NanjingForestryUniversity/supermachine-wood
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bins可调

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FEIJINTI 2023-03-15 09:19:05 +08:00
parent 962f88c65f
commit cafcd835cb
2 changed files with 4 additions and 3 deletions
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3
classifer.py
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@ -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])]

4
hist.py
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@ -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]))