image-segmentation

I am trying to detect the biggest/larger rectangular shape and draw bounding box to the detected area. I have tried different way to detect perfect edge ( Edges with no holes) for contour detection. I searched on stackoverflow and the solution proposed OpenCV sharpen the edges (edges with no holes) and Segmentation Edges did not work with my sample image. I would like to detect biggest/larger rectangular shape on the following two images Original Image 1 and Original Image 2 Below is the code that i use to preprocess the image before calling findcontour. public Mat processGrayScaleImage(Mat

Is there any recommendable per class IoU(intersection over union) per pixel accuracy(different from bounding box) implementation.I am using caffe and managed to get the mean IoU but i am having difficulty in doing IoU for per class accuracy.I would appreciate a lot if someone could point out a good implementation in any language so far this the only close semantic segmentation with multiple pixel label i ve seen so far here 来源： https://stackoverflow.com/questions/44041096/iou-for-semantic-segmentation-implementation-in-python-caffe-per-class

I have set up the Google's DeepLab V3 Demo on my local system and it runs successfully after making some minor changes. It's as: # -*- coding: utf-8 -*- # DeepLab Demo # This demo will demostrate the steps to run deeplab semantic segmentation model on sample input images. import os from io import BytesIO import tarfile import tempfile from six.moves import urllib from matplotlib import gridspec from matplotlib import pyplot as plt import numpy as np from PIL import Image import tensorflow as tf class DeepLabModel(object): """Class to load deeplab model and run inference.""" INPUT_TENSOR_NAME =