Scannet首頁:http://www.scan-net.org/
scannet資料集是一個二維三維資料集,主要采集了室内場景的二維圖像資訊,包括rgb、深度,三維點雲ply資料,并進行了語義标簽和執行個體标簽标注。
完整資料集:一共1513個采集場景資料(每個場景中點雲數量都不一樣,如果要用到端到端可能需要采樣,使每一個場景的點都相同),共21個類别的對象,其中,1201個場景用于訓練,312個場景用于測試。
較小子集:由于2DRGB-D幀的資料量特别大,作者提供了下載下傳較小子集的選項scannet_frames_25k(約25,000幀,從完整資料集中大約每100幀進行二次采樣)通過ScanNet資料下載下傳,有5.6G,還有基準評估scannet_frames_test這個,下圖是下載下傳scannet裡面的
其中scannetV2即第二版本的scannet的結構和檔案類型如下:
<scanId>
|-- <scanId>_vh_clean.ply
(Updated if had remove annotations)
|-- <scanId>_vh_clean_2.ply
(Updated if had remove annotations)
|-- <scanId>.aggregation.json, <scanId>_vh_clean.aggregation.json
Updated aggregated instance-level semantic annotations on lo-res, hi-res meshes, respectively
|-- <scanId>_vh_clean_2.labels.ply
Updated visualization of aggregated semantic segmentation; colored by nyu40 labels (see legend referenced above; ply property 'label' denotes the ScanNet label id)
|-- <scanId>_2d-label.zip
Updated raw 2d projections of aggregated annotation labels as 16-bit pngs with ScanNet label ids
|-- <scanId>_2d-instance.zip
Updated raw 2d projections of aggregated annotation instances as 8-bit pngs
|-- <scanId>_2d-label-filt.zip
Updated filtered 2d projections of aggregated annotation labels as 16-bit pngs with ScanNet label ids
|-- <scanId>_2d-instance-filt.zip
Updated filtered 2d projections of aggregated annotation instances as 8-bit pngs
其中各個檔案的類型還沒有細看,後面再補充。。。
擷取方法:填寫scannet在github上的ScanNet Terms of Use,之後發送郵件,制作團隊會回複一個腳本python檔案,用來下載下傳資料集。
參考文章:
scannet-github
關于ScanNet資料集-老韓Han
scannet資料集-一杯明月