AgriGround Annotations

AgriGround contains 11,421,148 Stage 4 instruction-tuning records across 503,919 source images and 14 tasks.

Split	Source images	Annotation records
Train	401,234	9,095,320
Test	102,685	2,325,828
Total	503,919	11,421,148

Layout

The train/ and test/ directories are grouped by source family and dataset. Each leaf directory contains a gzip-compressed stage4.jsonl.gz file. manifest.json provides row counts, task counts, compressed sizes, and SHA-256 checksums for every file. validation.json records the full-release integrity and schema validation result.

Record Format

Each line is one JSON object with these common fields:

image_path: path of the image in its source dataset
task_type: machine-readable task identifier
question_type: human-readable task identifier
question: model instruction or question
answer: target response

Task-dependent fields include COCO-style RLE masks, normalized [x, y, width, height] bounding boxes, object counts, grounded phrases, regions, and multi-turn conversations. The 14 task definitions and exact distribution are listed in docs/TASKS.md.

Loading

import gzip
import json

with gzip.open("annotations/train/classification/banana_leaf_disease_classification/stage4.jsonl.gz", "rt", encoding="utf-8") as stream:
    for line in stream:
        record = json.loads(line)
        print(record["task_type"], record["question"], record["answer"])
        break

Source images are not included. Resolve each image_path against the corresponding source dataset and follow that dataset's original license and usage terms.