A system for detecting a tool in a scene, the system comprising: a camera unit for acquiring an image of a scene; and one or more processors configured to: divide the image into a first number of patches to generate a first set of patches, wherein a patch is an area of the image, perform object detection on the first set of patches to identify the tool in a patch of the first set of patches, determine that the tool is not detected in the first set of patches, divide the image into a second number of patches to generate a second set of patches, after determining that the tool is not detected in the first set of patches, perform object detection on the second set of patches to identify the tool in a patch of the second set of patches, and determine that the tool is detected in a patch of the second set of patches, wherein the one or more processors being further configured to train a computer neural network to identify the tool before acquiring the image of the scene; and wherein the computer neural network is trained at a scale, and the scale is used for: performing the object detection on the first set of patches, and performing the object detection on the second set of patches. a camera unit for acquiring an image of a scene; and one or more processors configured to: divide the image into a first number of patches to generate a first set of patches, wherein a patch is an area of the image, perform object detection on the first set of patches to identify the tool in a patch of the first set of patches, determine that the tool is not detected in the first set of patches, divide the image into a second number of patches to generate a second set of patches, after determining that the tool is not detected in the first set of patches, perform object detection on the second set of patches to identify the tool in a patch of the second set of patches, and determine that the tool is detected in a patch of the second set of patches, wherein the one or more processors being further configured to train a computer neural network to identify the tool before acquiring the image of the scene; and wherein the computer neural network is trained at a scale, and the scale is used for: performing the object detection on the first set of patches, and performing the object detection on the second set of patches. divide the image into a first number of patches to generate a first set of patches, wherein a patch is an area of the image, perform object detection on the first set of patches to identify the tool in a patch of the first set of patches, determine that the tool is not detected in the first set of patches, divide the image into a second number of patches to generate a second set of patches, after determining that the tool is not detected in the first set of patches, perform object detection on the second set of patches to identify the tool in a patch of the second set of patches, and determine that the tool is detected in a patch of the second set of patches, wherein the one or more processors being further configured to train a computer neural network to identify the tool before acquiring the image of the scene; and wherein the computer neural network is trained at a scale, and the scale is used for: performing the object detection on the first set of patches, and performing the object detection on the second set of patches. performing the object detection on the first set of patches, and performing the object detection on the second set of patches.