Supervise.ly

Step 1: Collect images from production lines.

Step 2: Annotate defects using Supervisely's labeling tools.

Step 3: Train a deep learning model to detect defects automatically.

Step 4: Deploy the model to assist in quality inspections.

Step 1: Import lung CT scans into Supervisely.

Step 2: Annotate regions of interest, such as tumors.

Step 3: Train an AI model to detect lung abnormalities.

Step 4: Evaluate the model's performance and refine annotations.

Step 1: Import LiDAR point clouds and associated camera images.

Step 2: Use the 3D cuboid tool to annotate vehicles, pedestrians, and other objects.

Step 3: Track objects across consecutive frames.

Step 4: Train a 3D object detection model using the annotated data.

Step 1: Capture images of retail shelves.

Step 2: Annotate product locations and identify missing items.

Step 3: Train a model to automatically detect products and identify planogram violations.

Step 4: Generate reports on product availability and planogram compliance.

Step 1: Import satellite imagery into Supervisely.

Step 2: Annotate land cover types, such as forests, water bodies, and urban areas.

Step 3: Train a semantic segmentation model to classify land cover.

Step 4: Apply the model to large areas to create land cover maps.