> ## Documentation Index > Fetch the complete documentation index at: https://docs.encord.com/llms.txt > Use this file to discover all available pages before exploring further. # Image and Video Annotation - E2E ## What are we doing? Using a very small dataset of fruit (apples, bananas, blueberries, cherries, kiwi, persimmons, and strawberries) you will learn how to use Encord with images and videos. For all the tasks in this end-to-end process, all artifacts, relevant information, and code is provided. How you want to proceed is up to you. Each section provides a path to use Encord from basic use to SOTA (state-of-the-art) complexity. Pick the path at each STEP that suits your needs best. ## Our Goals Our basic goals are this: * **Import data:** Get our data into Encord. We might want to manage and curate our data, but that is going to depend on how much data we have or how complex our Projects are. * **Label data:** Label our data and export the labels. This is going to involve creating a Project and then actually labeling and reviewing our labels. Once our labels are okay we can export them from Encord. * **Validate our labels:** At scale, using Active streamlines and significantly speeds up validating our labels. * **Evaluate our model:** Compare and optimize our model's performance using Active. How you intend to use your data in Encord dictates the best way to use Encord. Using cloud integrations, the SDK, or Agents adds complexity to using Encord, but at scale, this complexity adds significant value. ## STEP 1: Import Data Performing ANY of these tasks results in creating the Dataset `E2E Fruit Dataset` for use with the Project. Testing and basic annotation Projects using local data. Testing and basic annotation Projects using cloud data. Testing and basic annotation Projects using cloud data. Programmatic testing and basic annotation Projects using cloud data. Manage and curate large amounts of data for one or more Projects, using Index Premium. Programmatic managing and curating large amounts of data for one or more Projects, using Index Premium. ## STEP 2: Create Project Performing ANY of these tasks results in creating the Project `E2E Fruit Project` to annotate. * The Ontology is the same for ALL tasks. * The Workflow varies depending on the task. Create Projects (Ontologies, Workflows, and Projects) using the Encord UI. Create Projects (Ontologies, Workflows, and Projects) using the SDK. Create Consensus Projects (Ontologies, Workflows, and Projects) using the UI. Create Consensus Projects (Ontologies, Workflows, and Projects) using the UI. Create Projects (Ontologies, Workflows, and Projects) for use with your own labels. Create Projects (Ontologies, Workflows, and Projects) for use with your own model predictions. ## STEP 3: Label Data Performing ANY of these tasks results in labeling the data and reviewing the labels on the data in the Project `E2E Fruit Project`. Manually annotate and review your data and then export your labels. Use SAM 2 and SAM 2 tracking to annotate your data, review using humans, and then export your labels using the UI or the SDK. Use SAM 2 and SAM 2 tracking to annotate your data on a Consensus Project, review using humans, and then export your labels using the UI or the SDK. Use your model's labels and review your data (with humans in the loop). Use your model's predictions. ## STEP 4: Label Verification Label verification can be performed visually in Annotate as a reviewer. However, at scale, using Active to verify the quality of your labels significantly improves the effectiveness and speed of label verification. Verify the quality of your labels using Active. Programmatically verify the quality of your labels using Active. ## STEP 5: Model Evaluation Use Active to compare and optimize your model's performance. Compare and optimize your model's performance using Active. Programmatically compare and optimize your model's performance using Active.