Good photos lead to good AI detections, and bad photos lead to missed defects and false positives. This article covers the practical photo capture techniques that will get you the best results from SuperClear AI. These aren't strict rules — they're proven habits that experienced inspectors have developed for working with computer vision.
The Golden Rules
- Sharp focus — Tap to focus before you take the shot
- Good lighting — Avoid heavy shadows and backlighting
- Get close enough — The WRB should fill most of the frame
- Straight-on angles — Avoid extreme tilts when possible
- One condition per photo — Capture each defect area separately
Stick to these five and you'll dramatically improve your detection accuracy.
Focus
Computer vision models depend on sharp edges and clear textures. A blurry photo can hide defects entirely or trigger the wrong predictions.
- Tap to focus on your phone's camera before tapping the shutter — most cameras let you tap the area of interest to lock focus
- Hold still for a moment after tapping the shutter — moving as you click is the most common cause of blur
- Wait for the autofocus indicator (the box or square) to confirm focus
- If a photo is blurry, retake it — don't try to compensate with editing later
Lighting
Natural light is best
Daylight gives the most consistent, even lighting for inspection photos. Early morning and late afternoon avoid the harsh shadows of midday sun. Overcast days are surprisingly good — soft, even light without strong shadows.
When to use flash
- Indoors with poor lighting
- Behind walls or in shadows where natural light doesn't reach
- Early morning before sunrise or late evening
Be aware that flash can wash out subtle defects and create harsh reflections on shiny surfaces. If you have a choice, natural light wins.
What to avoid
- Backlighting — Don't shoot toward a bright light source. The camera will expose for the bright background and your subject will be too dark.
- Direct overhead sun — Casts hard shadows on textured surfaces
- Mixed lighting — Half of the frame in shadow and half in sunlight makes the AI's job harder
Framing and Distance
Fill the frame
The WRB area you're inspecting should be the main subject of the photo, filling most of the frame. If the area of interest is just a tiny part of a wide shot, the AI may not recognize details. Get closer.
How close is too close?
- Too close — The camera can't focus, or you can only see a small section of fabric without context
- Just right — The defect is clearly visible and you can see the surrounding context (a few inches around the defect)
- Too far — The whole wall fills the frame and the defect is one tiny part
When in doubt, take two photos — one closer and one with more context. You can always delete the one you don't need.
Angle
Capture the WRB straight-on when you can. Heavy angles distort the appearance of seams, fasteners, and tape, and can make a properly installed area look defective. If you can't get straight-on, try a shallow angle (within ~30 degrees of perpendicular).
One Condition Per Photo
Take a separate photo for each defect or area of concern, instead of trying to capture multiple issues in a single wide shot.
Why this matters:
- The AI can mark each photo with its specific findings
- Photo tags work better when each photo represents one condition
- Punch lists are clearer when each finding has its own image
- You can delete or fix individual photos without losing context
Removing Obstructions
- Move scaffolding, ladders, tools, and hands out of the frame when possible
- Wait for workers to step out of the shot
- If something is unavoidable, take a second photo from a different angle that isn't obstructed
Capturing Context
When you find an unusual condition, take both a close-up and a wider context shot:
- Close-up — Shows the defect clearly for AI detection
- Wide shot — Shows where the defect is in the building (helpful for the report reader)
Tag both photos with the same condition so they group together.
Add Metadata While It's Fresh
After uploading, take a few seconds to add building, floor, elevation, and a caption to each photo. The AI doesn't need this metadata to detect defects, but it makes the punch list immediately useful and lets you filter photos later.
- Building — Pick from the project's building options
- Floor — Pick from the project's floor options
- Elevation — North, South, East, or West
- Caption — A short description of what you're seeing
See Managing Photo Tags and Conditions for more on tagging.
Batching Captures
When walking a site, capture all the photos for one area before moving on. This gives you cleaner mental groupings later when you review and tag everything.
When to Re-shoot
If you upload a photo and the AI seems to have missed something or flagged something incorrectly:
- First, check the photo quality — was it sharp? Well-lit? Properly framed?
- If yes, the AI may have legitimately missed a defect. Use the image editor to add your own annotation.
- If the photo quality was poor, retake it with the techniques above and re-upload
Bad Habits to Break
- Snapping without focus — Always tap to focus first
- Zooming in digitally — Move closer instead, digital zoom just crops a smaller area at the same resolution
- Wide panoramic shots of entire walls — Useful for context, useless for AI detection
- Heavy editing before upload — Filters and edits can confuse the AI. Capture the photo as it actually is.
- Mixing multiple defects in one shot — Take separate photos for each finding
Device Tips
- iPhone: Use the standard Camera app settings — "High Efficiency" format is fine
- Android: Most modern Android cameras work well; avoid extreme zoom
- iPad: Excellent for inspection photos — large viewfinder makes framing easier
- Battery and storage: Bring a power bank and check storage before going to a long site visit
Next Steps
- Photo Requirements for AI Detection
- Your First AI Inspection
- Managing Photo Tags and Conditions
- Reviewing AI Detections
Need help? Contact our support team at support@nxtconstruction.ai
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