#cv2.circle(img,(textx,texty),10,(0,0,0),-1) #cv2.circle(img, (j[1], j[0]), 5, (0,0,255), -1) cv2.putText(img, f'{ordered_bolt_no}', (textx,texty), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (255,0,255), 3) bolt_no += 1 # for i in bolts: # cv2.circle(img,(i[0],i[1]),10,(0,0,255),-1) if(angleCounter!=0): averageAngle = averageAngle / angleCounter if(suppressInput == False): print("-----------------------AVERAGE ANGLE = ", averageAngle) #########################Obtaining statistics on incorrectly labelled features########################################## if(labellingStats == True): incorrectlyMatchedFeatures = comparingLabelling.compare(inputFileType, outputTextFilename, "he_bolts239.txt") for i in incorrectlyMatchedFeatures: cv2.circle(img,(int(float(i[1])),int(float(i[2]))),5,(255,255,255),1) text = i[0][-2:] text = text.lstrip("0") cv2.putText(img, f'{text}', (int(float(i[1])),int(float(i[2]))), cv2.FONT_HERSHEY_PLAIN, 1, (255,255,180), 1) cv2.imwrite("OUTPUT.jpg",img) cv2.imshow(filename,img)
ordered_input_bolts[bolt_no][1]), (textx, texty), (0, 140, 140), thickness=1, lineType=8, shift=0) cv2.putText(img, f'{ordered_bolt_no}', (textx, texty), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 1) bolt_no += 1 ############################################################################################# outputFile.close() #########################Obtaining statistics on incorrectly labelled features########################################## #bolt_dict = {b: reco_transformed[fitter_all.feature_index[b]] for b in common_bolt_locations.keys()} if (labellingStats == True): incorrectlyMatchedFeatures = comparingLabelling.compare( inputFileType, outputTextFilename, "045-manualLabelling.txt") for i in incorrectlyMatchedFeatures: cv2.circle(img, (int(float(i[1])), int(float(i[2]))), 5, (255, 255, 255), 1) text = i[0][-2:] text = text.lstrip("0") cv2.putText(img, f'{text}', (int(float(i[1])), int(float(i[2]))), cv2.FONT_HERSHEY_PLAIN, 1, (255, 255, 180), 1) cv2.imwrite("OUTPUT.jpg", img) cv2.imshow(filename, img)
texty = int(item[1] + (30) * np.sin(angle)) pointerx = int((textx + textx + 20) / 2) pointery = int((texty + texty - 20) / 2) cv2.line(img, (item[0], item[1]), (textx, texty), (0, 150, 150), thickness=2, lineType=8, shift=0) #cv2.rectangle(img,(textx,texty),(textx+15,texty-15),(0,0,0), thickness=-1, lineType=8, shift=0) #cv2.circle(img,(textx,texty),10,(0,0,0),-1) #cv2.circle(img, (item[1], item[0]), 5, (0,0,255), -1) cv2.putText(img, f'{ordered_bolt_no}', (textx, texty), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 1) ############################################################################################# if (labellingStats == True): incorrectlyMatchedFeatures = comparingLabelling.compare( inputFileType, outputTextFilename, "379 (BJ).txt") for i in incorrectlyMatchedFeatures: cv2.circle(img, (int(float(i[1])), int(float(i[2]))), 5, (255, 255, 255), 1) text = i[0][-2:] text = text.lstrip("0") cv2.putText(img, f'{text}', (int(float(i[1])), int(float(i[2]))), cv2.FONT_HERSHEY_PLAIN, 1, (255, 255, 180), 1) cv2.imwrite("OUTPUT.jpg", img) cv2.imshow(filename, img) outputFile.close()