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Testaroo

Explore the test library

Find files, editable templates and browser test targets by what you need to make or test. The directory below is cut by format; the two collections under it cut the same library by subject and by workflow.

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Preview of Detection Annotations: COCO (JSON)
json
1 KB
Actual file preview for Detection Annotations: COCO (JSON)

Detection Annotations: COCO (JSON)

Object-detection annotations for the scene in the COCO JSON format: images, categories, and per-object bounding boxes as [x, y, width, height]. Grouped with YOLO and Pascal-VOC twins for testing annotation-format conversion.

File
JSON · Vision
Use case
Computer visionML training data+2· Conversion set
Preview of Detection Annotations: Pascal VOC (XML)
xml
1 KB
Actual file preview for Detection Annotations: Pascal VOC (XML)

Detection Annotations: Pascal VOC (XML)

The same detection boxes in the Pascal VOC XML format: a per-image annotation with size, and one object element per box with pixel corner coordinates. The XML twin of the COCO and YOLO annotations.

File
XML · Vision
Use case
Computer visionML training data+1· Conversion set
Preview of Detection Annotations: YOLO (TXT)
txt
117 B
Actual file preview for Detection Annotations: YOLO (TXT)

Detection Annotations: YOLO (TXT)

The same detection boxes in the YOLO text format: one object per line as class id and box centre, width, and height normalised to 0–1. The format twin of the COCO and VOC annotations.

File
TXT · Vision
Use case
Computer visionML training data+1· Conversion set
Preview of Detection Class List (TXT)
txt
19 B
Actual file preview for Detection Class List (TXT)

Detection Class List (TXT)

The class-name list for the detection scene, one label per line: index equals the zero-based line number, matching the YOLO class ids. A companion to the COCO/YOLO/VOC annotation files.

File
TXT · Vision
Preview of Extractive QA Dataset: SQuAD v2 Format (JSON)
json
2.2 KB
Actual file preview for Extractive QA Dataset: SQuAD v2 Format (JSON)

Extractive QA Dataset: SQuAD v2 Format (JSON)

An extractive question-answering dataset in the SQuAD v2.0 JSON structure, titled articles with context paragraphs, questions, character-offset answers, and one deliberately unanswerable question. Synthetic content; a fixture for QA model training and SQuAD-format loaders.

File
JSON · Nlp