/Tomato-Leaf-Disease-Detection

A Neural Network which uses Transfer Learning technique using pre-trained model of InceptionV3 to detect different type of diseases for tomato leaves.

Primary LanguageJupyter Notebook

Tomato Leaf Disease Detection

A Neural Network which uses Transfer Learning technique using pre-trained model of InceptionV3 to detect different type of diseases for tomato leaves.

Dataset - Tomato Leaf Disease Detection

This dataset consists of 11K files of training and validation data of different types of diseases for tomato leaves. It contains 18390 images belonging to 10 classes of training data and 4585 images belonging to 10 classes of validation data. The types of tomato leaf diseases the neural network can detect are: Tomato mosaic virus, Target Spot, Bacterial spot, Tomato Yellow Leaf Curl Virus, Late blight, Leaf Mold, Early blight, Spidermites Two spotted spider mite, Tomato healthy, Septoria leaf spot,

Tomato Leaf Diseases Dataset Classes

3c182852-8b72-465a-ad91-a031d9d725f5___UF GRC_BS_Lab Leaf 0411 0e2e58b7-1417-49c4-b014-b5efb4b4b831___RS_Erly B 8256 00bce074-967b-4d50-967a-31fdaa35e688___RS_HL 0223 0c47de5b-adbe-479f-8ccf-5b8c530c32f8___RS_Late B 6312 1bfe7244-44ab-4fac-abe5-f229217cdf0b___Crnl_L Mold 6815 0c48052c-232b-4ea7-b77d-322f5f642612___Matt S_CG 7724 0ac9558f-1e02-4498-9584-887627587bc0___Com G_SpM_FL 1148 0b126ce6-af82-477f-8f4e-1de79d84a6dd___Com G_TgS_FL 8294_new30degFlipLR 0d9accf3-1285-4356-b69b-2ae132c5f145___PSU_CG 2337 15553f35-1de9-4218-8472-6382d2c69597___UF GRC_YLCV_Lab 01809

Model Summary

Model: "model"


Layer (type) Output Shape Param # Connected to

================================================================================================== input_1 (InputLayer) [(None, 224, 224, 3) 0


conv2d (Conv2D) (None, 111, 111, 32) 864 input_1[0][0]


batch_normalization (BatchNorma (None, 111, 111, 32) 96 conv2d[0][0]


activation (Activation) (None, 111, 111, 32) 0 batch_normalization[0][0]


conv2d_1 (Conv2D) (None, 109, 109, 32) 9216 activation[0][0]


batch_normalization_1 (BatchNor (None, 109, 109, 32) 96 conv2d_1[0][0]


activation_1 (Activation) (None, 109, 109, 32) 0 batch_normalization_1[0][0]


conv2d_2 (Conv2D) (None, 109, 109, 64) 18432 activation_1[0][0]


batch_normalization_2 (BatchNor (None, 109, 109, 64) 192 conv2d_2[0][0]


activation_2 (Activation) (None, 109, 109, 64) 0 batch_normalization_2[0][0]


max_pooling2d (MaxPooling2D) (None, 54, 54, 64) 0 activation_2[0][0]


conv2d_3 (Conv2D) (None, 54, 54, 80) 5120 max_pooling2d[0][0]


batch_normalization_3 (BatchNor (None, 54, 54, 80) 240 conv2d_3[0][0]


activation_3 (Activation) (None, 54, 54, 80) 0 batch_normalization_3[0][0]


conv2d_4 (Conv2D) (None, 52, 52, 192) 138240 activation_3[0][0]


batch_normalization_4 (BatchNor (None, 52, 52, 192) 576 conv2d_4[0][0]


activation_4 (Activation) (None, 52, 52, 192) 0 batch_normalization_4[0][0]


max_pooling2d_1 (MaxPooling2D) (None, 25, 25, 192) 0 activation_4[0][0]


conv2d_8 (Conv2D) (None, 25, 25, 64) 12288 max_pooling2d_1[0][0]


batch_normalization_8 (BatchNor (None, 25, 25, 64) 192 conv2d_8[0][0]


activation_8 (Activation) (None, 25, 25, 64) 0 batch_normalization_8[0][0]


conv2d_6 (Conv2D) (None, 25, 25, 48) 9216 max_pooling2d_1[0][0]


conv2d_9 (Conv2D) (None, 25, 25, 96) 55296 activation_8[0][0]


