Global Wheat Full Semantic Organ Segmentation
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- cc-by-4.0
- Source / creator
- GlobalWheat/GWFSS_v1.0
- Collection method
- Images were collected from wheat fields across multiple global sites as part of the Global Wheat initiative, then annotated with pixel-level semantic masks covering full plant organ structure (canopy, leaves, stems, heads, etc.). See the linked paper in Plant Phenomics for full collection protocol, annotator guidance, and quality control procedures applied by the source.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
Preview contains complete records from a bounded prefix of the previous sample; it is not a random sample of the full dataset. Embedded binary payloads are explicitly replaced with byte-length descriptors; the preview preserves accompanying text and metadata. Dataset size is modest (1K-10K images) which limits coverage of all global wheat phenotypes and growth stages. Geographic and seasonal sampling distribution is not documented in the HF card — buyers should consult the paper for site coverage. Source does not document additional gaps; buyers should validate empirically for their target deployment regions and growth stages.
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 6 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 12 of 12 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 12 of 12 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 6 of 6 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| image | 0 / 6 | object | 0 / 6 |
| mask | 0 / 6 | object | 0 / 6 |
About this data
Labelled images for semantic segmentation of wheat plant organs (canopy, leaves, stems, heads) across diverse field conditions. Dataset spans multiple growing regions and environmental settings.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 47cd5023-ae43-4b02-998d-4eda31fb4c25 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| image | STRUCT(bytes BLOB, path VARCHAR) | RGB field photograph of wheat canopy stored as PNG binary with file path reference. |
| mask | STRUCT(bytes BLOB, path VARCHAR) | Pixel-level semantic segmentation mask identifying wheat organs (heads, leaves, stems, canopy) stored as PNG binary with file path reference. |
Sample Data
Preview a sample of the data before downloading.
Public sample only. Sign in to retrieve the full dataset, including free datasets.
For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Global Wheat Full Semantic Org" })
// Found: 47cd5023-ae43-4b02-998d-4eda31fb4c25
get_download_url({ dataset_id: "47cd5023-ae43-4b02-998d-4eda31fb4c25" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/47cd5023-ae43-4b02-998d-4eda31fb4c25/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"