Plz Add comment Every line of code Accident Detection:- Plz add comment in each line that will help me to understand

def calculateCollision(boxes,classes,scores,image_np):

global msg

#cv2.putText(image_np, "NORMAL!", (230, 50), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 2, cv2.LINE_AA)

for i, b in enumerate(boxes[0]):

if classes[0][i] == 3 or classes[0][i] == 6 or classes[0][i] == 8:

if scores[0][i] > 0.5:

for j, c in enumerate(boxes[0]):

if (i != j) and (classes[0][j] == 3 or classes[0][j] == 6 or classes[0][j] == 8) and scores[0][j]> 0.5:

Rectangle = namedtuple('Rectangle', 'xmin ymin xmax ymax')

ra = Rectangle(boxes[0][i][3], boxes[0][i][2], boxes[0][i][1], boxes[0][i][3])

rb = Rectangle(boxes[0][j][3], boxes[0][j][2], boxes[0][j][1], boxes[0][j][3])

ar = rectArea(boxes[0][i][3], boxes[0][i][1],boxes[0][i][2],boxes[0][i][3])

col_threshold = 0.6*np.sqrt(ar)

area(ra, rb)

if (area(ra,rb)

print('accident')

msg = 'ACCIDENT!'

beep()

return True

else:

return False

def rectArea(xmax, ymax, xmin, ymin):

x = np.abs(xmax-xmin)

y = np.abs(ymax-ymin)

return x*y

def load_image_into_numpy_array(image):

(im_width, im_height) = image.size

return np.array(image.getdata()).reshape((im_height, im_width, 3)).astype(np.uint8)

def area(a, b): # returns None if rectangles don't intersect

dx = min(a.xmax, b.xmax) - max(a.xmin, b.xmin)

dy = min(a.ymax, b.ymax) - max(a.ymin, b.ymin)

return dx*dy

def detector():

global msg

msg = ''

cap = cv2.VideoCapture(filename)

with detectionGraph.as_default():

with tf.compat.v1.Session(graph=detectionGraph) as sess:

while True:

ret, image_np = cap.read()

(h, w) = image_np.shape[:2]

blob = cv2.dnn.blobFromImage(cv2.resize(image_np, (300, 300)),0.007843, (300, 300), 127.5)

net.setInput(blob)

detections = net.forward()

for i in np.arange(0, detections.shape[2]):

confidence = detections[0, 0, i, 2]

if confidence > 0.2:

idx = int(detections[0, 0, i, 1])

box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])

(startX, startY, endX, endY) = box.astype("int")

if (confidence * 100) > 50:

label = "{}: {:.2f}%".format(CLASSES[idx],confidence * 100)

cv2.rectangle(image_np, (startX, startY), (endX, endY),COLORS[idx], 2)

y = startY - 15 if startY - 15 > 15 else startY + 15

image_np_expanded = np.expand_dims(image_np, axis=0)

image_tensor = detectionGraph.get_tensor_by_name('image_tensor:0')

boxes = detectionGraph.get_tensor_by_name('detection_boxes:0')

scores = detectionGraph.get_tensor_by_name('detection_scores:0')

classes = detectionGraph.get_tensor_by_name('detection_classes:0')

num_detections = detectionGraph.get_tensor_by_name('num_detections:0')

if image_np_expanded[0] is not None:

(boxes, scores, classes, num_detections) = sess.run([boxes, scores, classes, num_detections], feed_dict={image_tensor: image_np_expanded})

calculateCollision(boxes, classes, scores, image_np)

cv2.putText(image_np, msg, (230, 50), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 0, 0), 2, cv2.LINE_AA)

cv2.imshow('Accident Detection', image_np)

if cv2.waitKey(5) & 0xFF == ord('q'):

cv2.destroyAllWindows()

break

def exit():

main.destroy()