batch_normalization_6 (BatchNor (None, 25, 25, 48) 144 conv2d_6[0][0]


batch_normalization_9 (BatchNor (None, 25, 25, 96) 288 conv2d_9[0][0]


activation_6 (Activation) (None, 25, 25, 48) 0 batch_normalization_6[0][0]


activation_9 (Activation) (None, 25, 25, 96) 0 batch_normalization_9[0][0]


average_pooling2d (AveragePooli (None, 25, 25, 192) 0 max_pooling2d_1[0][0]


conv2d_5 (Conv2D) (None, 25, 25, 64) 12288 max_pooling2d_1[0][0]


conv2d_7 (Conv2D) (None, 25, 25, 64) 76800 activation_6[0][0]


conv2d_10 (Conv2D) (None, 25, 25, 96) 82944 activation_9[0][0]


conv2d_11 (Conv2D) (None, 25, 25, 32) 6144 average_pooling2d[0][0]


batch_normalization_5 (BatchNor (None, 25, 25, 64) 192 conv2d_5[0][0]


batch_normalization_7 (BatchNor (None, 25, 25, 64) 192 conv2d_7[0][0]


batch_normalization_10 (BatchNo (None, 25, 25, 96) 288 conv2d_10[0][0]


batch_normalization_11 (BatchNo (None, 25, 25, 32) 96 conv2d_11[0][0]


activation_5 (Activation) (None, 25, 25, 64) 0 batch_normalization_5[0][0]


activation_7 (Activation) (None, 25, 25, 64) 0 batch_normalization_7[0][0]


activation_10 (Activation) (None, 25, 25, 96) 0 batch_normalization_10[0][0]


activation_11 (Activation) (None, 25, 25, 32) 0 batch_normalization_11[0][0]


mixed0 (Concatenate) (None, 25, 25, 256) 0 activation_5[0][0]
activation_7[0][0]
activation_10[0][0]
activation_11[0][0]


conv2d_15 (Conv2D) (None, 25, 25, 64) 16384 mixed0[0][0]


batch_normalization_15 (BatchNo (None, 25, 25, 64) 192 conv2d_15[0][0]


activation_15 (Activation) (None, 25, 25, 64) 0 batch_normalization_15[0][0]


conv2d_13 (Conv2D) (None, 25, 25, 48) 12288 mixed0[0][0]


conv2d_16 (Conv2D) (None, 25, 25, 96) 55296 activation_15[0][0]


batch_normalization_13 (BatchNo (None, 25, 25, 48) 144 conv2d_13[0][0]


batch_normalization_16 (BatchNo (None, 25, 25, 96) 288 conv2d_16[0][0]


activation_13 (Activation) (None, 25, 25, 48) 0 batch_normalization_13[0][0]


activation_16 (Activation) (None, 25, 25, 96) 0 batch_normalization_16[0][0]


average_pooling2d_1 (AveragePoo (None, 25, 25, 256) 0 mixed0[0][0]


conv2d_12 (Conv2D) (None, 25, 25, 64) 16384 mixed0[0][0]


conv2d_14 (Conv2D) (None, 25, 25, 64) 76800 activation_13[0][0]


conv2d_17 (Conv2D) (None, 25, 25, 96) 82944 activation_16[0][0]


conv2d_18 (Conv2D) (None, 25, 25, 64) 16384 average_pooling2d_1[0][0]


batch_normalization_12 (BatchNo (None, 25, 25, 64) 192 conv2d_12[0][0]


batch_normalization_14 (BatchNo (None, 25, 25, 64) 192 conv2d_14[0][0]


batch_normalization_17 (BatchNo (None, 25, 25, 96) 288 conv2d_17[0][0]


batch_normalization_18 (BatchNo (None, 25, 25, 64) 192 conv2d_18[0][0]


activation_12 (Activation) (None, 25, 25, 64) 0 batch_normalization_12[0][0]


activation_14 (Activation) (None, 25, 25, 64) 0 batch_normalization_14[0][0]


activation_17 (Activation) (None, 25, 25, 96) 0 batch_normalization_17[0][0]


activation_18 (Activation) (None, 25, 25, 64) 0 batch_normalization_18[0][0]


mixed1 (Concatenate) (None, 25, 25, 288) 0 activation_12[0][0]
activation_14[0][0]
activation_17[0][0]
activation_18[0][0]


conv2d_22 (Conv2D) (None, 25, 25, 64) 18432 mixed1[0][0]


