def localization(image, min_size_components, similitary_contour_with_circle, model, count, current_sign_type, file_bin_path):
original_image = image.copy()
binary_image = preprocess_image(image)
binary_image = removeSmallComponents(binary_image, min_size_components)
binary_image = cv2.bitwise_and(binary_image,binary_image, mask=remove_other_color(image))
cv2.imwrite(os.path.join(file_bin_path, str(count)+'_'+'binary_image'+'.png'), binary_image)
#cv2.imshow('BINARY IMAGE', binary_image)
contours = findContour(binary_image)
#signs, coordinates = findSigns(image, contours, similitary_contour_with_circle, 15)
sign, coordinate = findLargestSign(original_image, contours, similitary_contour_with_circle, 15)
text = ""
sign_type = -1
i = 0
if sign is not None:
sign_type = getLabel(model, sign)
sign_type = sign_type if sign_type <= 8 else 8
text = SIGNS[sign_type]
if sign_type > 0 and sign_type != current_sign_type:
cv2.rectangle(original_image, coordinate[0],coordinate[1], (0, 255, 0), 1)
font = cv2.FONT_HERSHEY_PLAIN
cv2.putText(original_image,text,(coordinate[0][0], coordinate[0][1] -15), font, 1,(0,0,255),2,cv2.LINE_4)
return coordinate, original_image, sign_type, text
def detectImageFromVideo(clf):
font = cv2.FONT_HERSHEY_PLAIN
count = 0
cam = cv2.VideoCapture("MVI_1049.avi")
while (1):
_, img = cam.read()
if not _:
print("FINISHED")
break
else:
original_image = img
img = preprocess_image(original_image)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(imgHSV, lowerBound, upperBound)
mask_tmp = mask.copy()
mask = cv2.dilate(mask, kernelOpen)
img_binarization = binarization(img)
mask = MorpRemoveNoise(mask)
img_binarization = cv2.bitwise_and(mask_tmp, mask)
mask = removeSmallComponents(img_binarization, 300)
_, contours, h = cv2.findContours(mask, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
sign, coordinate = cropContour(img_binarization, contours, 0.65,
15)
text = ""
sign_type = None
if sign is not None:
sign_type = classification.getLabel(clf, sign)
sign_type = sign_type if sign_type > 0 else 0
text = signName[sign_type]
if sign_type > 0:
cv2.rectangle(original_image, coordinate[0], coordinate[1],
(0, 255, 0), 1)
cv2.putText(original_image, text,
(coordinate[0][0], coordinate[0][1] - 15), font, 1,
(0, 0, 255), 2, cv2.LINE_4)
cv2.imshow("Result", original_image)
if cv2.waitKey(10) & 0xFF == ord('q'):
cv2.destroyAllWindows()
def localization(image, min_size_components, similitary_contour_with_circle,
model, count, current_sign_type):
original_image = image.copy()
binary_image = preprocess_image(image)
binary_image = removeSmallComponents(binary_image, min_size_components)
binary_image = cv2.bitwise_and(binary_image,
binary_image,
mask=remove_other_color(image))
#binary_image = remove_line(binary_image)
cv2.imshow('BINARY IMAGE', binary_image)
contours = findContour(binary_image)
sign, coordinate = findLargestSign(original_image, contours,
similitary_contour_with_circle, 15)
text = ""
sign_type = -1
i = 0
# nhận dạng loại biển báo
if sign is not None:
#cắt hình là biển báo sau đó lưu vào file dạng số_tên.png
sign_type = getLabel(model, sign)
sign_type = sign_type if sign_type <= 11 else 11
text = SIGNS[sign_type]
cv2.imwrite(str(count) + '_' + text + '.png', sign)
if sign_type > 0 and sign_type != current_sign_type: #vẽ hình chữ nhật bao bên ngoài và puttext(ghi tên biển báo)
cv2.rectangle(original_image, coordinate[0], coordinate[1],
(0, 255, 0), 1)
font = cv2.FONT_HERSHEY_PLAIN
cv2.putText(original_image, text,
(coordinate[0][0], coordinate[0][1] - 15), font, 1,
(0, 0, 255), 2, cv2.LINE_4)
return coordinate, original_image, sign_type, text
while True:
if not video_cap.isOpened():
print("error: video capture is not opened")
break
ret, frame = video_cap.read()
if not ret:
print("error: failed to read frame")
break
frame = cv2.resize(frame, (640, 480))
ret = extract_roi(frame)
if ret is None:
print("error: failed to extract roi")
continue
roi, x, y, r = ret
label = textLables[getLabel(model, roi)]
print(label)
cv2.rectangle(frame, (x - r, y - r), (x + r, y + r), (0, 255, 255), 3)
cv2.imshow("", frame)
if cv2.waitKey(1) & 0xFF == ord('q'): break
video_cap.release()
