Depth Estimation (DepthAny. V2)

This function block estimates per-pixel depth from a single RGB/BGR image and produces both a colored visualization and a normalized grayscale depth map. It is useful for distance-aware analysis, scene understanding, and augmenting detection pipelines with depth information.

📥 Inputs

Image Provide an RGB/BGR image to estimate depth from.

📤 Outputs

Depth Vis Colored visualization of estimated depth (useful for quick inspection).

Depth Map Normalized grayscale depth map (0–255) that can be used by other blocks for measurements or masking.

🕹️ Controls

Model Size Select model quality/speed trade-off. Typical choices are Small, Base, Large.

Max Size Maximum image dimension used during processing (larger gives more detail but increases processing time and memory).

🎨 Features

• Produces both a human-friendly colored depth visualization and a numeric depth map suitable for further processing.

• Offers selectable model sizes to balance speed vs. accuracy.

• Adjustable processing size to manage memory and frame rate on different machines.

• Works with any image-producing block as input (cameras, files, streams).

⚙️ Running

When the block runs, it processes the latest image provided to the Image input and outputs a visual depth map on Depth Vis and a normalized grayscale depth map on Depth Map. Changing Model Size or reducing Max Size affects processing speed and memory usage; select a smaller model or lower Max Size for faster performance on limited hardware.

📝 Usage Instructions

1. Feed an image source (camera or file) into the Image input.

2. Choose a suitable Model Size depending on available resources and desired accuracy.

3. Tune Max Size to limit the processing resolution; lower values increase speed.

4. Use the Depth Vis output to quickly inspect results and Depth Map for programmatic tasks.

💡 Tips and Tricks

• Use Image Resizer before this block when your input image is very large to reduce memory use and increase throughput.

• Preview results by connecting Depth Vis to Show Image for quick visual checks.

• Save outputs with Image Logger or Image Write when you need recordings of depth maps or visualizations for offline analysis.

• Focus processing on a region of interest with Image ROI to speed up estimation and reduce unnecessary computation.

• Combine with Get Pixel to sample depth values at detected object centers (e.g., read depth at a detected object's coordinates).

• Run object detectors such as Object Detection (D-FINE) or Object Detection - Custom on the RGB image, then consult the Depth Map to filter or sort detections by distance (near vs. far).

• For measurement tasks, pair with Measure Position Distance (use positions obtained from detection or ROI tools) and depth sampling from Depth Map to estimate relative distances more robustly.

🛠️ Troubleshooting

• If processing is too slow or the interface becomes unresponsive, try selecting a smaller Model Size or lowering Max Size.

• If depth visualization looks noisy, try preprocessing the input with Denoising or Blur, or use Image Resizer to match reasonable processing dimensions.

• If results appear inconsistent across frames, ensure consistent lighting and try increasing image quality (better exposure, higher resolution) or use Image Logger to inspect problematic frames.

• If you cannot load the higher quality models on your machine, use Small or Base sizes for reliable performance.