| --- |
| pretty_name: "SEA Plant Health Close-Ups" |
| license: other |
| license_name: kled-commercial-training-license |
| license_link: https://www.kled.ai/datasets/plants-close-up |
| task_categories: |
| - image-classification |
| tags: |
| - kled |
| - commercial-license |
| - consented-data |
| - human-collected |
| - sample-on-request |
| - image |
| - real-world-capture |
| - phone-capture |
| - southeast-asia |
| - indonesia |
| - philippines |
| - malaysia |
| - labeled |
| - agriculture |
| - plant-health |
| - camera-original |
| - provenance |
| size_categories: |
| - 10K<n<100K |
| annotations_creators: |
| - crowdsourced |
| language_creators: |
| - crowdsourced |
| source_datasets: |
| - original |
| viewer: false |
| gated: manual |
| extra_gated_heading: "Request a sample set of SEA Plant Health Close-Ups" |
| extra_gated_prompt: "Kled delivers sample sets and licensed data by email, not through Hugging Face. Tell us a little about your work and the Kled data team will send a sample set and pricing. Your request goes to team@kled.ai." |
| extra_gated_fields: |
| Company or lab: text |
| Role: text |
| What are you building: text |
| Volume you need: |
| type: select |
| options: |
| - Sample set only |
| - Under 10,000 items |
| - 10,000 to 100,000 items |
| - 100,000 or more items |
| - Full dataset |
| - Custom collection on the Kled contributor base |
| I agree to be contacted by Kled about this request: checkbox |
| extra_gated_button_content: "Request a sample set" |
| extra_gated_description: "Prefer email? Write to team@kled.ai with the dataset name in the subject line." |
| --- |
| # Dataset Card for SEA Plant Health Close-Ups |
|
|
| <p align="center"><img src="https://knrucgucrxvizxlraxgn.supabase.co/storage/v1/object/public/task-images/v3/67/header-4a4fd785.jpg" alt="SEA Plant Health Close-Ups" width="520"></p> |
|
|
| > Close-ups of healthy and unhealthy plants in 11 Southeast Asian countries, leaf and stem detail, grower's note attached. |
|
|
| Collected through the Kled app by consenting contributors and licensed for commercial training. The files are delivered by Kled under license, not downloaded from this repository. Use **Request a sample set** at the top of this page, or write to [team@kled.ai](mailto:team@kled.ai). Catalog entry: [kled.ai/datasets/plants-close-up](https://www.kled.ai/datasets/plants-close-up?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=plants-close-up). |
|
|
| ## Dataset Details |
|
|
| ### Dataset Description |
|
|
| Find a plant in the prompted condition, healthy or sick, photograph it close enough to show leaf and stem detail, write what you observe. Describe rather than diagnose; never damage a plant for an example; distant shots and off-prompt photos are refused. Collection runs only in 11 Southeast Asian countries, 50 per contributor. Species are not tagged; the observation is a lay description, not an agronomist's diagnosis, a weak label for disease and a strong one for symptoms. Expect what tropical agritech models deploy into: rice, corn, banana, coconut, cassava, market vegetables, garden plants, which big species sets cover thinly; iNaturalist challenge sets are research-only, Pl@ntNet identifies species, and PlantVillage is lab shots of temperate crops. |
|
|
| - **Curated by:** Kled ([useKled](https://huggingface.co/useKled)) |
| - **Collected through:** Phone camera (in app) |
| - **Regions:** Southeast Asia (11 countries) |
| - **Volume:** 50,000+ photos (approx. 150 GB) |
| - **Contributors:** 5,000+ |
| - **Modality:** Images |
| - **Format:** JPG / PNG / HEIC |
| - **Resolution:** Native phone camera resolution (JPG, PNG, HEIC) |
| - **Annotations:** Labeled (observed condition) |
| - **Quality control:** 99%+ passed QA review |
| - **License:** Non-exclusive commercial training license ([terms](https://www.kled.ai/datasets/plants-close-up?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=plants-close-up)); exclusivity available on request |
| - **Consent:** Each contributor opted in to this use when they uploaded. |
|
|
| ### Dataset Sources |
|
|
| - **Catalog page:** [kled.ai/datasets/plants-close-up](https://www.kled.ai/datasets/plants-close-up?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=plants-close-up) |
| - **Sample set:** through the access request at the top of this page, or [team@kled.ai](mailto:team@kled.ai) |
| - **Publisher:** [huggingface.co/useKled](https://huggingface.co/useKled) |
|
|
| ## Uses |
|
|
| ### Direct Use |
|
|
| - Tropical crop disease and symptom recognition |
| - Agritech app fine-tuning |
| - Plant-health VLM evaluation |
|
|
| ### Out-of-Scope Use |
|
|
