video1.0<iframe src="https://www.loom.com/embed/bba8d51c07594a03bbc8eb7c4ec4c018" frameborder="0" width="1152" height="864" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8641152Loomhttps://www.loom.com8641152https://cdn.loom.com/sessions/thumbnails/bba8d51c07594a03bbc8eb7c4ec4c018-00001.gif1525Starting your project on Roboflow. Dataset Upload --> Dataset Generation & Model Training with Roboflow Train. Plus: Quick insight into Dataset Health Check, selecting preprocessing & augmentation steps, and exporting in different annotation formats. Time stamps: 0:00 - Creating Your Project 0:40 - What are annotation batches? Uploading images (working with annotation batches, and our annotation workflow) https://blog.roboflow.com/annotation-workflow/ 1:00 - Getting Images from Roboflow Universe to add to a project 1:58 - Uploading images to your annotation batch (fresh unannotated images, already annotated images, video files) 5:00 - Using the annotation tool 7:00 - Completing an annotation batch, and generating versions of your dataset for model training 8:10 - Uploading the images from Roboflow Universe to the project 10:35 - More on navigating annotation batches, and uploading new images 12:05 - Generating versions: quick primer on preprocessing and augmentation -- for more: https://roboflow.slab.com/posts/roboflow-preprocessing-and-augmentation-v57xsmv5 14:22 - Primer on Dataset Health Check -- insights into your dataset like: total number of annotations, heatmap of annotations, average image sizes, number of labels for each class (class balance) 15:55 - Training your model 16:20 - Using Label Assist 18:51 - Training a custom model (https://models.roboflow.com) 21:00 - Roboflow Train results: model inference/deployment options and running tests https://docs.roboflow.com/inference