1/22/2024 0 Comments Kaggle nfl play by playOur goal is to detect helmets and collisions. Each of these techniques is designed to simulate real-world differences we might see in our images. To the Kaggle data, we added random rotation, brightness, exposure, blur, and cutout to our image. Image Augmentation: These are steps you want to apply to only your training images so that your model can better generalize to unseen images.If you think about each pixel as an input to your model, there are over 920,000 inputs to your model! We used Roboflow to resize our images to be smaller (384 x 216) while keeping the same aspect ratio. It's good to have images that are of high resolution (blurry photos aren't very useful), but that high resolution can require significantly more time to train your model. In the Kaggle data, our images were very large: 1280 x 720 pixels. For example, if we want to convert our images to greyscale or re-size our images. Image Preprocessing: These are steps that you want to apply to all of your images.The image pre-processing and image augmentation techniques applied to our data. We uploaded the images to Roboflow to pre-process and augment our images. Kaggle has also done this for us! (Roboflow recently launched its labeling feature you can annotate your images right in the app.) In many image problems, you may need to annotate your images. (If you ever encounter a situation where you have a video and aren't given the images, Roboflow can turn video into images for you!) A sample of images after being pre-processed and augmented in Roboflow. Kaggle has done this for us, so we'll work with the images directly. Videos are just a sequence of pictures, so it is possible to splice the video into its individual images. By better detecting when two helmets crash into each other, we can start to understand what factors make it likelier that these collisions occur and if changes can be made – for example, to NFL rules – that may decrease the rate at which TBIs or CTE occur. The purpose of this Kaggle competition is to detect helmets on the field and when two helmets connect. Estimates of the percentage of NFL players with signs of CTE are well above 90%, with three studies from 20 estimating 95%, 97%, and 99%. CTE is a disease that may cause, among other symptoms, problems with judgment, reasoning, problem solving, impulse control, and aggression, according to Boston University. While helmets are designed to protect players' heads and necks, there is a lot of concern surrounding football players experiencing traumatic brain injuries (TBI) and/or developing chronic traumatic encephalopathy (CTE).
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