batch_normalization_22 (BatchNo (None, 25, 25, 64) 192 conv2d_22[0][0]


activation_22 (Activation) (None, 25, 25, 64) 0 batch_normalization_22[0][0]


conv2d_20 (Conv2D) (None, 25, 25, 48) 13824 mixed1[0][0]


conv2d_23 (Conv2D) (None, 25, 25, 96) 55296 activation_22[0][0]


batch_normalization_20 (BatchNo (None, 25, 25, 48) 144 conv2d_20[0][0]


batch_normalization_23 (BatchNo (None, 25, 25, 96) 288 conv2d_23[0][0]


activation_20 (Activation) (None, 25, 25, 48) 0 batch_normalization_20[0][0]


activation_23 (Activation) (None, 25, 25, 96) 0 batch_normalization_23[0][0]


average_pooling2d_2 (AveragePoo (None, 25, 25, 288) 0 mixed1[0][0]


conv2d_19 (Conv2D) (None, 25, 25, 64) 18432 mixed1[0][0]


conv2d_21 (Conv2D) (None, 25, 25, 64) 76800 activation_20[0][0]


conv2d_24 (Conv2D) (None, 25, 25, 96) 82944 activation_23[0][0]


conv2d_25 (Conv2D) (None, 25, 25, 64) 18432 average_pooling2d_2[0][0]


batch_normalization_19 (BatchNo (None, 25, 25, 64) 192 conv2d_19[0][0]


batch_normalization_21 (BatchNo (None, 25, 25, 64) 192 conv2d_21[0][0]


batch_normalization_24 (BatchNo (None, 25, 25, 96) 288 conv2d_24[0][0]


batch_normalization_25 (BatchNo (None, 25, 25, 64) 192 conv2d_25[0][0]


activation_19 (Activation) (None, 25, 25, 64) 0 batch_normalization_19[0][0]


activation_21 (Activation) (None, 25, 25, 64) 0 batch_normalization_21[0][0]


activation_24 (Activation) (None, 25, 25, 96) 0 batch_normalization_24[0][0]


activation_25 (Activation) (None, 25, 25, 64) 0 batch_normalization_25[0][0]


mixed2 (Concatenate) (None, 25, 25, 288) 0 activation_19[0][0]
activation_21[0][0]
activation_24[0][0]
activation_25[0][0]


conv2d_27 (Conv2D) (None, 25, 25, 64) 18432 mixed2[0][0]


batch_normalization_27 (BatchNo (None, 25, 25, 64) 192 conv2d_27[0][0]


activation_27 (Activation) (None, 25, 25, 64) 0 batch_normalization_27[0][0]


conv2d_28 (Conv2D) (None, 25, 25, 96) 55296 activation_27[0][0]


batch_normalization_28 (BatchNo (None, 25, 25, 96) 288 conv2d_28[0][0]


activation_28 (Activation) (None, 25, 25, 96) 0 batch_normalization_28[0][0]


conv2d_26 (Conv2D) (None, 12, 12, 384) 995328 mixed2[0][0]


conv2d_29 (Conv2D) (None, 12, 12, 96) 82944 activation_28[0][0]


batch_normalization_26 (BatchNo (None, 12, 12, 384) 1152 conv2d_26[0][0]


batch_normalization_29 (BatchNo (None, 12, 12, 96) 288 conv2d_29[0][0]


activation_26 (Activation) (None, 12, 12, 384) 0 batch_normalization_26[0][0]


activation_29 (Activation) (None, 12, 12, 96) 0 batch_normalization_29[0][0]


max_pooling2d_2 (MaxPooling2D) (None, 12, 12, 288) 0 mixed2[0][0]


mixed3 (Concatenate) (None, 12, 12, 768) 0 activation_26[0][0]
activation_29[0][0]
max_pooling2d_2[0][0]


conv2d_34 (Conv2D) (None, 12, 12, 128) 98304 mixed3[0][0]


batch_normalization_34 (BatchNo (None, 12, 12, 128) 384 conv2d_34[0][0]


activation_34 (Activation) (None, 12, 12, 128) 0 batch_normalization_34[0][0]


conv2d_35 (Conv2D) (None, 12, 12, 128) 114688 activation_34[0][0]


batch_normalization_35 (BatchNo (None, 12, 12, 128) 384 conv2d_35[0][0]


