Case Study: Footage Feature Annotation

We trained a neural network to recognize objects in real world images and videos. Fine grained image properties can be extracted, and statistics can be tracked and stored. This models can be trained to detect specific types of objects and features, according to client's needs.

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Evaluating your Images

You can find below a list of your pictures, ranked according to the number of objects that were detected within them. The image on top is the most likely to contain objects according to our pretrained models. All the way to the image at the bottom of the list, which shows the least amount of detected objects. Try uploading more pictures, and see the list updating accordingly!

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