first commit

scan_dealimages.py

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+"""
+author:Hatcher
+e-mail:hcwang@semi.ac.cn
+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
+文件夹格式：
+    images
+        data
+            images.jpg
+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
+
+"""
+import os
+import torch
+import cv2
+from System_I import Detection_Y5,Fine_grained_T
+from common import global_para as gp
+import json
+from tqdm import tqdm
+from creat_xml_fordetection import make_xml_scan
+root_path = "/data5/Project/scanData/YNDC/scanData/"
+save_root = "/data5/Project/scanData/YNDC/result/"
+save_json = "/data5/Project/scanData/YNDC/JSON/"
+os.environ['CUDA_VISIBLE_DEVICES'] = '7'
+devices = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+Detection = Detection_Y5(devices,root_path)
+Fine = Fine_grained_T(devices)
+if not os.path.exists(os.path.join(save_json, "ForDataBase")):
+    os.makedirs(os.path.join(save_json, "ForDataBase"))
+if not os.path.exists(os.path.join(save_json, "ForTest")):
+    os.makedirs(os.path.join(save_json, "ForTest"))
+for file_paths in tqdm(os.listdir(root_path)):
+    box_all = []
+    label_all = []
+    record_time = file_paths.replace("_","-",2)
+    record_time = record_time.replace("_"," ",1)
+    record_time = record_time.replace("_",":")
+    file_path = os.path.join(root_path,file_paths)
+    labels_fineall = []
+    resultDict = {}
+    allimageresult =[0 for i in range(len(gp.BHG_chineseName))]
+    if not os.path.exists(os.path.join(save_root,file_paths)):
+        os.makedirs(os.path.join(save_root,file_paths))
+    for imagepath in os.listdir(file_path):
+        image = cv2.imread(os.path.join(file_path,imagepath))
+        img_show,boxes_fine, labels_fine = Detection.inference_scan(image=image,fine_grained=Fine)
+        for m in range(len(labels_fine)):
+            box_all.append(boxes_fine[m])
+            label_all.append(gp.BHG_chineseName[int(labels_fine[m])])
+        cv2.imwrite(os.path.join(save_root,file_paths,imagepath),img_show)
+        oneimageresultcdict = {}
+        oneimageresult =[0 for i in range(len(gp.BHG_chineseName))]
+        for i in labels_fine:
+            oneimageresult[int(i)]+=1
+            allimageresult[int(i)]+=1
+        for i in range(len(oneimageresult)):
+            if not (int(oneimageresult[i]) == 0):
+                oneimageresultcdict[gp.BHG_chineseName[i]]=int(oneimageresult[i])
+        resultDict[imagepath] = oneimageresultcdict
+    allimageresultcdict = {}
+    for i in range(len(allimageresult)):
+            if not (int(allimageresult[i]) == 0):
+                allimageresultcdict[gp.BHG_chineseName[i]]=int(allimageresult[i])
+    resultDict[file_paths] = allimageresultcdict
+    json_str = json.dumps(resultDict, indent=4)
+    with open(os.path.join(save_json,"ForTest",file_paths + "_Test.json"), 'w',encoding='utf-8') as json_file:
+        #json_file.write(json_str)
+        json.dump(resultDict,json_file,indent=4,ensure_ascii=False)
+    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"))
+
+    
+
+        
+
+