This guide walks users through how to identify and understand photo validation failures flagged by AI during project review.
🧠 What is AI Photo Validation?
AI Photo Validation is a feature that helps automatically detect and flag photos that don’t meet quality or content requirements, as defined in a template. This allows teams to quickly identify which images need attention, saving time and improving accuracy.
🔧 Step 1: Template Setup (Admin Only)
⚠️ This step is completed by a Portal Admin and is covered in a separate setup guide.
- An Admin User uses the Template Editor to configure a specific field with one or more AI-based validation checks.
- The validations and validation meta data are saved with the template.
📤 Step 2: Project Completion and AI Processing
Once a project is completed using a template with photo validations:
- The project is submitted as usual.
- Photos from fields with configured validations are automatically sent to Image AI for analysis.
- AI runs checks based on the validation rules defined in the template.
👀 Step 3: Reviewing Failed Photos in the Photo Viewer
When a user opens the Photo Viewer in a completed project:
🔹 Thumbnail Indicators
- Any photo that fails validation will display a red warning icon overlay on its thumbnail.
- This helps you quickly spot which images need attention without opening each one.
🔹 Tooltip on Hover
- Hovering your mouse over a thumbnail; directly over the failed validation icon will display a tooltip pop-up.
- The tooltip explains the reason for the failure — for example in the screen show below:
🖼 Step 4: Viewing Details of Image Analysis Results
Clicking a photo or video thumbnail opens it in full view.
📋 Right Sidebar: AI Metadata
- In the right-hand column, alongside other AI metadata, you’ll see a section labeled:
- This section lists:
- Category
- Caption
- Tags
- Description
- Failed Validations (Eg: Instruction, Object, Proximity, etc)
Example of a Failed Photo Instruction Validation:
📝 Example Use Case (with Object Validation)
Imagine you're reviewing a roof inspection project. The field for “Roof Condition” is configured with the following requirements:
- ✅ Object Validation: Roof must be present and detectable in the image
During review:
You notice two thumbnail images with a red warning icon:
Clicking one of the images opens it in the viewer, where the right-hand metadata panel displays an error message:
Object Validation Failed The object 'roof' was not found in the image.
This indicates that the AI-driven object validation could not identify a roof in the image, possibly due to poor angle, obstruction, or the photo being unrelated.
This helps you quickly flag or replace invalid content, ensuring your inspection reports maintain accuracy and completeness.
💡 Tips
- Use the validation icons as a triage tool before deeper photo review.
- You can still manually override or add comments to explain or justify failed photos, if applicable.
- Make sure your project teams understand what each validation rule is checking.
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