Depth Estimation

Class: DepthEstimationBlockV1

Source: inference.core.workflows.core_steps.models.foundation.depth_estimation.v1.DepthEstimationBlockV1

        🎯 This workflow block performs depth estimation on images using Apple's DepthPro model. It analyzes the spatial relationships
        and depth information in images to create a depth map where:

        📊 Each pixel's value represents its relative distance from the camera
        🔍 Lower values (darker colors) indicate closer objects
        🔭 Higher values (lighter colors) indicate further objects

        The model outputs:
        1. 🗺️ A depth map showing the relative distances of objects in the scene
        2. 📐 The camera's field of view (in degrees)
        3. 🔬 The camera's focal length

        This is particularly useful for:
        - 🏗️ Understanding 3D structure from 2D images
        - 🎨 Creating depth-aware visualizations
        - 📏 Analyzing spatial relationships in scenes
        - 🕶️ Applications in augmented reality and 3D reconstruction

        ⚡ The model runs efficiently on Apple Silicon (M1-M4) using Metal Performance Shaders (MPS) for accelerated inference.

Type identifier

Use the following identifier in step "type" field: roboflow_core/depth_estimation@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
model_version	str	The Depth Estimation model to be used for inference..	❌

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to Depth Estimation in version v1.

• inputs: Crop Visualization, SIFT, Stability AI Image Generation, Triangle Visualization, Blur Visualization, Background Color Visualization, Relative Static Crop, Color Visualization, Image Contours, Camera Focus, Corner Visualization, Line Counter Visualization, Icon Visualization, Mask Visualization, Image Convert Grayscale, Circle Visualization, Image Blur, Pixelate Visualization, Absolute Static Crop, Model Comparison Visualization, Image Threshold, Reference Path Visualization, Image Slicer, Stitch Images, Depth Estimation, Trace Visualization, Image Preprocessing, Classification Label Visualization, Polygon Visualization, Stability AI Outpainting, Keypoint Visualization, Dot Visualization, Grid Visualization, Bounding Box Visualization, Camera Calibration, Polygon Zone Visualization, Ellipse Visualization, QR Code Generator, Halo Visualization, Perspective Correction, Stability AI Inpainting, Image Slicer, SIFT Comparison, Label Visualization, Dynamic Crop
• outputs: QR Code Detection, Anthropic Claude, Crop Visualization, SIFT, LMM For Classification, Blur Visualization, Line Counter Visualization, Color Visualization, Image Contours, Camera Focus, Mask Visualization, Image Convert Grayscale, Google Gemini, Circle Visualization, Absolute Static Crop, VLM as Classifier, Object Detection Model, Multi-Label Classification Model, Keypoint Detection Model, Stitch Images, Trace Visualization, Image Preprocessing, Qwen2.5-VL, OCR Model, Object Detection Model, Clip Comparison, SmolVLM2, Polygon Zone Visualization, LMM, YOLO-World Model, Halo Visualization, CLIP Embedding Model, Florence-2 Model, Moondream2, Perspective Correction, Stability AI Inpainting, Buffer, Template Matching, Label Visualization, VLM as Detector, Pixel Color Count, Segment Anything 2 Model, Perception Encoder Embedding Model, Stability AI Image Generation, Keypoint Detection Model, Triangle Visualization, Background Color Visualization, Relative Static Crop, Detections Stabilizer, Corner Visualization, Multi-Label Classification Model, Icon Visualization, SIFT Comparison, Pixelate Visualization, Image Blur, Gaze Detection, Model Comparison Visualization, VLM as Detector, Llama 3.2 Vision, Time in Zone, Instance Segmentation Model, Image Threshold, VLM as Classifier, Google Vision OCR, Reference Path Visualization, Image Slicer, Roboflow Dataset Upload, CogVLM, Byte Tracker, Barcode Detection, Depth Estimation, Roboflow Dataset Upload, Single-Label Classification Model, OpenAI, Classification Label Visualization, Polygon Visualization, Stability AI Outpainting, Keypoint Visualization, Dot Visualization, OpenAI, Single-Label Classification Model, Bounding Box Visualization, Camera Calibration, Ellipse Visualization, OpenAI, Florence-2 Model, Image Slicer, Instance Segmentation Model, SIFT Comparison, Detections Stitch, Dominant Color, Clip Comparison, Dynamic Crop

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Depth Estimation in version v1 has.

Bindings

• input

  • images (image): The image to infer on..

• output

  • image (image): Image in workflows.
  • normalized_depth (numpy_array): Numpy array.

Example JSON definition of step Depth Estimation in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/depth_estimation@v1",
    "images": "$inputs.image",
    "model_version": "depth-anything-v2/small"
}