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YAML Metadata Warning:The task_categories "image-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
SRTM 30m OZT2 Elevation Tiles
This dataset contains SRTM 30-meter resolution elevation data encoded in the OZT2 tile format.
Format
OZT2 is a high-performance elevation tile format:
- Compression: ~93% smaller than Terrarium PNG
- Prediction: Gradient-based prediction (left neighbor + vertical gradient)
- Quantization: Adaptive bit-depth (8/10/12/16-bit per channel)
- Codec: Zstd q3 (30× faster encode than Brotli, same decode speed)
Each tile is 256×256 pixels in Web Mercator projection (EPSG:3857).
Usage
from huggingface_hub import HfFileSystem
from openzenith import decode_v2
fs = HfFileSystem(repo_id="aliasfox/srtm30m-ozt2-v2")
with fs.open("tiles/z10/163/395.ozt2", "rb") as f:
data = f.read()
elevation, meta = decode_v2(data)
Source
Source: SRTM 30m via aliasfox/srtm30m-merged
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