activation_35 (Activation) (None, 12, 12, 128) 0 batch_normalization_35[0][0]


conv2d_31 (Conv2D) (None, 12, 12, 128) 98304 mixed3[0][0]


conv2d_36 (Conv2D) (None, 12, 12, 128) 114688 activation_35[0][0]


batch_normalization_31 (BatchNo (None, 12, 12, 128) 384 conv2d_31[0][0]


batch_normalization_36 (BatchNo (None, 12, 12, 128) 384 conv2d_36[0][0]


activation_31 (Activation) (None, 12, 12, 128) 0 batch_normalization_31[0][0]


activation_36 (Activation) (None, 12, 12, 128) 0 batch_normalization_36[0][0]


conv2d_32 (Conv2D) (None, 12, 12, 128) 114688 activation_31[0][0]


conv2d_37 (Conv2D) (None, 12, 12, 128) 114688 activation_36[0][0]


batch_normalization_32 (BatchNo (None, 12, 12, 128) 384 conv2d_32[0][0]


batch_normalization_37 (BatchNo (None, 12, 12, 128) 384 conv2d_37[0][0]


activation_32 (Activation) (None, 12, 12, 128) 0 batch_normalization_32[0][0]


activation_37 (Activation) (None, 12, 12, 128) 0 batch_normalization_37[0][0]


average_pooling2d_3 (AveragePoo (None, 12, 12, 768) 0 mixed3[0][0]


conv2d_30 (Conv2D) (None, 12, 12, 192) 147456 mixed3[0][0]


conv2d_33 (Conv2D) (None, 12, 12, 192) 172032 activation_32[0][0]


conv2d_38 (Conv2D) (None, 12, 12, 192) 172032 activation_37[0][0]


conv2d_39 (Conv2D) (None, 12, 12, 192) 147456 average_pooling2d_3[0][0]


batch_normalization_30 (BatchNo (None, 12, 12, 192) 576 conv2d_30[0][0]


batch_normalization_33 (BatchNo (None, 12, 12, 192) 576 conv2d_33[0][0]


batch_normalization_38 (BatchNo (None, 12, 12, 192) 576 conv2d_38[0][0]


batch_normalization_39 (BatchNo (None, 12, 12, 192) 576 conv2d_39[0][0]


activation_30 (Activation) (None, 12, 12, 192) 0 batch_normalization_30[0][0]


activation_33 (Activation) (None, 12, 12, 192) 0 batch_normalization_33[0][0]


activation_38 (Activation) (None, 12, 12, 192) 0 batch_normalization_38[0][0]


activation_39 (Activation) (None, 12, 12, 192) 0 batch_normalization_39[0][0]


mixed4 (Concatenate) (None, 12, 12, 768) 0 activation_30[0][0]
activation_33[0][0]
activation_38[0][0]
activation_39[0][0]


conv2d_44 (Conv2D) (None, 12, 12, 160) 122880 mixed4[0][0]


batch_normalization_44 (BatchNo (None, 12, 12, 160) 480 conv2d_44[0][0]


activation_44 (Activation) (None, 12, 12, 160) 0 batch_normalization_44[0][0]


conv2d_45 (Conv2D) (None, 12, 12, 160) 179200 activation_44[0][0]


batch_normalization_45 (BatchNo (None, 12, 12, 160) 480 conv2d_45[0][0]


activation_45 (Activation) (None, 12, 12, 160) 0 batch_normalization_45[0][0]


conv2d_41 (Conv2D) (None, 12, 12, 160) 122880 mixed4[0][0]


conv2d_46 (Conv2D) (None, 12, 12, 160) 179200 activation_45[0][0]


batch_normalization_41 (BatchNo (None, 12, 12, 160) 480 conv2d_41[0][0]


batch_normalization_46 (BatchNo (None, 12, 12, 160) 480 conv2d_46[0][0]


activation_41 (Activation) (None, 12, 12, 160) 0 batch_normalization_41[0][0]


activation_46 (Activation) (None, 12, 12, 160) 0 batch_normalization_46[0][0]


conv2d_42 (Conv2D) (None, 12, 12, 160) 179200 activation_41[0][0]


conv2d_47 (Conv2D) (None, 12, 12, 160) 179200 activation_46[0][0]


batch_normalization_42 (BatchNo (None, 12, 12, 160) 480 conv2d_42[0][0]


batch_normalization_47 (BatchNo (None, 12, 12, 160) 480 conv2d_47[0][0]


