diff --git a/RAFT/analysis_video.py b/RAFT/analysis_video.py
index 6ad3454..54673ca 100755
--- a/RAFT/analysis_video.py
+++ b/RAFT/analysis_video.py
@@ -43,7 +43,7 @@ def analysis_video(model, video_path, result_path, uuid_barcode, maskpath=None,
     search_r = ManagingFeature().getfeature(barcode)
     #print('search_r>>>>>>>>', len(search_r))
     ori_mask = cv2.imread(maskpath, 0)
-    nn, nu = 0, 1
+    nn, nu, result = 0, 1, None
     Result = '03'
     img_dic = {}
     ex_ocrList, resultList = [],[]
@@ -87,16 +87,17 @@ def analysis_video(model, video_path, result_path, uuid_barcode, maskpath=None,
 
             flow_low, flow_up = model(image1, image2, iters=2, test_mode=True)
             flo = viz(image1, flow_up)
-            result = get_target(result_path, flo, imfile1, nu, ori_mask, uuid_barcode, MASKIMG)
+            result,coordination = get_target(result_path, flo, imfile1, nu, ori_mask, uuid_barcode, MASKIMG)
             imfile1 = imfile2
             flag, nu, Result = detect(match, affd, net, result, transform, ms, search_r, nn, nu, Result)
             if flag: break
         Addimg_content(uuid_barcode, frame_show)#图片上传
         #if not Result=='03':
         if result is not None:
-            cv2.imwrite(os.sep.join([cfg.Ocrimg, uuid_barcode+'_'+str(nu)+'.jpg']), result) #give ocr img
+            coordinate = str(coordination[0])+'_'+str(coordination[1])+'_'+str(coordination[2])+'_'+str(coordination[3])
+            cv2.imwrite(os.sep.join([cfg.Ocrimg, uuid_barcode+'_'+str(nu)+'_'+coordinate+'.jpg']), frame_show) #give ocr img
         else:
-            cv2.imwrite(os.sep.join([cfg.Ocrimg, uuid_barcode+'_'+str(nu)+'.jpg']), frame_show) #give ocr img
+            cv2.imwrite(os.sep.join([cfg.Ocrimg, uuid_barcode+'_'+str(nu)+'_0_0_0_0'+'.jpg']), frame_show) #give ocr img
         return Result
 
 def detect(match, affd, net, result, transform, ms, search_r, nn, nu, Result):
@@ -141,28 +142,28 @@ def get_target(path, img, ori_img, nu, ori_mask, uuid_barcode, MASKIMG):
     else:
         contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
     if len(contours)>100:
-        return None
+        return None, '_'
     for contour in contours:
         mask_area_now = cv2.contourArea(contour)
         if mask_area_now > mask_max_area:
             mask_max_area = mask_area_now
             mask_max_contour = contour
-    if mask_max_area == 0 :return None  #mask_max_area 目标位的面积
+    if mask_max_area == 0 :return None, '_'  #mask_max_area 目标位的面积
     (x, y, w, h) = cv2.boundingRect(mask_max_contour)
     if (w*h)/(img.shape[0]*img.shape[1])>0.80:
-        return None
+        return None, '_'
     if min(w,h) <100 or max(w,h)>1000:
-        return None
+        return None, '_'
     coordination = [x, y, x + w, y + h]
     mask_image = cv2.fillPoly(mask_image, [mask_max_contour], (255))
     if pre_area==0:
         pre_area = mask_max_area
-        return None
+        return None, '_'
     else:
         if abs(mask_max_area-pre_area)/pre_area > 0.4:
             pre_area = mask_max_area
             #print('abs:',abs(mask_max_area-pre_area)/pre_area)
-            return None
+            return None, '_'
         else:
             pre_area = mask_max_area
     A,B,C = mask_image, mask_image, mask_image
@@ -170,13 +171,13 @@ def get_target(path, img, ori_img, nu, ori_mask, uuid_barcode, MASKIMG):
     
     #该方法去除框外干扰
     if not get_iou_ratio(mask_image, MASKIMG):
-        return None
+        return None, '_'
     
     show = cv2.bitwise_and(ori_img, mask_image)
     #show = show[coordination[1]:coordination[3], coordination[0]:coordination[2]]
     show = ori_img[coordination[1]:coordination[3], coordination[0]:coordination[2]]
     #cv2.imwrite(os.sep.join([cfg.Ocrimg, str(nu-1)+'_'+uuid_barcode+'.jpg']), show)
-    return show
+    return show, coordination
 
 def get_iou_ratio(oimg, MASKIMG):
     mimg = cv2.imread(MASKIMG)