first push

server.py

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+import sys
+import argparse
+#from utils.retrieval_index import EvaluteMap
+from utils.tools import EvaluteMap
+from utils.retrieval_feature import AntiFraudFeatureDataset
+from utils.monitor import Moniting
+from utils.updateObs import *
+from utils.config import cfg
+from utils.tools import createNet
+from flask import request,Flask, jsonify
+from utils.forsegmentation import analysis
+from gevent.pywsgi import WSGIServer
+import os, base64, stat, shutil
+sys.path.append('RAFT')
+sys.path.append('RAFT/core')
+sys.path.append('RAFT/core/utils')
+from RAFT.analysis_video import *
+
+os.environ["CUDA_VISIBLE_DEVICES"] = '0,1'
+app = Flask(__name__)
+parser = argparse.ArgumentParser()
+parser.add_argument('--model', default='RAFT/models/raft-things.pth',help="restore checkpoint")
+parser.add_argument('--small', action='store_true', help='use small model')
+parser.add_argument('--mixed_precision', action='store_true', help='use mixed precision')
+parser.add_argument('--alternate_corr', action='store_true', help='use efficent correlation implementation')
+opt, unknown = parser.parse_known_args()
+'''
+status 状态码
+00: 视频未解析成功(视频截取错误)
+01: 未纳入监查列表
+02: 未检测出商品
+03: 异常输出
+04: 正确识别
+'''
+status = ['00', '01', '02', '03', '04']
+net, transform, ms = createNet()
+raft_model = raft_init_model(opt)
+@app.route('/search', methods=['POST'])
+def search():
+    pre_status = False
+    try:
+      video_name = request.form.get('video_name')
+      video_data = request.files['video']
+      video_path = os.sep.join([cfg.VIDEOPATH, video_name])
+      video_data.save(video_path)
+      uuid_barcode = video_name.split('.')[0] 
+      barcode_name = uuid_barcode.split('_')[-1]
+      photo_nu = analysis_video(raft_model, video_path, cfg.TEST_IMG_DIR, uuid_barcode)
+      Addimg(uuid_barcode)
+      if not Moniting(barcode_name).search() == 'nomatch':
+          if photo_nu == 0:
+              deleteimg(uuid_barcode)
+              AddObs(video_path, status[0])
+              return uuid_barcode+'_0.90_!_'+status[0]+'_'+video_name
+          #Addimg(uuid_barcode)
+          feature_dict = AntiFraudFeatureDataset(uuid_barcode).extractFeature(net, transform, ms)
+          res = EvaluteMap().match_images(feature_dict, barcode_name)
+          if res == 'nan':
+              res = '0.90'
+              pre_status = status[1]
+          if res<cfg.THRESHOLD: pre_status = status[2]
+          else: pre_status = status[4]
+      else:
+          pre_status = status[1]
+          res = '0.90'
+    except:
+          AddObs(video_path, status[3])
+          deleteimg(uuid_barcode)
+          return uuid_barcode+'_0.90_!_'+status[3]+'_'+video_name
+    data = uuid_barcode+'_'+str(res)+'_!'
+    if pre_status == '04':
+        deleteimg(uuid_barcode)
+    AddObs(video_path, pre_status)
+    print('result:',data)
+    return data+'_'+pre_status+'_'+video_name
+
+def deleteimg(uuid_barcode):
+    for img_name in os.listdir(cfg.TEST_IMG_DIR):
+        if uuid_barcode in img_name:
+            os.remove(os.sep.join([cfg.TEST_IMG_DIR, img_name]))
+
+if __name__ == '__main__':
+#        http_server = WSGIServer(('192.168.1.142', 6001), app)
+#        http_server.serve_forever()
+        app.run()