[英]What kind of neural network should I use to to find the equation of this data set?
[英]What kind of parameters should I use to find and crop objects in an image?
我是深度學習的新手,並嘗試實現用於圖像聚類的 ML 算法。 問題是我無法使用 OpenCV 在 Python 中裁剪圖像中的對象。 這是我已經實現的代碼,如果 object 的顏色與背景非常不同(在 RGB 值中),它適用於某些對象,但它不適用於 ML 算法所需的圖像。 我應該擁有/更改什么樣的參數? 有什么建議么?
import cv2
import numpy as np
from PIL import Image
import tkinter as tk
from tkinter import filedialog as fd
from tkinter import*
import random
#!/usr/bin/python
from PIL import Image
import sys
myFile = 'Path' + '/crop.png'
nr_of_im = 1
q = 0
r = 0
x_list = []
y_list = []
img = cv2.imread(myFile, cv2.IMREAD_UNCHANGED)
ret, thresh = cv2.threshold(cv2.cvtColor(img.copy(), cv2.COLOR_BGR2GRAY) , 30, 255, cv2.THRESH_BINARY)
contours, hier = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
print("len",len(contours))
if cv2.contourArea(contour) > 80:
x, y, w, h = cv2.boundingRect(contour)
q = w
r = h
x_list.append(x)
y_list.append(y)
font = cv2.FONT_HERSHEY_SIMPLEX
ROI = img[y-10:y+10+h, x-10:x+10+w]
ROI = cv2.resize(ROI,(300,300))
file_all = "/images/%d.jpg"%nr_of_im
nr_of_im += 1
cv2.imwrite(file_all,ROI)
圖像中有 21 個對象,但輪廓的長度返回 1。圖像看起來像這樣
作物.png:
您的閾值太低,為我生成了一個完全白色的圖像。 你需要提高你的門檻。 始終查看您的閾值,以確保它按您期望的方式工作。 您以后可以隨時刪除查看。
以下適用於我使用閾值為 97 的 Otsu 閾值。我得到 21 個輪廓。
輸入:
import cv2
import numpy as np
# read image
img = cv2.imread('blocks.jpg')
# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# threshold
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
print(ret)
# apply morphology fill and separate large regions and remove small ones
kernel = cv2.getStructuringElement(cv2.MORPH_RECT , (9,9))
morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT , (15,15))
morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)
# get contours
result = img.copy()
contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
# get count of contours
print(len(contours))
# draw bounding boxes on contours
for cntr in contours:
x,y,w,h = cv2.boundingRect(cntr)
cv2.rectangle(result, (x, y), (x+w, y+h), (0, 0, 255), 2)
#print("x,y,w,h:",x,y,w,h)
# save results
cv2.imwrite("blocks_thresh.jpg", thresh)
cv2.imwrite("blocks_morphology.jpg", morph)
cv2.imwrite("blocks_bboxes.jpg", result)
# show thresh and result
cv2.imshow("thresh", thresh)
cv2.imshow("morph", morph)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
閾值圖像:
形態清潔圖像:
從輪廓生成的邊界框:
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