activation_42 (Activation) (None, 12, 12, 160) 0 batch_normalization_42[0][0]


activation_47 (Activation) (None, 12, 12, 160) 0 batch_normalization_47[0][0]


average_pooling2d_4 (AveragePoo (None, 12, 12, 768) 0 mixed4[0][0]


conv2d_40 (Conv2D) (None, 12, 12, 192) 147456 mixed4[0][0]


conv2d_43 (Conv2D) (None, 12, 12, 192) 215040 activation_42[0][0]


conv2d_48 (Conv2D) (None, 12, 12, 192) 215040 activation_47[0][0]


conv2d_49 (Conv2D) (None, 12, 12, 192) 147456 average_pooling2d_4[0][0]


batch_normalization_40 (BatchNo (None, 12, 12, 192) 576 conv2d_40[0][0]


batch_normalization_43 (BatchNo (None, 12, 12, 192) 576 conv2d_43[0][0]


batch_normalization_48 (BatchNo (None, 12, 12, 192) 576 conv2d_48[0][0]


batch_normalization_49 (BatchNo (None, 12, 12, 192) 576 conv2d_49[0][0]


activation_40 (Activation) (None, 12, 12, 192) 0 batch_normalization_40[0][0]


activation_43 (Activation) (None, 12, 12, 192) 0 batch_normalization_43[0][0]


activation_48 (Activation) (None, 12, 12, 192) 0 batch_normalization_48[0][0]


activation_49 (Activation) (None, 12, 12, 192) 0 batch_normalization_49[0][0]


mixed5 (Concatenate) (None, 12, 12, 768) 0 activation_40[0][0]
activation_43[0][0]
activation_48[0][0]
activation_49[0][0]


conv2d_54 (Conv2D) (None, 12, 12, 160) 122880 mixed5[0][0]


batch_normalization_54 (BatchNo (None, 12, 12, 160) 480 conv2d_54[0][0]


activation_54 (Activation) (None, 12, 12, 160) 0 batch_normalization_54[0][0]


conv2d_55 (Conv2D) (None, 12, 12, 160) 179200 activation_54[0][0]


batch_normalization_55 (BatchNo (None, 12, 12, 160) 480 conv2d_55[0][0]


activation_55 (Activation) (None, 12, 12, 160) 0 batch_normalization_55[0][0]


conv2d_51 (Conv2D) (None, 12, 12, 160) 122880 mixed5[0][0]


conv2d_56 (Conv2D) (None, 12, 12, 160) 179200 activation_55[0][0]


batch_normalization_51 (BatchNo (None, 12, 12, 160) 480 conv2d_51[0][0]


batch_normalization_56 (BatchNo (None, 12, 12, 160) 480 conv2d_56[0][0]


activation_51 (Activation) (None, 12, 12, 160) 0 batch_normalization_51[0][0]


activation_56 (Activation) (None, 12, 12, 160) 0 batch_normalization_56[0][0]


conv2d_52 (Conv2D) (None, 12, 12, 160) 179200 activation_51[0][0]


conv2d_57 (Conv2D) (None, 12, 12, 160) 179200 activation_56[0][0]


batch_normalization_52 (BatchNo (None, 12, 12, 160) 480 conv2d_52[0][0]


batch_normalization_57 (BatchNo (None, 12, 12, 160) 480 conv2d_57[0][0]


activation_52 (Activation) (None, 12, 12, 160) 0 batch_normalization_52[0][0]


activation_57 (Activation) (None, 12, 12, 160) 0 batch_normalization_57[0][0]


average_pooling2d_5 (AveragePoo (None, 12, 12, 768) 0 mixed5[0][0]


conv2d_50 (Conv2D) (None, 12, 12, 192) 147456 mixed5[0][0]


conv2d_53 (Conv2D) (None, 12, 12, 192) 215040 activation_52[0][0]


conv2d_58 (Conv2D) (None, 12, 12, 192) 215040 activation_57[0][0]


conv2d_59 (Conv2D) (None, 12, 12, 192) 147456 average_pooling2d_5[0][0]


batch_normalization_50 (BatchNo (None, 12, 12, 192) 576 conv2d_50[0][0]


batch_normalization_53 (BatchNo (None, 12, 12, 192) 576 conv2d_53[0][0]


batch_normalization_58 (BatchNo (None, 12, 12, 192) 576 conv2d_58[0][0]


