mvoreo.blogg.se - Trash it pictures

#TRASH IT PICTURES MOVIE#
#TRASH IT PICTURES MANUAL#

Selecting what images to annotate and add was done rather methodically. The results were promising, but clearly not enough: This was done on about 40 images selected from the web. We selected the initial weights available (tiny yolo) and trained the model to detect only one class: trash. We started off testing the idea of trash detection with the YOLO ( You Only Look Once) object detection system in the beginning of March 2019. These images were not in the training dataset and were used to assess the accuracy of the model. Result validation, Testing the training – After each training cycle, the best model was chosen and tested by having it predict trash on test images.Training the machine learning model – This was done multiple times, each time adapting the parameters of the Mask R-CNN model to improve the results and adding new images to the training dataset.

We got help from the lovely volunteers from LDIW Foundation and UC Riverside, and all together manually annotated over 1000 images for the model to learn what trash is.

#TRASH IT PICTURES MANUAL#

Object detection – This step was very time consuming because it required a lot of manual work: marking all the trash in each of our selected images.

Based on the results, we determined what images we had to add to the next iteration of training. We started with a sample of images, trained the model, and analyzed the results.

Selecting images – We strategically chose most of the images that went into the model.

We had thousands of images collected through the World Cleanup App and scraped from Google Street View to use for our model.

Collecting images – Luckily for us, this part was mostly done by the Let’s Do It World foundation and UC Riverside, who are experts at identifying and cleaning up trash.

The machine learning project was divided into 5 steps : Trash is a word people use of an object that lacks purpose, and the purpose of an object is often not obvious in the images we use for teaching an algorithm to spot trash. Not everything that LOOKS like trash IS trash. This is the main challenge with any image-based trash detection algorithm. BUT, when those cans are on the street, they can most likely be considered trash. Imagine a restaurant table with cans of soda on it, people having fun, eating and drinking. Trash is a rather complicated object to detect. TRASH is published by Random House, and is available at all good bookshops, or through the usual on-line stores.This is the story of how we achieved it. I also get requests for a sequel, but that's not going to happen: the book ends just where it needs to end.' A school in Indonesia staged it as a piece of dance-drama, and I'm often asked to talk about how it came to be written. Schools all over the world are studying it, and I visited a primary school last year that had turned two year-six classrooms into a 'Trash' installation.

'It's a fast-moving thriller,' says Andy, 'and – yes – its popularity still surprises me.

#TRASH IT PICTURES MOVIE#

The movie hit cinemas in 2014, directed by Stephen Daldry and scripted by Richard Curtis. The novel was shortlisted for the CILIP Carnegie Medal, and has been translated into thirty-five languages. 'Trash' was published by the legendary David Fickling, whose credits include 'The Boy in the Striped Pyjamas' and 'The Curious Incident of the Dog in the Night-Time'. And it's three street-boys against the world. As the net tightens, they uncover a dead man's mission to put right a terrible wrong. Hounded by the police, it takes all their quick-thinking and fast-talking to stay ahead. Soon he and his friends are running for their lives. A small leather bag falls into his hands. Then one unlucky-lucky day, the world turns upside down. He spends his days wading through mountains of steaming trash, sifting it, sorting it, breathing it, sleeping on it.