Blogs

Prediction DeepForest allows the prediction of the new data with the prebuilt model or we can also use our custom trained models.  Predict a single image DeepForest allows to predict single images with predict_image function which can read an image from memory or file provided by user, which returns the bounding boxes of the predicted trees in image.   image_path = get_data( "OSBS_029.png" ) boxes = model.predict_image( path = image_path , return_plot = False )     boxes.head() xmin ymin xmax ymax label scores 0 334.708405 342.333954 375.941376 392.187531 0 0.736650 1 295.990601 371.456604 331.521240 400.000000 0 0.714327 2 216.828201 207.996216 245.123276 240.167023 0 0.691064 3 276.206848 330.758636 303.309631 363.038422 0 0.690987 4 328.604736 45.947182 361.095276 80.635254 0 0.638212   The current DeepForest has release model there is a category named &qu

My GSOC workflow I have talked about  what my project is about, and some weeks have passed since the start of the coding period, however, now I realize I have yet to talk about what GSoC is and what is my daily routine as a participant. This post will have two main sections, one little introduction about GSoC (all the info about the program is available on its official site), and a second larger section on my daily work routine. GSoC Google Summer of Code is a global program organized by Google Open Source. Its goal is at the same time to support students by giving them the opportunity to work as programmers during their summer and to empower and increase the open source software community. It started in 2005 with 200 students, growing every year. GSoC has two selection phases, one for free open source projects and another for students. Once the organizations have been selected, it is up to the organizations alone to choose which students are accepted. Google’s role is to assign the nu

Start of the Coding Period After the admission to the GSoC program, there is a time period to get started with the project, contact the mentors and so on. After this, the Coding Period starts. This year, it started on May 27th. In my case, I had already contributed to DeepForest, so I had already set up my working environment even before the proposal submission. Thus, I dedicated this period to add detail to my proposal and to discuss with my mentors who were actually very helpful and were always ready to guide and discussed how to tackle the different tasks. I started by checking some papers on multi class object detection and how Resnet works, similar projects and going issue by issue in DeepForest to find all feature requests related to my project. Afterwards I outlined a list of all the methods with their priority and workflow for the whole project which was then discussed with my mentors. I immediately started with a pull request on making the model able to interact with multiple

DeepForest This project aims to make the model which would already be trained for the classification of species and detection of alive and dead, trees or birds using transfer learning on the current release model which is based on object detection, only detecting trees and birds, for now, It also involves improving the user interface for working with the multi-class model for a better understating of the species. Basic Understanding of project Through initial understanding and contribution to DeepForest, I have grasped a basic understanding that DeepForest uses Retinanet as a one-stage object detection model that utilizes a focal loss function to address class imbalance during training and which is composed of a backbone network. Backbone Network The backbone is responsible for computing a convolutional feature map over an entire input image and is an off-the-self convolutional network to predict individual tree crowns and birds from airborne RGB images. The pre-built model uses a semi

  How to create Dart packages for Flutter In Flutter, we use the Dart programming language to build cross-platform applications. Dart packages are like the libraries you might be used to installing for, say, Node.js projects using either npm or yarn. These packages are built by Flutter devs for Flutter devs. In this tutorial, we’ll show you how to build Dart packages and share them with other Flutter developers around the world. We’ll cover the following with practical examples: What is a Dart package? Flutter project requirements Dart package types Creating a Flutter/Dart package Initializing a Git repo Writing a Flutter widget Testing your Flutter package Publishing and sharing your Flutter package What is a Dart package? Dart packages help us solve issues and create workarounds for problems without having to write the code ourselves from scratch. For example, let’s say we’re building a Flutter app and we discover that we need to upload a picture from our local filesystem and display