batch_normalization_59 (BatchNo (None, 12, 12, 192) 576 conv2d_59[0][0]


activation_50 (Activation) (None, 12, 12, 192) 0 batch_normalization_50[0][0]


activation_53 (Activation) (None, 12, 12, 192) 0 batch_normalization_53[0][0]


activation_58 (Activation) (None, 12, 12, 192) 0 batch_normalization_58[0][0]


activation_59 (Activation) (None, 12, 12, 192) 0 batch_normalization_59[0][0]


mixed6 (Concatenate) (None, 12, 12, 768) 0 activation_50[0][0]
activation_53[0][0]
activation_58[0][0]
activation_59[0][0]


conv2d_64 (Conv2D) (None, 12, 12, 192) 147456 mixed6[0][0]


batch_normalization_64 (BatchNo (None, 12, 12, 192) 576 conv2d_64[0][0]


activation_64 (Activation) (None, 12, 12, 192) 0 batch_normalization_64[0][0]


conv2d_65 (Conv2D) (None, 12, 12, 192) 258048 activation_64[0][0]


batch_normalization_65 (BatchNo (None, 12, 12, 192) 576 conv2d_65[0][0]


activation_65 (Activation) (None, 12, 12, 192) 0 batch_normalization_65[0][0]


conv2d_61 (Conv2D) (None, 12, 12, 192) 147456 mixed6[0][0]


conv2d_66 (Conv2D) (None, 12, 12, 192) 258048 activation_65[0][0]


batch_normalization_61 (BatchNo (None, 12, 12, 192) 576 conv2d_61[0][0]


batch_normalization_66 (BatchNo (None, 12, 12, 192) 576 conv2d_66[0][0]


activation_61 (Activation) (None, 12, 12, 192) 0 batch_normalization_61[0][0]


activation_66 (Activation) (None, 12, 12, 192) 0 batch_normalization_66[0][0]


conv2d_62 (Conv2D) (None, 12, 12, 192) 258048 activation_61[0][0]


conv2d_67 (Conv2D) (None, 12, 12, 192) 258048 activation_66[0][0]


batch_normalization_62 (BatchNo (None, 12, 12, 192) 576 conv2d_62[0][0]


batch_normalization_67 (BatchNo (None, 12, 12, 192) 576 conv2d_67[0][0]


activation_62 (Activation) (None, 12, 12, 192) 0 batch_normalization_62[0][0]


activation_67 (Activation) (None, 12, 12, 192) 0 batch_normalization_67[0][0]


average_pooling2d_6 (AveragePoo (None, 12, 12, 768) 0 mixed6[0][0]


conv2d_60 (Conv2D) (None, 12, 12, 192) 147456 mixed6[0][0]


conv2d_63 (Conv2D) (None, 12, 12, 192) 258048 activation_62[0][0]


conv2d_68 (Conv2D) (None, 12, 12, 192) 258048 activation_67[0][0]


conv2d_69 (Conv2D) (None, 12, 12, 192) 147456 average_pooling2d_6[0][0]


batch_normalization_60 (BatchNo (None, 12, 12, 192) 576 conv2d_60[0][0]


batch_normalization_63 (BatchNo (None, 12, 12, 192) 576 conv2d_63[0][0]


batch_normalization_68 (BatchNo (None, 12, 12, 192) 576 conv2d_68[0][0]


batch_normalization_69 (BatchNo (None, 12, 12, 192) 576 conv2d_69[0][0]


activation_60 (Activation) (None, 12, 12, 192) 0 batch_normalization_60[0][0]


activation_63 (Activation) (None, 12, 12, 192) 0 batch_normalization_63[0][0]


activation_68 (Activation) (None, 12, 12, 192) 0 batch_normalization_68[0][0]


activation_69 (Activation) (None, 12, 12, 192) 0 batch_normalization_69[0][0]


mixed7 (Concatenate) (None, 12, 12, 768) 0 activation_60[0][0]
activation_63[0][0]
activation_68[0][0]
activation_69[0][0]


conv2d_72 (Conv2D) (None, 12, 12, 192) 147456 mixed7[0][0]


batch_normalization_72 (BatchNo (None, 12, 12, 192) 576 conv2d_72[0][0]


activation_72 (Activation) (None, 12, 12, 192) 0 batch_normalization_72[0][0]


conv2d_73 (Conv2D) (None, 12, 12, 192) 258048 activation_72[0][0]


