Downloading a pretrained object detection model
We've pretrained and uploaded a state-of-the-art object detection model called You only look once, or YOLO for short, so that you can easily download it into this scenario and deploy it from here. To do so, just run
curl -o ./yolo_v2.pb https://github.com/deeplearning4j/dl4j-test-resources/raw/4fbca7f8286b7e0856903828193f50c08ceb1cee/src/main/resources/tf_graphs/examples/yolov2_608x608/frozen_model.pb
YOLO can detect objects in images by giving you bounding boxes around these objects, together with a probability assessing how likely the model thinks this box actually contains that object. The version of YOLO we provide here is trained on the so called COCO dataset, which contains 80 real-world categories, such as person, dog or cat. For instance, if you take the following image, you can expect this model to find all people, cars, bikes and umbrellas in it.
In the next step you'll see how to deploy your downloaded model quickly to get an image with labeled bounding boxes for this input image. Go ahead and download this image:
curl -o input.jpg https://raw.githubusercontent.com/SkymindIO/skil-python/cc99a0d9bb67d63f21233fad264a0fa5c1eae4c9/examples/tensorflow-yolo/input.jpg