Objects detected as multiple dots while using custom tensorflow model in OpenCV dnn [closed]

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I am using Ubuntu 16.04, built Opencv 3.4.0 from source using master for python 2.7 and 3.5 today (expecting the PR's pushed for tensorflow multibox anchors dnn issues)

I tried to replicate frozen_inference_graph.pb & textgraph

On running the sample provided as project.py

import numpy as np
import cv2 as cv
cvNet = cv.dnn.readNetFromTensorflow('frozen_inference_graph.pb', 'ssd_mobilenet_v1_coco_hat.pbtxt')
img = cv.imread('image4.jpg')
cvNet.setInput(cv.dnn.blobFromImage(img, 1.0/127.5, (300, 300), (127.5, 127.5, 127.5), swapRB=True, crop=False))
cvOut = cvNet.forward()
for detection in cvOut[0,0,:,:]:
    score = float(detection[2])
    if score > 0.5:
        left = detection[3] * img.shape[1]
        top = detection[4] * img.shape[0]
        right = detection[5] * img.shape[1]
        bottom = detection[6] * img.shape[0]
        cv.rectangle(img, (int(left), int(top)), (int(right), int(bottom)), (0, 255, 0))
cv.imshow('img', img)
cv.waitKey(0)

tf_importer.cpp and prior_box_layer.cpp files of OpenCV master sourceare shared here:

https://drive.google.com/open?id=1YgS...

Output is with detections having couple of random green color dots as below, instead of rectangular bounding boxes

Any fix for this would be very much helpful