The Semantic Segmentation or Pixel-level labeling is used to label each and every pixel in the image. Unlike polygonal segmentation devised specifically to detect a defined object of interest, full semantic segmentation provides a complete understanding of every pixel of the scene in the image. This kind of for detection and localization of specific objects […] The post Use Case: Semantic Segmentation of Autonomous Vehicles appeared first on Playment Blog.
Performing exploratory data analysis on the three most widely used semantic segmentation datasets in the Autonomous Vehicles domain. import cv2 from collections import namedtuple, Counter from glob import glob import matplotlib.pyplot as plt import numpy as np import os import pickle from skimage.io import imread from tqdm.notebook import tqdm from bdd_config import labels as bdd_labels […] The post Comparing Cityscapes, Mapillary and BDD for Segmentation Datasets appeared first on Playment Blogs.
I started working with Playment back in January 2017 with a vision to create a fantastic customer-centric organization. However, working for an early-stage startup is stressful; not only did I have to learn about complex product and features; I had to learn them while they were changing. Very often, the product that my team worked […] The post What I love about working at Playment? appeared first on Playment Blogs.
Today, almost all autonomous vehicle companies targeting level-5 autonomy use a setup involving LiDARs calibrated together with cameras working in sync to perceive the world around them. As a result, we’re seeing a huge surge in the demand for data to train the deep learning systems built around these sensors. To this end, we built […] The post Playment partners with Ouster to simplify LiDAR data annotations appeared first on Playment Blogs.