Have you ever struggled with editing your Tiff document while on the go? Well, DocHub has a great solution for that! Access this online editor from any internet-connected device. It allows users to Negate shape in Tiff files quickly and anytime needed.
DocHub will surprise you with what it provides you with. It has robust functionality to make any changes you want to your paperwork. And its interface is so simple-to-use that the entire process from beginning to end will take you only a few clicks.
As soon as you complete modifying and sharing, you can save your updated Tiff file on your device or to the cloud as it is or with an Audit Trail that includes all changes applied. Also, you can save your paperwork in its original version or turn it into a multi-use template - complete any document management task from anywhere with DocHub. Sign up today!
hi everyone welcome to digital sweeney on youtube and please do not forget to subscribe because youll benefit from these tips and tricks and of course my regular videos and this is again based on your questions especially during these unit series many of you are asking okay you have large images and you have large masks corresponding masks right that you have annotated how would you divide them into smaller patches so you can actually train a unit or whatever algorithm youre trying to train so this video is exactly about this explaining this believe me its very very simple and straightforward of course you can write uh every line you know to to take in the large images and then cut them down i used to do that now there is a library called patchify and ive used it in a couple of my videos in the past but thats exactly what you can use to cut down your images and store the cropped images or patched images into a into a numpy area or save your patched images to your drive so you can