batch_normalization_73 (BatchNo (None, 12, 12, 192) 576 conv2d_73[0][0]


activation_73 (Activation) (None, 12, 12, 192) 0 batch_normalization_73[0][0]


conv2d_70 (Conv2D) (None, 12, 12, 192) 147456 mixed7[0][0]


conv2d_74 (Conv2D) (None, 12, 12, 192) 258048 activation_73[0][0]


batch_normalization_70 (BatchNo (None, 12, 12, 192) 576 conv2d_70[0][0]


batch_normalization_74 (BatchNo (None, 12, 12, 192) 576 conv2d_74[0][0]


activation_70 (Activation) (None, 12, 12, 192) 0 batch_normalization_70[0][0]


activation_74 (Activation) (None, 12, 12, 192) 0 batch_normalization_74[0][0]


conv2d_71 (Conv2D) (None, 5, 5, 320) 552960 activation_70[0][0]


conv2d_75 (Conv2D) (None, 5, 5, 192) 331776 activation_74[0][0]


batch_normalization_71 (BatchNo (None, 5, 5, 320) 960 conv2d_71[0][0]


batch_normalization_75 (BatchNo (None, 5, 5, 192) 576 conv2d_75[0][0]


activation_71 (Activation) (None, 5, 5, 320) 0 batch_normalization_71[0][0]


activation_75 (Activation) (None, 5, 5, 192) 0 batch_normalization_75[0][0]


max_pooling2d_3 (MaxPooling2D) (None, 5, 5, 768) 0 mixed7[0][0]


mixed8 (Concatenate) (None, 5, 5, 1280) 0 activation_71[0][0]
activation_75[0][0]
max_pooling2d_3[0][0]


conv2d_80 (Conv2D) (None, 5, 5, 448) 573440 mixed8[0][0]


batch_normalization_80 (BatchNo (None, 5, 5, 448) 1344 conv2d_80[0][0]


activation_80 (Activation) (None, 5, 5, 448) 0 batch_normalization_80[0][0]


conv2d_77 (Conv2D) (None, 5, 5, 384) 491520 mixed8[0][0]


conv2d_81 (Conv2D) (None, 5, 5, 384) 1548288 activation_80[0][0]


batch_normalization_77 (BatchNo (None, 5, 5, 384) 1152 conv2d_77[0][0]


batch_normalization_81 (BatchNo (None, 5, 5, 384) 1152 conv2d_81[0][0]


activation_77 (Activation) (None, 5, 5, 384) 0 batch_normalization_77[0][0]


activation_81 (Activation) (None, 5, 5, 384) 0 batch_normalization_81[0][0]


conv2d_78 (Conv2D) (None, 5, 5, 384) 442368 activation_77[0][0]


conv2d_79 (Conv2D) (None, 5, 5, 384) 442368 activation_77[0][0]


conv2d_82 (Conv2D) (None, 5, 5, 384) 442368 activation_81[0][0]


conv2d_83 (Conv2D) (None, 5, 5, 384) 442368 activation_81[0][0]


average_pooling2d_7 (AveragePoo (None, 5, 5, 1280) 0 mixed8[0][0]


conv2d_76 (Conv2D) (None, 5, 5, 320) 409600 mixed8[0][0]


batch_normalization_78 (BatchNo (None, 5, 5, 384) 1152 conv2d_78[0][0]


batch_normalization_79 (BatchNo (None, 5, 5, 384) 1152 conv2d_79[0][0]


batch_normalization_82 (BatchNo (None, 5, 5, 384) 1152 conv2d_82[0][0]


batch_normalization_83 (BatchNo (None, 5, 5, 384) 1152 conv2d_83[0][0]


conv2d_84 (Conv2D) (None, 5, 5, 192) 245760 average_pooling2d_7[0][0]


batch_normalization_76 (BatchNo (None, 5, 5, 320) 960 conv2d_76[0][0]


activation_78 (Activation) (None, 5, 5, 384) 0 batch_normalization_78[0][0]


activation_79 (Activation) (None, 5, 5, 384) 0 batch_normalization_79[0][0]


activation_82 (Activation) (None, 5, 5, 384) 0 batch_normalization_82[0][0]


activation_83 (Activation) (None, 5, 5, 384) 0 batch_normalization_83[0][0]


batch_normalization_84 (BatchNo (None, 5, 5, 192) 576 conv2d_84[0][0]


