Non-zero of Image

This block returns the total number of non-zero pixels found in an image. It is useful for quick measurements such as foreground pixel count, occupancy checks, or verifying mask coverage.

📥 Inputs

Image Any Provide the image you want to analyze. The block accepts color or grayscale images.

📤 Outputs

Count Total number of non-zero pixels detected in the provided image.

🕹️ Controls

This block has no user-facing controls. It runs automatically when an image is provided.

✨ Features

• Fast single-value result useful for simple analytics and decision making.

• Accepts both color and grayscale images (color images are internally interpreted for pixel activity).

• Works well as a lightweight metric for masks, binary results, or foreground detection.

⚙️ Running mechanism

When the block is evaluated it examines the provided image and counts pixels that are non-zero (i.e., contain useful/foreground information). The result is returned as a single numeric value through the Count output.

📝 Usage

1. Connect an image-producing block to the Image Any input.

2. Read the numeric result from the Count output to drive logic, logging, or alarms.

3. Combine with other blocks for pre-processing, visualization, or decision-making.

💡 Tips and Tricks

• Prepare a clear binary mask before counting by using Image Threshold or Image Adaptive Threshold to reduce false positives from noise.

• Use Image ROI or Image ROI Select to limit the counting area to a region of interest (for localized measurements).

• Reduce noise with Blur, Bilateral Filter or Denoising before counting to avoid inflated results.

• Visualize what is being counted by sending the same image to Show Image or overlay results with Draw Result On Image / Write Text On Image.

• Log numeric results over time using CSV Export or Data to JSON for trend analysis or record keeping.

• Combine with Logic Input or comparison blocks to trigger actions when the count crosses a threshold.

🛠️ Troubleshooting

• Unexpectedly high counts: check for image noise or stray pixels. Apply Image Threshold and smoothing blocks to clean the input.

• Zero or very low counts: confirm the upstream image is valid using Show Image and ensure the area of interest contains the expected foreground.

• Counts vary unexpectedly between frames: restrict the area with Image ROI or stabilize the input using filters to reduce frame-to-frame variation.