Field Image Processing Requirements
- Matthew Kutugata
Target release | Jun 30, 2024 Type // to add a target release date |
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Document status | DRAFT |
Document owner | @Matthew Kutugata |
Tech lead | @Matthew Kutugata @Boscosylvester John (Unlicensed) |
Technical writers | @Navjot Singh |
QA | @Maria Laura Cangiano |
Goal and Objectives
The primary goal is to extract detailed vegetation segments from field images. These images include additional tools like gray mats and color cards to enhance the accuracy of segmentation. The segments extracted are intended to be used directly for detailed analysis or to create synthetic image data, facilitating diverse machine learning tasks.
Report on the current status of the dataset
Process Backlog
Continuously Monitor and Process
Images Sample Examples
Weeds
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Cover crops
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Cash Crops
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Key Features
Feature | Description |
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Reporting |
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Color correction |
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Semi-Automatic |
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image quality classification |
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Verify label accuracy |
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Validation
Timeline
Outputs
ID | Requirement | Category | Description | Format | Notes |
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A.1 | weed semantic mask | dataset |
| PNG |
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A.2 | cover crop semantic mask | dataset |
| PNG |
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A.3 | cash crop semantic mask | dataset |
| PNG |
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A.4 | bounding box detection | dataset |
| JSON key/value pair | identify format (consider yolo) |
A.5 | Metadata | dataset | contains various metadata | JSON |
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B.5 | Report | Monitoring |
| PNG/CSV |
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A.6 | image content tags | dataset | tags in metadata for whether the image contains a gray mat, color correction card, or has a plain background | JSON key/value pair |
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Open Questions
Question | Answer | Date Answered |
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