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int64
0
8.47k
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320
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200
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299
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300
600
423
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305
320
240
{ "id": [ 305 ], "area": [ 46760 ], "bbox": [ [ 38, 44, 280, 167 ] ], "category": [ "Tomato Early blight leaf" ] }
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275
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351
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369
1,024
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{ "id": [ 369 ], "area": [ 109052 ], "bbox": [ [ 50, 117, 548, 199 ] ], "category": [ "Peach leaf" ] }
370
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374
1,200
630
{ "id": [ 374 ], "area": [ 333477 ], "bbox": [ [ 300, 9, 537, 621 ] ], "category": [ "Corn Gray leaf spot" ] }
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405
393
{ "id": [ 375, 376, 377, 378, 379 ], "area": [ 2747, 5670, 9483, 6004, 7597 ], "bbox": [ [ 243, 297, 67, 41 ], [ 322, 8, 70, 81 ], [ 32, 36, 109, 87 ], [ 50, ...
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1,008
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End of preview. Expand in Data Studio

This Dataset is created from processing the files from this GitHub repository : PlantDoc-Object-Detection-Dataset

@inproceedings{10.1145/3371158.3371196, author = {Singh, Davinder and Jain, Naman and Jain, Pranjali and Kayal, Pratik and Kumawat, Sudhakar and Batra, Nipun}, title = {PlantDoc: A Dataset for Visual Plant Disease Detection}, year = {2020}, isbn = {9781450377386}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3371158.3371196}, doi = {10.1145/3371158.3371196}, booktitle = {Proceedings of the 7th ACM IKDD CoDS and 25th COMAD}, pages = {249–253}, numpages = {5}, keywords = {Deep Learning, Object Detection, Image Classification}, location = {Hyderabad, India}, series = {CoDS COMAD 2020} }

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