Q&A
pythonで文字領域を求めるプログラムを作りたいのですが文字の重心を求め、その重心の距離が近いとその2点を結合して・・・と進め最終的には文字領域を検出するプログラムを作りたいと思っています。ある距離より近くなったらその2点を結合してとやりたいのですが詳しく教えて頂けませんでしょうか。また、ランダムフォレストを用いるのですがランダムフォレストも教えて頂けると嬉しいです。
# 二値化 def area(): files = os.listdir('C:\Users\LSL\file\opicture') print(files) length=len(files)-1 allw=[] for i in range(length): filename=files[i] logfilename="opicture/"+filename #logfilename="input.png" img2=cv2.imread(logfilename) img3=cv2.cvtColor(img2,cv2.COLOR_BGR2HSV) # 面積（white） hsv_min = np.array([0, 0, 255]) hsv_max = np.array([0, 0, 255]) mask = cv2.inRange(img3, hsv_min, hsv_max) white= cv2.countNonZero(mask) total=mask.shape[0]*mask.shape[1] black=total-white # 白の面積が黒の面積より広い場合は再度白黒を反転する if white>black: mask2=cv2.bitwise_not(img2) name2= mask2.copy() t = 127 name2[mask2 < t] = 0 name2[mask2 >= t] = 255 os.remove(logfilename) cv2.imwrite(logfilename, name2) pre=black black=white white=pre a=[total,white] allw.append(a) else: a=[filename,total,white] allw.append(a) return allw # 周囲長(permister) def perimister (): files = os.listdir('C:\Users\LSL\file\opicture') length=len(files)-1 allw=[] for i in range(length): filename=files[i] logfilename="opicture/"+filename #logfilename="input.png" print(logfilename) img2=cv2.imread(logfilename) img3=cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(img3,127,255,0) #cv2.imshow("th",thresh) imgEdge,contours,hierarchy = cv2.findContours(thresh, 1, 2) imgEdge,contours,hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) imagecounter1 = np.copy(img2) min_coin_area =0.1 large_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > min_coin_area] img4=cv2.drawContours( imagecounter1, large_contours, -1, (0,0,255),1) outputfn="opicture2/"+"out2putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img4) warea=0 permister=0 for contour in large_contours: area = cv2.contourArea(contour) per=cv2.arcLength(contour,True) warea+=area permister+=per imagecounter2 = np.copy(img2) imagecounter8 = np.copy(img2) acx=0 acy=0 a=[] print(large_contours) # 重心 for contour in large_contours: M = cv2.moments(contour) cx = int(M['m10']/M['m00']) cy = int(M['m01']/M['m00']) img12=cv2.circle(imagecounter2, (cx,cy), 3,(0,0,255), -1) ab=[cx,cy] a.append(ab) acx+=cx acy+=cy acx=int(acx/len(large_contours)) acy=int(acy/len(large_contours)) img10=cv2.circle(imagecounter8, (acx,acy),1,(0,255,0), 2) outputfn="opicture2/"+"Mout10putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img10) outputfn="opicture2/"+"Mout5putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img12) print(a) imagecounter2 = np.copy(img2) j=0 print(len(a)) zyusin=[] ar=[0] while 1: try1=a[j] x=try1[0] y=try1[1] w=1 arc=[] #ar.remove(j) while 1: if any(w==arr for arr in ar ): True try: try2=a[w+j] x2=try2[0] y2=try2[1] cx=abs(x-x2) cy=abs(y-y2) root=math.sqrt((cx*cx)+(cy*cy)) print("-------------") print(j) print(w+j) print(root) print("-------------") if root<=20: print("a") ar.append(w) arc.append([x2,y2]) print(arc) w+=1; if root>20: w+=1 except IndexError: print(arc) start=try1 while 1: try: a1=random.choice(arc) arc.remove(a1) except IndexError: zyu=[try1[0],try1[1]] zyusin.append(zyu) break; try: a2=random.choice(arc) arc.remove(a2) acx=(a1[0]+a2[0]+start[0])/3 acy=(a1[1]+a2[1]+start[1])/3 start=[acx,acy] except IndexError: x=(a1[0]+try1[0])/2 y=(a1[1]+try1[1])/2 zyu=[x,y] print(zyu) zyusin.append(zyu) break; if len(arc)==0: zyu=[acx,acy] zyusin.append(zyu) print(zyu) break; j+=1 break ; if j>=len(a): break; print(zyusin) for r in range(len(zyusin)): x=int(zyusin[r][0]) y=int(zyusin[r][1]) img11=cv2.circle(imagecounter2, (x,y), 4,(200,200,200), 2, 4) outputfn="opicture2/"+"Mout32putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img11) #sys.exit() # 回転を考慮しない外接矩形(辺長、面積) imagecounter2 = np.copy(img2) aarea=0 per1=0 print("---------------") for contour in large_contours: x, y, w, h = cv2.boundingRect(contour) aarea=aarea+(w*h) per1=per1+(2*w+2*h) img5=cv2.rectangle(imagecounter2 , (x, y), (x + w, y + h), (0, 255, 0), 1) percent=warea/aarea outputfn="opicture3/"+"out2putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img5) # 回転を考慮した外接矩形 imagecounter3 = np.copy(img2) for contour in large_contours: rect = cv2.minAreaRect(contour) box = cv2.boxPoints(rect) box = np.int0(box) img6 = cv2.drawContours(imagecounter3,[box],0,(255,0,0),3) outputfn="opicture4/"+"out3putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img6) # 外接円の円周の長さと面積（permister2、menseki3) imagecounter4 = np.copy(img2) permister2=0 menseki3=0 for contour in large_contours: (x,y),radius = cv2.minEnclosingCircle(contour) center = (int(x),int(y)) radius = int(radius) permister2=permister2+(2*radius*math.pi) menseki3=menseki3+(radius*radius*math.pi) img7= cv2.circle( imagecounter4,center,radius,(0,255,0),2) outputfn="opicture5/"+"out3putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img7) # 最小凸包の端点数(toppou) imagecounter1 = np.copy(img2) toppou=0 for contour in large_contours: epsilon = 0.01*cv2.arcLength(contour,True) approx= cv2.approxPolyDP(contour,epsilon,True) toppou=toppou+len(approx) img8=cv2.drawContours(imagecounter1 , [approx], -1, (0, 255, 0), 2) outputfn="opicture6/"+"out3putpic"+str(i)+".jpg" cv2.imwrite(outputfn,img8) # [文字の面積、周囲長、外接矩形の辺長、面積、外接矩形の面積に対する文字の面積の割合、 # 最小凸包の端点数、外接円の円周の長さ、面積] allw.append([warea,permister,per1,aarea,percent,toppou,permister2,menseki3]) return allw if __name__ == "__main__": loadfile() allw=area() allw2=perimister () print(allw2)
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