default='5', type=str,
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help='GPU.')
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args = parser1.parse_args()
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num_count = 0
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VocToFineWithLabel(num_count,args.root_path, int(args.image_T))
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#os.remove(xml_file)
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print(num_count)
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