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LPR-Accuracy-Testing
Commit 8bdd3716 authored by Bruce's avatar Bruce
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Update Accuracy_Testing.ipynb

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Accuracy_Testing.ipynb
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......@@ -142,6 +142,7 @@
"from hyperlpr import calculation_raito_origin as fm\n",
"from hyperlpr import finemapping_vertical as fv\n",
"from hyperlpr import segmentation_0124 as segmentation\n",
"import plate_judgment\n"
"\n",
"\n",
"import numpy as np\n",
......@@ -165,62 +166,61 @@
"\n",
"###車牌辨識方法\n",
"def MYSimpleRecognizePlate(img):\n",
" car=img\n",
" w,h=car.shape[:2]\n",
" h=int(w*500/h)\n",
" w=500\n",
" car=cv2.resize(car,(w,h))\n",
" images=detect.detectPlateRough(car,car.shape[0])\n",
" y1,y2,x1,x2=0,1080,0,1000 ##限定區域\n"
" car=img[y1:y2,x1:x2]\n",
" images=detect.detectPlateRough(car,500)\n",
"\n",
" origin_plate_list=[]\n",
" image_rgb_rl_list=[]\n",
" for j,plate in enumerate(images):\n",
" plate, rect, origin_plate,flg =plate\n",
" img =cv2.resize(origin_plate,(300,100))\n",
" img = cv2.bitwise_not(img)\n",
" ### 車排上下定位\n",
" image_rgb = fm.findContoursAndDrawBoundingBox(img)\n",
" image_rgb = cv2.bitwise_not(image_rgb)\n",
" plt.figure(\"Imgae\"+str(j))\n",
" plt.imshow(image_rgb)\n",
" plt.show\n",
" ### 車排左右定位\n",
" image_rgb = cv2.bitwise_not(image_rgb)\n",
" image_rgb_rl = fv.finemappingVertical(image_rgb)\n",
" image_rgb_rl = cv2.bitwise_not(image_rgb_rl)\n",
" judgment_type=plate_judgment.SimplePredict(origin_plate)"
" if(judgment_type==0):"
" img =cv2.resize(origin_plate,(300,100))\n",
" img = cv2.bitwise_not(img)\n",
" ### 車排上下定位\n",
" image_rgb = fm.findContoursAndDrawBoundingBox(img)\n",
" image_rgb = cv2.bitwise_not(image_rgb)\n",
" plt.figure(\"Imgae\"+str(j))\n",
" plt.imshow(image_rgb)\n",
" plt.show\n",
" ### 車排左右定位\n",
" image_rgb = cv2.bitwise_not(image_rgb)\n",
" image_rgb_rl = fv.finemappingVertical(image_rgb)\n",
" image_rgb_rl = cv2.bitwise_not(image_rgb_rl)\n",
"\n",
" plt.figure(\"Imgae2\"+str(j))\n",
" plt.imshow(image_rgb_rl)\n",
" plt.show\n",
" plt.figure(\"Imgae2\"+str(j))\n",
" plt.imshow(image_rgb_rl)\n",
" plt.show\n",
"\n",
" ### 車牌辨識\n",
" image_gray = cv2.cvtColor(image_rgb_rl,cv2.COLOR_RGB2GRAY)\n",
" val = segmentation.slidingWindowsEval(image_gray)\n",
" refined,name,con,nums,cut_data=val\n",
" \n",
" ### 分割機率圖\n",
" p=cut_data[0]\n",
" lmin=cut_data[1]\n",
" x=np.zeros(114)\n",
" \n",
" for i in lmin:\n",
" x[i]=p[i]\n",
" \n",
" \n",
" plt.figure()\n",
" plt.plot(x,'*',p) \n",
" \n",
" ### 車牌辨識\n",
" image_gray = cv2.cvtColor(image_rgb_rl,cv2.COLOR_RGB2GRAY)\n",
" val = segmentation.slidingWindowsEval(image_gray)\n",
" refined,name,con,nums,cut_data=val\n",
" \n",
" ### 分割機率圖\n",
" p=cut_data[0]\n",
" lmin=cut_data[1]\n",
" x=np.zeros(114)\n",
" \n",
" for i in lmin:\n",
" x[i]=p[i]\n",
" \n",
" \n",
" plt.figure()\n",
" plt.plot(x,'*',p) \n",
" \n",
"\n",
" ### 切割出的字元\n",
" for i,one in enumerate (refined):\n",
" plt.figure(\"Imgae3\"+str(i))\n",
" plt.imshow(one)\n",
" plt.show\n",
" ### 切割出的字元\n",
" for i,one in enumerate (refined):\n",
" plt.figure(\"Imgae3\"+str(i))\n",
" plt.imshow(one)\n",
" plt.show\n",
"\n",
" ### 辨識結果\n",
" print('車牌',name,'可信度',con,'字數',nums)\n",
" \n",
" return cut_data\n",
" ### 辨識結果\n",
" print('車牌',name,'可信度',con,'字數',nums)\n",
" \n",
" return name,con,nums\n",
" \n",
" \n",
"LPR=MYSimpleRecognizePlate(img)\n",
......
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