75 lines
3.2 KiB
Python
Executable File
75 lines
3.2 KiB
Python
Executable File
"""
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author:Hatcher
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e-mail:hcwang@semi.ac.cn
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功能：扫描文件夹下面的所有图像，并以文件夹为单位统计鸟类数量
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文件夹格式：
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images
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data
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images.jpg
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输出：每个文件夹中保存一个txt文件，每个种类鸟类的数量，所有鸟类种类的数量
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"""
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import os
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import torch
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import cv2
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from System_I import Detection_Y5,Fine_grained_T
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from common import global_para as gp
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import json
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from tqdm import tqdm
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from creat_xml_fordetection import make_xml_scan
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root_path = "/data5/Project/scanData/YNDC/scanData/"
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save_root = "/data5/Project/scanData/YNDC/result/"
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save_json = "/data5/Project/scanData/YNDC/JSON/"
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os.environ['CUDA_VISIBLE_DEVICES'] = '7'
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devices = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
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Detection = Detection_Y5(devices,root_path)
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Fine = Fine_grained_T(devices)
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if not os.path.exists(os.path.join(save_json, "ForDataBase")):
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os.makedirs(os.path.join(save_json, "ForDataBase"))
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if not os.path.exists(os.path.join(save_json, "ForTest")):
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os.makedirs(os.path.join(save_json, "ForTest"))
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for file_paths in tqdm(os.listdir(root_path)):
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box_all = []
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label_all = []
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record_time = file_paths.replace("_","-",2)
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record_time = record_time.replace("_"," ",1)
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record_time = record_time.replace("_",":")
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file_path = os.path.join(root_path,file_paths)
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labels_fineall = []
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resultDict = {}
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allimageresult =[0 for i in range(len(gp.BHG_chineseName))]
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if not os.path.exists(os.path.join(save_root,file_paths)):
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os.makedirs(os.path.join(save_root,file_paths))
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for imagepath in os.listdir(file_path):
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image = cv2.imread(os.path.join(file_path,imagepath))
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img_show,boxes_fine, labels_fine = Detection.inference_scan(image=image,fine_grained=Fine)
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for m in range(len(labels_fine)):
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box_all.append(boxes_fine[m])
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label_all.append(gp.BHG_chineseName[int(labels_fine[m])])
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cv2.imwrite(os.path.join(save_root,file_paths,imagepath),img_show)
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oneimageresultcdict = {}
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oneimageresult =[0 for i in range(len(gp.BHG_chineseName))]
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for i in labels_fine:
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oneimageresult[int(i)]+=1
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allimageresult[int(i)]+=1
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for i in range(len(oneimageresult)):
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if not (int(oneimageresult[i]) == 0):
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oneimageresultcdict[gp.BHG_chineseName[i]]=int(oneimageresult[i])
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resultDict[imagepath] = oneimageresultcdict
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allimageresultcdict = {}
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for i in range(len(allimageresult)):
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if not (int(allimageresult[i]) == 0):
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allimageresultcdict[gp.BHG_chineseName[i]]=int(allimageresult[i])
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resultDict[file_paths] = allimageresultcdict
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json_str = json.dumps(resultDict, indent=4)
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with open(os.path.join(save_json,"ForTest",file_paths + "_Test.json"), 'w',encoding='utf-8') as json_file:
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#json_file.write(json_str)
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json.dump(resultDict,json_file,indent=4,ensure_ascii=False)
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json_conversion = make_xml_scan(record_time=record_time, serial_number="iDS-2DF8C840IXS-AFW/SP20220507CCCHJ90488961",boxes=box_all,labels=label_all, savename=os.path.join(save_json,"ForDataBase" ,file_paths + "_DataBase.json"))
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