In Machine Learning, Object Detection is a computer vision technique which allows us to locate and identify objects present in an image or a video. Object Detection can count objects in a video or a picture while precisely labeling them and determining their location. Object Detection is widely utilized in different domains for instance healthcare, autonomous driving, face and iris recognition. Object Detection is a supervised machine learning problem requiring you to train your models on labeled examples. In the training dataset, each image in the dataset must be accompanied by a file including the boundaries and the class of the object it has. Object Detection network is trained on the annotated data until it can find region in images that correspond to each kind. Object Detection is often confused with Image Recognition. An image is given a label through Image Recognition. Image Recognition assigns a label to an image for example a picture of a cat will receive the label “Cat”. A picture of two cats will still receive the label “cat”. Object Detection works by drawing a box around each Cat and labeling it “Cat”. Object Detection provides more information about an image than recognition.