Dataset Open Access
Arbash, Elias; Fuchs, Margret; Rasti, Behnood; Lorenz, Sandra; Ghamisi, Pedram; Gloaguen, Richard
{ "doi": "10.14278/rodare.2704", "metadata": { "doc_id": "1", "title": "PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards", "publication_date": "2024-01-29", "access_right_category": "success", "pub_id": "38684", "description": "<p><strong>PCB-Vision Dataset</strong></p>\n\n<p>Description:</p>\n\n<p>The PCB-Vision dataset is a multiscene RGB-Hyperspectral benchmark dataset comprising 53 Printed Circuit Boards (PCBs). The RGB images are collected using a Teledyne Dalsa C4020 camera on a conveyor belt, while hyperspectral images (HSI) are acquired with a Specim FX10 spectrometer. The HSI data contains 224 bands in the VNIR range [400 - 1000]nm.</p>\n\n<p><strong>Data Format</strong></p>\n\n<ul>\n\t<li>RGB Images: .png files</li>\n\t<li>PCB Masks: .jpg files</li>\n\t<li>HSI Data: Each hyperspectral data cube is accompanied by a data file and a .hdr file.</li>\n</ul>\n\n<p><strong>Folder Organization</strong></p>\n\n<ul>\n\t<li>PCBVision\n\t<ul>\n\t\t<li>HSI/\n\t\t<ul>\n\t\t\t<li>53 subfolders (one for each PCB)</li>\n\t\t\t<li>'General_masks' folder for 'General' segmentation ground truth</li>\n\t\t\t<li>'Monoseg_masks' folder for 'Monoseg' segmentation ground truth</li>\n\t\t\t<li>'PCB_Masks' folder for masks of the 53 PCBs in the hyperspectral cube</li>\n\t\t</ul>\n\t\t</li>\n\t\t<li>RGB/\n\t\t<ul>\n\t\t\t<li>53 .jpg images</li>\n\t\t\t<li>'General' folder for RGB images 'General' segmentation ground truth</li>\n\t\t\t<li>'Monoseg_masks' folder for RGB images 'Monoseg' segmentation ground truth</li>\n\t\t</ul>\n\t\t</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p><strong>Data Classes in Masks</strong></p>\n\n<ul>\n\t<li>Masks (both 'General' and 'Monoseg') contain 1 to 4 segmentation classes:\n\t<ul>\n\t\t<li>0: "Others"</li>\n\t\t<li>1: "IC"</li>\n\t\t<li>2: "Capacitors"</li>\n\t\t<li>3: "Connectors"</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p><strong>Code Repository</strong></p>\n\n<p>To facilitate reading and working with the data, Python codes are available on the GitHub repository:</p>\n\n<p>https://github.com/hifexplo/PCBVision</p>\n\n<p><strong>Citation</strong></p>\n\n<p>If you use this dataset, please cite the following article:</p>\n\n<p><strong>Word</strong>:</p>\n\n<p>Arbash, Elias, Fuchs, Margret, Rasti, Behnood, Lorenz, Sandra, Ghamisi, Pedram, & Gloaguen, Richard. (2024). PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards (Version 1) [Data set]. Rodare. <a href=\"http://doi.org/10.14278/rodare.2704\">http://doi.org/10.14278/rodare.2704</a></p>\n\n<p><strong>Latex:</strong></p>\n\n<p>@article{arbash2024pcb, title={PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards}, author={Arbash, Elias and Fuchs, Margret and Rasti, Behnood and Lorenz, Sandra and Ghamisi, Pedram and Gloaguen, Richard}, journal={arXiv preprint arXiv:2401.06528}, year={2024} }</p>\n\n<p><strong>Contact</strong></p>\n\n<p>For further information or inquiries, please visit our website:</p>\n\n<p>https://www.iexplo.space/</p>\n\n<p>Contact Email: e.arbash@hzdr.de</p>", "doi": "10.14278/rodare.2704", "communities": [ { "id": "hzdr" }, { "id": "rodare" } ], "relations": { "version": [ { "count": 1, "is_last": true, "index": 0, "last_child": { "pid_type": "recid", "pid_value": "2704" }, "parent": { "pid_type": "recid", "pid_value": "2703" } } ] }, "keywords": [ "circular economy", "automated data processing", "optical sensors", "recycling", "e-waste", "printed circuit board", "hyperspectral", "dataset", "RGB", "conveyor belt", "sensors", "machine learning", "deep learning", "PCBVision", "open-source data", "digitalization" ], "license": { "id": "CC-BY-4.0" }, "version": "1", "access_right": "open", "related_identifiers": [ { "relation": "isSupplementTo", "identifier": "10.48550/arXiv.2401.06528", "scheme": "doi" }, { "relation": "isIdenticalTo", "identifier": "https://www.hzdr.de/publications/Publ-38684", "scheme": "url" }, { "relation": "isVersionOf", "identifier": "10.14278/rodare.2703", "scheme": "doi" } ], "creators": [ { "name": "Arbash, Elias", "affiliation": "Helmholtz Institute Freiberg for Resource Technology" }, { "orcid": "0000-0001-7210-1132", "name": "Fuchs, Margret", "affiliation": "Helmholtz Institute Freiberg for Resource Technology" }, { "name": "Rasti, Behnood" }, { "orcid": "0000-0001-8464-2331", "name": "Lorenz, Sandra", "affiliation": "Helmholtz Institute Freiberg for Resource Technology" }, { "orcid": "0000-0003-1203-741X", "name": "Ghamisi, Pedram", "affiliation": "Helmholtz Institute Freiberg for Resource Technology" }, { "orcid": "0000-0002-4383-473X", "name": "Gloaguen, Richard", "affiliation": "Helmholtz Institute Freiberg for Resource Technology" } ], "resource_type": { "type": "dataset", "title": "Dataset" } }, "created": "2024-01-29T15:42:20.914128+00:00", "conceptdoi": "10.14278/rodare.2703", "stats": { "volume": 1640505334320.0, "unique_downloads": 54.0, "version_unique_downloads": 54.0, "unique_views": 139.0, "downloads": 144.0, "version_unique_views": 139.0, "version_views": 167.0, "version_downloads": 144.0, "version_volume": 1640505334320.0, "views": 167.0 }, "owners": [ 840 ], "links": { "badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.2704.svg", "doi": "https://doi.org/10.14278/rodare.2704", "conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.2703.svg", "conceptdoi": "https://doi.org/10.14278/rodare.2703", "bucket": "https://rodare.hzdr.de/api/files/671920b9-68a5-4a82-98d1-c696f25e497c", "html": "https://rodare.hzdr.de/record/2704", "latest": "https://rodare.hzdr.de/api/records/2704", "latest_html": "https://rodare.hzdr.de/record/2704" }, "id": 2704, "conceptrecid": "2703", "files": [ { "type": "zip", "size": 11392398155, "checksum": "md5:caeee8bafb7857e9bef3479d5ab3f9b4", "links": { "self": "https://rodare.hzdr.de/api/files/671920b9-68a5-4a82-98d1-c696f25e497c/PCBDataset.zip" }, "bucket": "671920b9-68a5-4a82-98d1-c696f25e497c", "key": "PCBDataset.zip" } ], "revision": 9, "updated": "2024-02-22T11:57:43.528904+00:00" }
All versions | This version | |
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Views | 167 | 167 |
Downloads | 144 | 144 |
Data volume | 1.6 TB | 1.6 TB |
Unique views | 139 | 139 |
Unique downloads | 54 | 54 |