Guilherme Martins / Tomato_leaf_disease_detection Public

Target: Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz) Clone this project

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Tomato_leaf_disease_detection

Este projeto utiliza os conceitos de TinyML para identificar doenças presentes em folhas de tomate a partir de fotografias, com intuito de auxiliar no monitoramento agrícola.

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Data (5,991 items)

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c6492dd1-0d2e-4d57-85cc-3544734a8125___UF.GRC_BS_Lab Leaf 8646

ID: 1078050141

Label: bacterial_spot

171b6622-c111-4fe9-b3f9-12b12ee0db06___RS_Erly.B 7836

ID: 1078057003

Label: early_blight

939be2cc-6c00-4205-85cd-5276c12969e0___RS_HL 9883

ID: 1078064954

Label: healthy

f5cb0905-3729-492a-a45f-63c20ae7e6a1___RS_Late.B 6777

ID: 1078071764

Label: late_blight

b3eaae0f-95b4-4bb5-89b5-4460cf79e554___RS_HL 0583

ID: 1078065363

Label: healthy

93725854-5d37-48e9-872d-64c38f0462b1___UF.GRC_BS_Lab Leaf 0940

ID: 1078048797

Label: bacterial_spot

e13e5c45-eab7-4a23-a2bc-3f89fbc7cda6___Matt.S_CG 6879

ID: 1078086623

Label: septoria_leaf_spot

a01034d4-69a1-4a6f-b05a-9561acba2ff2___GHLB2 Leaf 9057

ID: 1078070193

Label: late_blight

Model accuracy (Unoptimized (float32))

Validation set

86.5%

Test set

80.7%

On-device performance (Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz), Quantized (int8))

Latency

1014 ms.

Peak RAM usage

70.9K

Flash usage

85.1K

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Dataset summary

Data collected

5,991 items

Labels

bacterial_spot, early_blight, healthy, late_blight, mosaic_virus, septoria_leaf_spot

Project info

Project ID	439395
License	Apache 2.0
No. of views	57,037
No. of clones	2