activation_76 (Activation) (None, 5, 5, 320) 0 batch_normalization_76[0][0]


mixed9_0 (Concatenate) (None, 5, 5, 768) 0 activation_78[0][0]
activation_79[0][0]


concatenate (Concatenate) (None, 5, 5, 768) 0 activation_82[0][0]
activation_83[0][0]


activation_84 (Activation) (None, 5, 5, 192) 0 batch_normalization_84[0][0]


mixed9 (Concatenate) (None, 5, 5, 2048) 0 activation_76[0][0]
mixed9_0[0][0]
concatenate[0][0]
activation_84[0][0]


conv2d_89 (Conv2D) (None, 5, 5, 448) 917504 mixed9[0][0]


batch_normalization_89 (BatchNo (None, 5, 5, 448) 1344 conv2d_89[0][0]


activation_89 (Activation) (None, 5, 5, 448) 0 batch_normalization_89[0][0]


conv2d_86 (Conv2D) (None, 5, 5, 384) 786432 mixed9[0][0]


conv2d_90 (Conv2D) (None, 5, 5, 384) 1548288 activation_89[0][0]


batch_normalization_86 (BatchNo (None, 5, 5, 384) 1152 conv2d_86[0][0]


batch_normalization_90 (BatchNo (None, 5, 5, 384) 1152 conv2d_90[0][0]


activation_86 (Activation) (None, 5, 5, 384) 0 batch_normalization_86[0][0]


activation_90 (Activation) (None, 5, 5, 384) 0 batch_normalization_90[0][0]


conv2d_87 (Conv2D) (None, 5, 5, 384) 442368 activation_86[0][0]


conv2d_88 (Conv2D) (None, 5, 5, 384) 442368 activation_86[0][0]


conv2d_91 (Conv2D) (None, 5, 5, 384) 442368 activation_90[0][0]


conv2d_92 (Conv2D) (None, 5, 5, 384) 442368 activation_90[0][0]


average_pooling2d_8 (AveragePoo (None, 5, 5, 2048) 0 mixed9[0][0]


conv2d_85 (Conv2D) (None, 5, 5, 320) 655360 mixed9[0][0]


batch_normalization_87 (BatchNo (None, 5, 5, 384) 1152 conv2d_87[0][0]


batch_normalization_88 (BatchNo (None, 5, 5, 384) 1152 conv2d_88[0][0]


batch_normalization_91 (BatchNo (None, 5, 5, 384) 1152 conv2d_91[0][0]


batch_normalization_92 (BatchNo (None, 5, 5, 384) 1152 conv2d_92[0][0]


conv2d_93 (Conv2D) (None, 5, 5, 192) 393216 average_pooling2d_8[0][0]


batch_normalization_85 (BatchNo (None, 5, 5, 320) 960 conv2d_85[0][0]


activation_87 (Activation) (None, 5, 5, 384) 0 batch_normalization_87[0][0]


activation_88 (Activation) (None, 5, 5, 384) 0 batch_normalization_88[0][0]


activation_91 (Activation) (None, 5, 5, 384) 0 batch_normalization_91[0][0]


activation_92 (Activation) (None, 5, 5, 384) 0 batch_normalization_92[0][0]


batch_normalization_93 (BatchNo (None, 5, 5, 192) 576 conv2d_93[0][0]


activation_85 (Activation) (None, 5, 5, 320) 0 batch_normalization_85[0][0]


mixed9_1 (Concatenate) (None, 5, 5, 768) 0 activation_87[0][0]
activation_88[0][0]


concatenate_1 (Concatenate) (None, 5, 5, 768) 0 activation_91[0][0]
activation_92[0][0]


activation_93 (Activation) (None, 5, 5, 192) 0 batch_normalization_93[0][0]


mixed10 (Concatenate) (None, 5, 5, 2048) 0 activation_85[0][0]
mixed9_1[0][0]
concatenate_1[0][0]
activation_93[0][0]


flatten (Flatten) (None, 51200) 0 mixed10[0][0]
Dense (Dense) (None, 10) 512010 flatten[0][0]

================================================================================================== Total params: 22,314,794 Trainable params: 512,010 Non-trainable params: 21,802,784

The above Neural Network has around 22 Lakh Parameters. It gives 81% accuracy and 83% validation accuracy for 3 epochs.

Model Evaluation

Accuracy

Screenshot 2021-07-28 132132