#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()