analysis result

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Analysis result

Same dataset, same model ,same library

Fruit dataset MobileNet

Frozen 100 base layer 15Epoch

Model :I use 51 **mobileNetV2 **base layer and classification layer to training. Total 154 base layer.
Traning mathon:10Epoch traning the classification, 5 epoch traning the 54 base layer with classification . fine-tune
Dataset : Fruit360 in kaggle

Chip type	Colab TPU	Colab GPU
model classification training Spend time		644 s
Model 54 base layer with head training spend time		331 s
Train Acceleration		0.9002 = 90.02%
Train loss		0.3169 = 31.69%
Valiation acceleration		0.9368 = 93.68%
Valiation loss		0.4223 = 42.23%
Test acceleration		93.75%

For Detect Result

10 images averaged, every images only one fruit

Type

Computer use tensorflow

Rpi use tensorflow-lite

Condition	Computer	Computer+Coral	Rpi	Rpi + Coral
Speed	-	2.5ms	-	3.8ms
Accuracy	86.52%	72.93%	84.23%	71.52%

GPU Curve

only train classification head acc and loss
10 Epoch
Cross Entropy = Loss

curve

Continue training 5 Epoch for 54 base layer of MobileNetV2 with classification head

curve2

请我喝杯咖啡吧~