Depth Estimation¶
Class: DepthEstimationBlockV1
Source: inference.core.workflows.core_steps.models.foundation.depth_estimation.v1.DepthEstimationBlockV1
π― 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:
π Each pixel's value represents its relative distance from the camera
π Lower values (darker colors) indicate closer objects
π Higher values (lighter colors) indicate further objects
The model outputs:
1. πΊοΈ A depth map showing the relative distances of objects in the scene
2. π The camera's field of view (in degrees)
3. π¬ The camera's focal length
This is particularly useful for:
- ποΈ Understanding 3D structure from 2D images
- π¨ Creating depth-aware visualizations
- π Analyzing spatial relationships in scenes
- πΆοΈ Applications in augmented reality and 3D reconstruction
β‘ 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@v1
to add the block as
as step in your workflow.
Properties¶
Name | Type | Description | Refs |
---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | β |
model_version |
str |
The Depth Estimation model to be used for inference.. | β |
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:
Image Contours
,Stability AI Inpainting
,Mask Visualization
,Corner Visualization
,Keypoint Visualization
,Line Counter Visualization
,Reference Path Visualization
,Circle Visualization
,Absolute Static Crop
,Image Blur
,Relative Static Crop
,Perspective Correction
,Image Convert Grayscale
,Pixelate Visualization
,Model Comparison Visualization
,Triangle Visualization
,Trace Visualization
,Background Color Visualization
,SIFT Comparison
,Camera Calibration
,Depth Estimation
,Label Visualization
,Image Threshold
,Classification Label Visualization
,Blur Visualization
,Color Visualization
,Image Preprocessing
,Bounding Box Visualization
,Ellipse Visualization
,Stability AI Image Generation
,Polygon Zone Visualization
,SIFT
,Grid Visualization
,Camera Focus
,Stitch Images
,Stability AI Outpainting
,Polygon Visualization
,Image Slicer
,Image Slicer
,Dynamic Crop
,Crop Visualization
,Halo Visualization
,Dot Visualization
- outputs:
Image Contours
,Stability AI Inpainting
,Corner Visualization
,Time in Zone
,Google Gemini
,Line Counter Visualization
,Reference Path Visualization
,Keypoint Detection Model
,Florence-2 Model
,YOLO-World Model
,Circle Visualization
,OCR Model
,Llama 3.2 Vision
,SIFT Comparison
,Relative Static Crop
,Roboflow Dataset Upload
,Multi-Label Classification Model
,Image Convert Grayscale
,Pixelate Visualization
,Dominant Color
,Object Detection Model
,Model Comparison Visualization
,Detections Stitch
,Trace Visualization
,LMM
,Roboflow Dataset Upload
,Label Visualization
,Depth Estimation
,Classification Label Visualization
,Perception Encoder Embedding Model
,Blur Visualization
,OpenAI
,Color Visualization
,Moondream2
,Bounding Box Visualization
,Template Matching
,Anthropic Claude
,Pixel Color Count
,Ellipse Visualization
,Instance Segmentation Model
,VLM as Classifier
,Polygon Zone Visualization
,Object Detection Model
,Gaze Detection
,Image Slicer
,Image Slicer
,VLM as Detector
,Crop Visualization
,Perspective Correction
,Halo Visualization
,Dot Visualization
,QR Code Detection
,Mask Visualization
,Keypoint Visualization
,Detections Stabilizer
,SmolVLM2
,Absolute Static Crop
,Clip Comparison
,Image Blur
,OpenAI
,Qwen2.5-VL
,VLM as Classifier
,Clip Comparison
,Instance Segmentation Model
,Triangle Visualization
,Segment Anything 2 Model
,Background Color Visualization
,SIFT Comparison
,CLIP Embedding Model
,Florence-2 Model
,Camera Calibration
,Google Vision OCR
,Image Threshold
,Single-Label Classification Model
,Buffer
,Image Preprocessing
,OpenAI
,CogVLM
,VLM as Detector
,Keypoint Detection Model
,Stability AI Image Generation
,SIFT
,Stitch Images
,Camera Focus
,Stability AI Outpainting
,Polygon Visualization
,Multi-Label Classification Model
,Dynamic Crop
,Barcode Detection
,Byte Tracker
,Single-Label Classification Model
,LMM For Classification
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"
}