| Redistribution or resale of the files, use outside the terms of the commercial training license, and any attempt to identify or contact contributors or people who appear in the data. Uses that require labels this set does not carry should be scoped with the data team first. |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| One photo per record, delivered as JPG / PNG / HEIC. Volume: 50,000+ photos. |
|
|
| ### Data Fields |
|
|
| - **File:** the JPG / PNG / HEIC file as captured or uploaded by the contributor |
| - **Labels:** Labeled (observed condition), entered by the contributor at capture and checked at review. |
| - **Capture metadata:** capture tool, country of capture, submission time |
| - **Review status:** QA outcome (99%+ passed QA review) |
|
|
| Field names and the manifest format are confirmed with the sample set. |
|
|
| ### Data Splits |
|
|
| Delivered as one set. Subsets by country, language or label, and custom splits, are available on request. |
|
|
| ## Dataset Creation |
|
|
| ### Curation Rationale |
|
|
| The dataset exists because the public alternatives named in the description are non-commercial, synthetic, small or collected elsewhere. Kled runs the task as a paid brief in its app so that the data is captured on purpose, under the capture rules above, by people who have opted in to commercial use. |
|
|
| ### Source Data |
|
|
| #### Data Collection and Processing |
|
|
| Contributors complete the task in the Kled app. Capture tool: Phone camera (in app). Each submission is reviewed against the task brief; submissions that break the capture rules are rejected. 99%+ passed QA review. Files are delivered as JPG / PNG / HEIC, in the resolution noted above. |
|
|
| #### Who are the source data producers? |
|
|
| Kled contributors, who complete paid data tasks on their own phones. This task was open to contributors in the 11 Southeast Asian countries where the task runs. Kled has 625,000+ contributors in 100+ countries, strongest in Southeast Asia, the United States and Europe. |
|
|
| ### Annotations |
|
|
| #### Annotation process |
|
|
| Labeled (observed condition). The label is entered by the contributor as part of the task and checked at review against the task brief; it is a contributor label, not an expert annotation, unless the description above says otherwise. |
|
|
| #### Who are the annotators? |
|
|
| The contributors themselves, at the moment of capture. Kled reviewers check each submission against the task brief. |
|
|
| #### Personal and Sensitive Information |
|
|
| Every item was contributed by its owner, who opted in to this use at upload. The task brief states what may and may not appear in a submission, and reviewers reject submissions that break those rules. Kled's data handling practices are documented at [trust.kled.ai](https://trust.kled.ai/); questions about handling requirements for your use go to [team@kled.ai](mailto:team@kled.ai). |
|
|
| ## Bias, Risks, and Limitations |
|
|
| Coverage follows the contributor base: strongest in Southeast Asia, the United States and Europe, thinner elsewhere, and limited to the 11 Southeast Asian countries where the task runs for this task. Devices, settings and conditions vary by contributor, which is the point of the collection and also means no two items are captured under identical conditions. Where labels are contributor-entered, they are checked at review but are not expert annotations. Volumes are the current scope of the task and grow as collection continues. |
|
|
| ### Recommendations |
|
|
| Request a sample set and run it against your task before licensing. Ask for per-country or per-language counts where they matter to your use. |
|
|
| ## Licensing Information |
|
|
| Non-exclusive commercial training license; exclusivity on request. Each contributor opted in to this use when they uploaded. The license terms are on the [catalog page](https://www.kled.ai/datasets/plants-close-up?utm_source=huggingface&utm_medium=dataset_card&utm_campaign=plants-close-up). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{kled_plants_close_up_2026, |
| title = {SEA Plant Health Close-Ups}, |
| author = {Kled}, |
| year = {2026}, |
| url = {https://www.kled.ai/datasets/plants-close-up}, |
| note = {Commercially licensed dataset collected through the Kled app. Sample sets on request.} |
| } |
| ``` |
|
|
| ## Dataset Card Contact |
|
|
| Kled data team: [team@kled.ai](mailto:team@kled.ai) |
|
|
| ## Related Kled datasets |
|
|
| - [Six-View Product Photos (10,000 products)](https://huggingface.co/datasets/useKled/all-six-faces-of-one-package) |
| - [Naturally Failed Photos (150,000 photos)](https://huggingface.co/datasets/useKled/bad-photos-you-d-normally-delete) |
| - [SEA Construction Sites (5,000 photos)](https://huggingface.co/datasets/useKled/building-sites) |
| - [Nutrition Label Panels (50,000 photos)](https://huggingface.co/datasets/useKled/food-labels) |
|
|
