Durian Lens Support
Durian Lens
Durian Lens is an iPhone app that helps you choose durians. After you take or select a photo of a durian, the app provides conservative, explainable buying guidance based only on visible evidence in the image, including the whole-fruit outline, stem, spines, seams, and exterior defects.
Privacy first
- Photo analysis runs entirely on your iPhone and is not sent to the developer’s servers.
- The app requires no account, contains no ads, and does not track users.
- Analysis history is stored only in the app’s private local storage.
See the Privacy Policy for details.
What one photo can—and cannot—show
Durian Lens interprets only exterior evidence visible in the photo, such as signs that may be consistent with splitting, mold, leakage, insect damage, or mechanical damage, plus the visible condition of the stem, spines, and seams. Lighting, occlusion, camera angle, cultivar, and postharvest handling can all affect the assessment. When the available evidence is insufficient, the app recommends another photo.
An ordinary RGB photo cannot directly measure sweetness, dry matter, flesh thickness, number of locules, edible yield, aroma, or tapping sound. Durian Lens does not present information it has not captured as a measurement, and it cannot guarantee what the fruit will be like when opened.
Get a better analysis
- Photograph the durian in bright, even natural light. Avoid filters, strong glare, and deep shadows.
- Capture the whole durian first, keeping the stem, spines, and seams clearly visible.
- If the app reports insufficient evidence, follow its guidance and take a closer photo.
- Treat the result as one reference at the point of purchase, together with seller information, cultivar, and harvest conditions.
Support
For app issues, general feedback, or feature suggestions, email 281928643@qq.com or open an issue on GitHub Issues. Include your iPhone model, iOS version, app version, and steps to reproduce the problem. GitHub Issues is public, so do not post private photos or other sensitive information.