Most welders don't think about what's happening behind the screen when they upload a photo to an AI welding app. The truth is fascinating, and it explains why AI is so good at finding defects that the human eye might miss.
When you upload a weld photo, it doesn't stay as an image. The AI converts it into a grid of pixels. A standard photo might be 1920 x 1080 pixels - that's over 2 million individual data points the AI can analyze.
Each pixel contains:
This is where it gets interesting. The AI doesn't just see "something wrong" - it knows exactly where:
X coordinate: Horizontal position (left to right)
Y coordinate: Vertical position (top to bottom)
When DimeVision detects a defect, it reports something like:
Porosity
That's radically more precise than "your bead looks messy."
Here's how the AI analyzes each pixel group:
Dark spots in the weld metal. The AI looks for circular or irregular dark patterns that differ from the surrounding weld color.
Grooves at the weld toe. The AI detects color discontinuities - places where the weld doesn't fully fill the joint.
Irregular metal particles outside the weld. The AI identifies scattered bright spots that don't match the expected pattern.
Where the weld didn't fully penetrate. The AI looks for boundary inconsistencies where the weld metal didn't fuse with the base metal.
For each detected defect, the AI draws a "bounding box" - a rectangle around the problem area. Each box comes with a confidence level, which is how sure that one callout is. DimeVision does not rate the bead.
When confidence is high, the callout is a likely visible issue. When confidence is low, treat it as a possible issue and check the bead yourself.
Traditional feedback is vague:
AI feedback is precise:
As camera technology improves and AI models get better, we'll see real-time video analysis. Point your phone at a weld in progress and get feedback before you finish the bead.
That's the future DimeVision is building toward.
Get DimeVision on the App Store