diff --git a/classifer.py b/classifer.py
index f1a286d..b0f2b6b 100755
--- a/classifer.py
+++ b/classifer.py
@@ -31,6 +31,7 @@ import utils
 
 FEATURE_INDEX = [0, 1, 2]
 delete_columns = 10        # 已弃用
+num_bins = 10
 
 class WoodClass(object):
     def __init__(self, load_from=None, w=2048, h=12450, n=5000, p1=0.3, pur=0.99999, left_correct=False, single_pick_mode=False,
@@ -276,7 +277,7 @@ class WoodClass(object):
         x = cv2.cvtColor(x, cv2.COLOR_BGR2LAB)
         x = np.concatenate((x, x_hsv), axis=2)
         x = np.reshape(x, (x.shape[0]*x.shape[1], x.shape[2]))
-        hist, bins = np.histogram(x[:, 0], bins=10)
+        hist, bins = np.histogram(x[:, 0], bins=num_bins)
         hist = hist[1:]
         bins = bins[1:]
         # x = x[np.argsort(x[:, 0])]
diff --git a/hist.py b/hist.py
index 388234e..b0a7b75 100644
--- a/hist.py
+++ b/hist.py
@@ -2,7 +2,7 @@ import cv2
 import numpy as np
 
 
-img_path = 'data/data1015/middle/rgb0.png'
+img_path = 'data/data1103/dark/rgb20.png'
 img = cv2.imread(img_path)
 img = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
 x = img.reshape(img.shape[0]*img.shape[1], img.shape[2])
@@ -16,5 +16,5 @@ y = np.zeros((img.shape[0]*img.shape[1], img.shape[2]), dtype=np.uint8)
 y[:, ] = mean_value
 #lab转rgb再保存
 y = cv2.cvtColor(y.reshape(img.shape[0], img.shape[1], img.shape[2]), cv2.COLOR_LAB2BGR)
-cv2.imwrite('3.png', y.reshape(img.shape[0], img.shape[1], img.shape[2]))
+cv2.imwrite('5.png', y.reshape(img.shape[0], img.shape[1], img.shape[2]))