![]() ![]() ![]() Some of these results were measured by "team MegaDetector", and some are user-reported YMMV. These were chosen to be "typical", and anecdotally they are, though FWIW we have seen very high-resolution images that run around 30% slower than these, and very low-resolution images (typically video frames) that run around 100% faster than these. These results are based on a test batch of around 13,000 images from the public Snapshot Karoo and Idaho Camera Traps datasets. We don't typically recommend running MegaDetector on embedded devices, although some folks have done it! More commonly, for embedded scenarios, it probably makes sense to use MegaDetector to generate bounding boxes on lots of images from your specific ecosystem, then use those boxes to train a smaller model that fits your embedded device's compute budget. We include a few benchmark timings below on some specific GPUs. On a dedicated deep learning GPU that is neither the fastest nor slowest GPU you can buy in 2023, MegaDetector v5 can process between 300,000 and 1,000,000 images per day.This might be totally fine for scenarios where you have even hundreds of thousands of images, as long as you can wait a few days. On a decent laptop (without a fancy deep learning GPU) that is neither the fastest nor slowest laptop you can buy in 2023, MegaDetector v5 can process somewhere between 25,000 and 50,000 images per day.Here are some rules of thumb to help you estimate how fast you can run MegaDetector on different types of hardware. If you want to crunch through 20 million images as fast as possible, you'll want at least one GPU. If you only need to process a few thousand images per week, for example, a typical laptop will be just fine. That said, you can run anything on anything if you have enough time, and we're happy to support users who run MegaDetector on their own GPUs (in the cloud or on their own PCs), on their own CPUs, or even on embedded devices. MegaDetector is designed to favor accuracy over speed, and we typically run it on GPU-enabled computers. But there are many reasons to run MegaDetector on your own how practical this is will depend in part on how many images you need to process and what kind of computer hardware you have available. We often run MegaDetector on behalf of users as a free service see our "Getting started with MegaDetector" page for more information. That means we don't know who's using it unless you contact us (or we happen to run into you), so please please pretty-please email us at if you find it useful! How fast is MegaDetector, and can I run it on my giant/small computer? MegaDetector is free, and it makes us super-happy when people use it, so we put it out there as a downloadable model that is easy to use in a variety of conservation scenarios. This page is about the technical elements of MegaDetector if you are an ecologist looking to use MegaDetector, you may prefer to start at our "Getting started with MegaDetector" page. It does not identify animals to the species level, it just finds them. To this end, this page hosts a model we've trained - called "MegaDetector" - to detect animals, people, and vehicles in camera trap images. Machine learning can accelerate this process, letting biologists spend their time on the images that matter. ![]() This primarily includes empty images, but for many projects, images of people and vehicles are also "noise", or at least need to be handled separately from animals. Tell me more about why detectors are a good first step for camera trap imagesĬonservation biologists invest a huge amount of time reviewing camera trap images, and a huge fraction of that time is spent reviewing images they aren't interested in.Have you evaluated MegaDetector's accuracy?.What if I just want to run non-MD scripts from this repo?.OK, but is that how the MD devs run the model?.How fast is MegaDetector, and can I run it on my giant/small computer?. ![]()
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