Display interface for manual inspection
The Display module provides an interactive web-based dashboard for visualizing and analyzing image data using Dash and Bootstrap components.
Key Features
- Interactive File Explorer: Dropdown interface to select images from a dictionary
- Image Display: Real-time image preview in the dashboard
- Multi-Detector Support: Run different analysis detectors:
- TextDetector (text extraction and translation)
- ColorDetector (color analysis)
- VQA (Visual Question Answering with image summaries)
- Dynamic Settings: Context-aware settings panels that appear based on selected detector
- Real-time Analysis: Execute analysis on selected images with loading indicators
- Results Visualization: JSON-style table display of analysis results
- Customizable Questions: Text area for entering custom VQA questions (one per line)
- Privacy Controls: Environment variable configuration for privacy disclosure acceptance
Usage
from ammico.display import AnalysisExplorer
explorer = AnalysisExplorer(mydict=image_dict)
explorer.run_server(port=8050)
Features
- TextDetector Settings: Privacy disclosure environment variable configuration
- ColorDetector Settings: Delta-E method selection dropdown
- VQA Settings:
- Analysis type selection (summary, questions, or both)
- Custom questions textarea (shown/hidden based on analysis type)
- Model selection (base/large)
Output
Displays analysis results in an interactive table format, showing all extracted features and metadata for the selected image.
Workflow
flowchart TD
Start([Initialize AnalysisExplorer]) --> RunServer[Explorer.run_server]
RunServer --> Dashboard[Dash Dashboard Loaded]
subgraph Dashboard Interaction
Dashboard --> SelectImg{Select Image}
SelectImg --> UpdatePic[Update Picture View]
Dashboard --> SelectDet{Select Detector}
SelectDet --> UpdateSet[Update Settings Panel]
UpdateSet --> Settings{Adjust Settings}
Settings --> ClickRun{Click Run Detector}
ClickRun --> CheckDet[Check Selected Detector]
end
CheckDet -- TextDetector --> TextDet[Init TextDetector]
CheckDet -- ColorDetector --> ColorDet[Init ColorDetector]
CheckDet -- VQA --> VQADet[Init ImageSummaryDetector]
TextDet --> RunMeasure[Run analyse_image]
ColorDet --> RunMeasure
VQADet --> RunMeasure
RunMeasure --> Format[Format Output as Table]
Format --> UpdateTable[Update JSON Viewer]
UpdateTable --> Dashboard